Datasets:

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ftopal

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huggingface-datasets

like 0

[ "task_categories:graph-ml", "size_categories:1K<n<10K", "license:cc", "arxiv:2210.02016", "region:us" ]

[ "2210.02016" ]

[]

[]

[ "TAGS\n#task_categories-graph-ml #size_categories-1K<n<10K #license-cc #arxiv-2210.02016 #region-us \n" ]

[ "region:us" ]

[]

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[ "# Dataset Card for Evaluation run of vicgalle/Miqu-6B-truthy\n\n\n\nDataset automatically created during the evaluation run of model vicgalle/Miqu-6B-truthy on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-14T17:59:06.649913(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of vicgalle/Miqu-6B-truthy\n\n\n\nDataset automatically created during the evaluation run of model vicgalle/Miqu-6B-truthy on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-14T17:59:06.649913(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of FelixChao/Capricorn-7B\n\n\n\nDataset automatically created during the evaluation run of model FelixChao/Capricorn-7B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-14T18:16:40.340194(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of FelixChao/Capricorn-7B\n\n\n\nDataset automatically created during the evaluation run of model FelixChao/Capricorn-7B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-14T18:16:40.340194(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"stenotype-eval-dataset-func-type-stripped-v4\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"stenotype-eval-dataset-func-type-stripped-v4\"\n\nMore Information needed" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"Aksharantar\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"Aksharantar\"\n\nMore Information needed" ]

[ "task_categories:summarization", "size_categories:10K<n<100K", "language:uk", "license:cc-by-nc-4.0", "region:us" ]

[]

[ "uk" ]

[ "# Ukrainian News Summarization Dataset", "# Based on shamotskyi/ukr_pravda_2y News Dataset\n\nThis dataset contains news articles from the Ukrainian news website URL, summarized using the Claude Instant summarization model. The dataset is designed to support research in Ukrainian text summarization, news headline generation, and other NLP tasks.", "## Dataset Structure\n\nThe dataset is structured as a CSV file with the following columns:\n\n* text: The full text of the news article.\n* summary: The Claude Instant-generated summary of the news article via AWS Bedrock API", "## Usage Examples\n\nFine-tuning Summarization Models:\n\n\n\nEvaluating Summarization Quality:", "## Creation Process\n\n1. Web Scraping: shamotskyi/ukr_pravda_2y dataset was used as a base.\n2. Summarization: Each article's 'ukr_text' was summarized using the Claude Instant model via AWS Bedrock API.\n3. Dataset Formatting: The data was compiled into a CSV format.", "## Licensing\n\nThis dataset is released under the [CC-BY-NC-4.0]. The rights to the original URL news articles remain with their respective authors.", "## Ethical Considerations\n\n* News article summarization comes with its own ethical concerns. Ensure this dataset is not used to generate misleading or deceptive content.\n* Always consider the potential biases and limitations of Claude Instant as a summarization model.", "## Contributors\n\n* [d0p3]", "## Expanding the Dataset\n\nWe welcome contributions! If you'd like to expand the dataset by adding more articles or summaries from other Ukrainian news sources!" ]

[ "TAGS\n#task_categories-summarization #size_categories-10K<n<100K #language-Ukrainian #license-cc-by-nc-4.0 #region-us \n", "# Ukrainian News Summarization Dataset", "# Based on shamotskyi/ukr_pravda_2y News Dataset\n\nThis dataset contains news articles from the Ukrainian news website URL, summarized using the Claude Instant summarization model. The dataset is designed to support research in Ukrainian text summarization, news headline generation, and other NLP tasks.", "## Dataset Structure\n\nThe dataset is structured as a CSV file with the following columns:\n\n* text: The full text of the news article.\n* summary: The Claude Instant-generated summary of the news article via AWS Bedrock API", "## Usage Examples\n\nFine-tuning Summarization Models:\n\n\n\nEvaluating Summarization Quality:", "## Creation Process\n\n1. Web Scraping: shamotskyi/ukr_pravda_2y dataset was used as a base.\n2. Summarization: Each article's 'ukr_text' was summarized using the Claude Instant model via AWS Bedrock API.\n3. Dataset Formatting: The data was compiled into a CSV format.", "## Licensing\n\nThis dataset is released under the [CC-BY-NC-4.0]. The rights to the original URL news articles remain with their respective authors.", "## Ethical Considerations\n\n* News article summarization comes with its own ethical concerns. Ensure this dataset is not used to generate misleading or deceptive content.\n* Always consider the potential biases and limitations of Claude Instant as a summarization model.", "## Contributors\n\n* [d0p3]", "## Expanding the Dataset\n\nWe welcome contributions! If you'd like to expand the dataset by adding more articles or summaries from other Ukrainian news sources!" ]

[ "region:us" ]

[]

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[]

[ "TAGS\n#region-us \n" ]

[ "arxiv:1903.02741", "region:us" ]

[ "1903.02741" ]

[]

[]

[ "TAGS\n#arxiv-1903.02741 #region-us \n" ]

[ "license:mit", "dna", "variant-effect-prediction", "biology", "genomics", "region:us" ]

[]

[]

[ "# GPN-MSA predictions for all possible SNPs in the human genome (~9 billion)\nFor more information check out our paper and repository.", "## Querying specific variants or genes\n\n- Install the latest tabix: \n In your current conda environment (might be slow):\n \n or in a new conda environment:\n \n- Query a specific region (e.g. BRCA1), from the remote file: \n \n The output has the following columns: \n | chrom | pos | ref | alt | GPN-MSA score | \n and would start like this: \n \n- If you want to do many queries you might want to first download the files locally\n \n and then score:" ]

[ "TAGS\n#license-mit #dna #variant-effect-prediction #biology #genomics #region-us \n", "# GPN-MSA predictions for all possible SNPs in the human genome (~9 billion)\nFor more information check out our paper and repository.", "## Querying specific variants or genes\n\n- Install the latest tabix: \n In your current conda environment (might be slow):\n \n or in a new conda environment:\n \n- Query a specific region (e.g. BRCA1), from the remote file: \n \n The output has the following columns: \n | chrom | pos | ref | alt | GPN-MSA score | \n and would start like this: \n \n- If you want to do many queries you might want to first download the files locally\n \n and then score:" ]

[ "region:us" ]

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[ "# Dataset Card for Evaluation run of bigcode/starcoderbase\n\n\n\nDataset automatically created during the evaluation run of model bigcode/starcoderbase on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-14T19:33:07.504814(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of bigcode/starcoderbase\n\n\n\nDataset automatically created during the evaluation run of model bigcode/starcoderbase on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-14T19:33:07.504814(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Args" ]

[ "TAGS\n#region-us \n", "# Args" ]

[ "region:us" ]

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[ "# Dataset Card for \"ultrafeedback_binarized_1707945637\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"ultrafeedback_binarized_1707945637\"\n\nMore Information needed" ]

[ "region:us" ]

[]

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[ "TAGS\n#region-us \n" ]

[ "region:us" ]

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[ "# Dataset Card for Evaluation run of bigcode/starcoderbase-1b\n\n\n\nDataset automatically created during the evaluation run of model bigcode/starcoderbase-1b on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-14T21:51:42.530406(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of bigcode/starcoderbase-1b\n\n\n\nDataset automatically created during the evaluation run of model bigcode/starcoderbase-1b on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-14T21:51:42.530406(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Args" ]

[ "TAGS\n#region-us \n", "# Args" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"ultrafeedback_binarized_1707947544\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"ultrafeedback_binarized_1707947544\"\n\nMore Information needed" ]

[ "region:us" ]

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[ "# Dataset Card for Evaluation run of bigcode/starcoderbase-3b\n\n\n\nDataset automatically created during the evaluation run of model bigcode/starcoderbase-3b on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-14T22:11:18.391995(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of bigcode/starcoderbase-3b\n\n\n\nDataset automatically created during the evaluation run of model bigcode/starcoderbase-3b on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-14T22:11:18.391995(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "license:apache-2.0", "region:us" ]

[]

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[ "TAGS\n#license-apache-2.0 #region-us \n" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of bigcode/starcoderbase-7b\n\n\n\nDataset automatically created during the evaluation run of model bigcode/starcoderbase-7b on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-14T22:30:37.851656(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of bigcode/starcoderbase-7b\n\n\n\nDataset automatically created during the evaluation run of model bigcode/starcoderbase-7b on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-14T22:30:37.851656(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "size_categories:1K<n<10K", "language:tr", "license:apache-2.0", "region:us" ]

[]

[ "tr" ]

[ "# Description\nThis dataset was created by filtering the aya_dataset by CohereForAI for rows containing Turkish texts.\n\nTraining split: 4046 rows\\\nTest split: 250 rows" ]

[ "TAGS\n#size_categories-1K<n<10K #language-Turkish #license-apache-2.0 #region-us \n", "# Description\nThis dataset was created by filtering the aya_dataset by CohereForAI for rows containing Turkish texts.\n\nTraining split: 4046 rows\\\nTest split: 250 rows" ]

[ "task_categories:question-answering", "task_categories:text-generation", "size_categories:1K<n<10K", "language:en", "license:other", "math", "nvidia", "arxiv:2402.10176", "region:us" ]

[ "2402.10176" ]

[ "en" ]

[ "# OpenMath GSM8K Masked\n\nWe release a *masked* version of the GSM8K solutions.\nThis data can be used to aid synthetic generation of additional solutions for GSM8K dataset\nas it is much less likely to lead to inconsistent reasoning compared to using\nthe original solutions directly.\n\nThis dataset was used to construct OpenMathInstruct-1:\na math instruction tuning dataset with 1.8M problem-solution pairs\ngenerated using permissively licensed Mixtral-8x7B model.\n\nFor details of how the masked solutions were created, see our paper.\n\nYou can re-create this dataset or apply similar techniques to mask solutions for other datasets\nby using our open-sourced code.\n\nIf you find our work useful, please consider citing us!", "## License\n\nThe use of this dataset is governed by the NVIDIA License which permits commercial usage." ]

[ "TAGS\n#task_categories-question-answering #task_categories-text-generation #size_categories-1K<n<10K #language-English #license-other #math #nvidia #arxiv-2402.10176 #region-us \n", "# OpenMath GSM8K Masked\n\nWe release a *masked* version of the GSM8K solutions.\nThis data can be used to aid synthetic generation of additional solutions for GSM8K dataset\nas it is much less likely to lead to inconsistent reasoning compared to using\nthe original solutions directly.\n\nThis dataset was used to construct OpenMathInstruct-1:\na math instruction tuning dataset with 1.8M problem-solution pairs\ngenerated using permissively licensed Mixtral-8x7B model.\n\nFor details of how the masked solutions were created, see our paper.\n\nYou can re-create this dataset or apply similar techniques to mask solutions for other datasets\nby using our open-sourced code.\n\nIf you find our work useful, please consider citing us!", "## License\n\nThe use of this dataset is governed by the NVIDIA License which permits commercial usage." ]

[ "task_categories:question-answering", "task_categories:text-generation", "size_categories:1K<n<10K", "language:en", "license:other", "math", "nvidia", "arxiv:2402.10176", "region:us" ]

[ "2402.10176" ]

[ "en" ]

[ "# OpenMath GSM8K Masked\n\nWe release a *masked* version of the MATH solutions.\nThis data can be used to aid synthetic generation of additional solutions for MATH dataset\nas it is much less likely to lead to inconsistent reasoning compared to using\nthe original solutions directly.\n\nThis dataset was used to construct OpenMathInstruct-1:\na math instruction tuning dataset with 1.8M problem-solution pairs\ngenerated using permissively licensed Mixtral-8x7B model.\n\nFor details of how the masked solutions were created, see our paper.\n\nYou can re-create this dataset or apply similar techniques to mask solutions for other datasets\nby using our open-sourced code.\n\nIf you find our work useful, please consider citing us!", "## License\n\nThe use of this dataset is governed by the NVIDIA License which permits commercial usage." ]

[ "TAGS\n#task_categories-question-answering #task_categories-text-generation #size_categories-1K<n<10K #language-English #license-other #math #nvidia #arxiv-2402.10176 #region-us \n", "# OpenMath GSM8K Masked\n\nWe release a *masked* version of the MATH solutions.\nThis data can be used to aid synthetic generation of additional solutions for MATH dataset\nas it is much less likely to lead to inconsistent reasoning compared to using\nthe original solutions directly.\n\nThis dataset was used to construct OpenMathInstruct-1:\na math instruction tuning dataset with 1.8M problem-solution pairs\ngenerated using permissively licensed Mixtral-8x7B model.\n\nFor details of how the masked solutions were created, see our paper.\n\nYou can re-create this dataset or apply similar techniques to mask solutions for other datasets\nby using our open-sourced code.\n\nIf you find our work useful, please consider citing us!", "## License\n\nThe use of this dataset is governed by the NVIDIA License which permits commercial usage." ]

[ "task_categories:text-generation", "task_categories:question-answering", "size_categories:100K<n<1M", "language:en", "license:cc-by-nc-nd-4.0", "biology", "pytorch", "causal-lm", "region:us" ]

[]

[ "en" ]

[ "# Overview\n\nCell2Sentence is a novel method for adapting large language models to single-cell transcriptomics. \nWe transform single-cell RNA sequencing data into sequences of gene names ordered by expression level, termed \"cell sentences\". \nThis dataset was constructed from the immune tissue dataset in Domínguez et al., \nand it was used to train the Pythia-160m model capable of generating complete cells described in our paper. \nDetails about the Cell2Sentence transformation and preprocessing pipeline can be found in our paper and GitHub repo linked below.\n\nGitHub: <URL \nPaper: <URL \nModel Card: <URL" ]

[ "TAGS\n#task_categories-text-generation #task_categories-question-answering #size_categories-100K<n<1M #language-English #license-cc-by-nc-nd-4.0 #biology #pytorch #causal-lm #region-us \n", "# Overview\n\nCell2Sentence is a novel method for adapting large language models to single-cell transcriptomics. \nWe transform single-cell RNA sequencing data into sequences of gene names ordered by expression level, termed \"cell sentences\". \nThis dataset was constructed from the immune tissue dataset in Domínguez et al., \nand it was used to train the Pythia-160m model capable of generating complete cells described in our paper. \nDetails about the Cell2Sentence transformation and preprocessing pipeline can be found in our paper and GitHub repo linked below.\n\nGitHub: <URL \nPaper: <URL \nModel Card: <URL" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of touqir/Cyrax-7B\n\n\n\nDataset automatically created during the evaluation run of model touqir/Cyrax-7B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-14T23:34:58.336806(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of touqir/Cyrax-7B\n\n\n\nDataset automatically created during the evaluation run of model touqir/Cyrax-7B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-14T23:34:58.336806(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of Xenon1/Zenith-7B-dpo-v1\n\n\n\nDataset automatically created during the evaluation run of model Xenon1/Zenith-7B-dpo-v1 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T00:49:59.820976(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of Xenon1/Zenith-7B-dpo-v1\n\n\n\nDataset automatically created during the evaluation run of model Xenon1/Zenith-7B-dpo-v1 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T00:49:59.820976(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of Xenon1/Zenith-7B-dpo\n\n\n\nDataset automatically created during the evaluation run of model Xenon1/Zenith-7B-dpo on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T00:56:08.608321(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of Xenon1/Zenith-7B-dpo\n\n\n\nDataset automatically created during the evaluation run of model Xenon1/Zenith-7B-dpo on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T00:56:08.608321(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of Josephgflowers/tinyllama-730M-test\n\n\n\nDataset automatically created during the evaluation run of model Josephgflowers/tinyllama-730M-test on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T01:02:27.411834(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of Josephgflowers/tinyllama-730M-test\n\n\n\nDataset automatically created during the evaluation run of model Josephgflowers/tinyllama-730M-test on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T01:02:27.411834(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of BarraHome/Wistral-7B-Instruct-v0.3\n\n\n\nDataset automatically created during the evaluation run of model BarraHome/Wistral-7B-Instruct-v0.3 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T19:11:00.348101(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of BarraHome/Wistral-7B-Instruct-v0.3\n\n\n\nDataset automatically created during the evaluation run of model BarraHome/Wistral-7B-Instruct-v0.3 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T19:11:00.348101(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of Xenon1/Eclipse-7B\n\n\n\nDataset automatically created during the evaluation run of model Xenon1/Eclipse-7B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T01:56:20.654560(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of Xenon1/Eclipse-7B\n\n\n\nDataset automatically created during the evaluation run of model Xenon1/Eclipse-7B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T01:56:20.654560(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "task_categories:question-answering", "size_categories:n<1K", "language:en", "license:apache-2.0", "region:us" ]

[]

[ "en" ]

[ "# Hello Datasets\n\nThis is the dataset used to fine tune fine-tuned-gpt2." ]

[ "TAGS\n#task_categories-question-answering #size_categories-n<1K #language-English #license-apache-2.0 #region-us \n", "# Hello Datasets\n\nThis is the dataset used to fine tune fine-tuned-gpt2." ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"VN-SFT-New\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"VN-SFT-New\"\n\nMore Information needed" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of tyson0420/stack_llama_full\n\n\n\nDataset automatically created during the evaluation run of model tyson0420/stack_llama_full on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T02:39:31.431617(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of tyson0420/stack_llama_full\n\n\n\nDataset automatically created during the evaluation run of model tyson0420/stack_llama_full on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T02:39:31.431617(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of tyson0420/stack_llama-clang\n\n\n\nDataset automatically created during the evaluation run of model tyson0420/stack_llama-clang on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T02:56:08.832354(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of tyson0420/stack_llama-clang\n\n\n\nDataset automatically created during the evaluation run of model tyson0420/stack_llama-clang on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T02:56:08.832354(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "language:en", "region:us" ]

[]

[ "en" ]

[ "# A corpus of rewritten pubmed abstracts\n\nThis corpus contains a 1k example subset from the pubmed corpus and various rewritten versions. The rewritten versions change one aspect of the orginal text and keeps other aspects unchanged as much as possible.\n\n- Paper: Dissecting learning and forgetting in language model finetuning\n\nAnother corpus of rewritten general text is provided here: c4_derived", "### Data Splits\n\n- pubmed: a 1k example subset from the original pubmed corpus\n\n- nonbiomedical: main topic of text changed to nonbiomedical topic\n\n- counerfactual: factuals knowledge in text replaced by incorrect factuals\n\n- casual: style of text changed to a casual style\n\n- rap: style of text changed to a rap style", "## Dataset Creation\n\nText is generated by ChatGPT with corresponding prompts. Refer to the paper for the instructions used to generate text in each derived subsets.\n\nPlease check the terms and conditions of pubmed data here." ]

[ "TAGS\n#language-English #region-us \n", "# A corpus of rewritten pubmed abstracts\n\nThis corpus contains a 1k example subset from the pubmed corpus and various rewritten versions. The rewritten versions change one aspect of the orginal text and keeps other aspects unchanged as much as possible.\n\n- Paper: Dissecting learning and forgetting in language model finetuning\n\nAnother corpus of rewritten general text is provided here: c4_derived", "### Data Splits\n\n- pubmed: a 1k example subset from the original pubmed corpus\n\n- nonbiomedical: main topic of text changed to nonbiomedical topic\n\n- counerfactual: factuals knowledge in text replaced by incorrect factuals\n\n- casual: style of text changed to a casual style\n\n- rap: style of text changed to a rap style", "## Dataset Creation\n\nText is generated by ChatGPT with corresponding prompts. Refer to the paper for the instructions used to generate text in each derived subsets.\n\nPlease check the terms and conditions of pubmed data here." ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"c4_derived\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"c4_derived\"\n\nMore Information needed" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of Yuma42/KangalKhan-Ruby-7B\n\n\n\nDataset automatically created during the evaluation run of model Yuma42/KangalKhan-Ruby-7B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T04:27:32.929090(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of Yuma42/KangalKhan-Ruby-7B\n\n\n\nDataset automatically created during the evaluation run of model Yuma42/KangalKhan-Ruby-7B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T04:27:32.929090(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of DreadPoor/ToppyLake-Bagel-7B-slerp\n\n\n\nDataset automatically created during the evaluation run of model DreadPoor/ToppyLake-Bagel-7B-slerp on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T04:32:24.928446(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of DreadPoor/ToppyLake-Bagel-7B-slerp\n\n\n\nDataset automatically created during the evaluation run of model DreadPoor/ToppyLake-Bagel-7B-slerp on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T04:32:24.928446(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "task_categories:text-classification", "size_categories:10K<n<100K", "language:en", "license:other", "region:us" ]

[]

[ "en" ]

[ "# Dataset Card for Dataset Name\n\nsummary\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.", "## Dataset Details", "### Dataset Description\n\nuse this dataset to train a module\n\n\n\n- Curated by: Le Minh\n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): Llama2\n- License:LLama2", "### Dataset Sources [optional]\n\na\n\n- Repository: github\n- Paper [optional]: \n- Demo [optional]:", "## Uses\n\ntrain llama2 model", "### Direct Use\n\nload it and train", "### Out-of-Scope Use\n\ntext prediction", "## Dataset Structure\n\nID, summary and dialogue", "## Dataset Creation", "### Curation Rationale\n\ntrain LLM", "### Source Data\n\ninternet", "#### Data Collection and Processing\n\nconversation", "#### Who are the source data producers?\n\ncopy from samsum", "### Annotations [optional]", "#### Annotation process\n\ntrain annotators, interannotator statistics, annotation validation, etc. -->", "#### Who are the annotators?\n\nLe Minh", "#### Personal and Sensitive Information\n\nno", "## Bias, Risks, and Limitations\n\nno risk", "### Recommendations\n\ndo not use it\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#task_categories-text-classification #size_categories-10K<n<100K #language-English #license-other #region-us \n", "# Dataset Card for Dataset Name\n\nsummary\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.", "## Dataset Details", "### Dataset Description\n\nuse this dataset to train a module\n\n\n\n- Curated by: Le Minh\n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): Llama2\n- License:LLama2", "### Dataset Sources [optional]\n\na\n\n- Repository: github\n- Paper [optional]: \n- Demo [optional]:", "## Uses\n\ntrain llama2 model", "### Direct Use\n\nload it and train", "### Out-of-Scope Use\n\ntext prediction", "## Dataset Structure\n\nID, summary and dialogue", "## Dataset Creation", "### Curation Rationale\n\ntrain LLM", "### Source Data\n\ninternet", "#### Data Collection and Processing\n\nconversation", "#### Who are the source data producers?\n\ncopy from samsum", "### Annotations [optional]", "#### Annotation process\n\ntrain annotators, interannotator statistics, annotation validation, etc. -->", "#### Who are the annotators?\n\nLe Minh", "#### Personal and Sensitive Information\n\nno", "## Bias, Risks, and Limitations\n\nno risk", "### Recommendations\n\ndo not use it\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "task_categories:feature-extraction", "size_categories:100K<n<1M", "language:en", "license:apache-2.0", "biology", "region:us" ]

[]

[ "en" ]

[ "# Dataset Card for Dataset Name\n\n\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#task_categories-feature-extraction #size_categories-100K<n<1M #language-English #license-apache-2.0 #biology #region-us \n", "# Dataset Card for Dataset Name\n\n\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "language:en", "license:cc-by-nc-4.0", "region:us" ]

[]

[ "en" ]

[]

[ "TAGS\n#language-English #license-cc-by-nc-4.0 #region-us \n" ]

[ "license:llama2", "region:us" ]

[]

[]

[ "# Syiah Kuala University Dataset V1", "## Source \n\n- ULT USK (Unit Layanan Terpadu USK)", "## Content \n\n1. Data QnA bagi Mahasiswa baru", "## Contact \n\n- You Can Contact Me at Email : haryrachmat10@URL" ]

[ "TAGS\n#license-llama2 #region-us \n", "# Syiah Kuala University Dataset V1", "## Source \n\n- ULT USK (Unit Layanan Terpadu USK)", "## Content \n\n1. Data QnA bagi Mahasiswa baru", "## Contact \n\n- You Can Contact Me at Email : haryrachmat10@URL" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"comparisons_20k_regen_labeled_dpo1b1\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"comparisons_20k_regen_labeled_dpo1b1\"\n\nMore Information needed" ]

[ "task_categories:token-classification", "size_categories:n<1K", "language:id", "license:pddl", "region:us" ]

[]

[ "id" ]

[]

[ "TAGS\n#task_categories-token-classification #size_categories-n<1K #language-Indonesian #license-pddl #region-us \n" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of Changgil/k2s3_test_24001\n\n\n\nDataset automatically created during the evaluation run of model Changgil/k2s3_test_24001 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T07:38:41.232311(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of Changgil/k2s3_test_24001\n\n\n\nDataset automatically created during the evaluation run of model Changgil/k2s3_test_24001 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T07:38:41.232311(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of FelixChao/Capricorn-7B-DPO\n\n\n\nDataset automatically created during the evaluation run of model FelixChao/Capricorn-7B-DPO on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T06:20:03.216862(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of FelixChao/Capricorn-7B-DPO\n\n\n\nDataset automatically created during the evaluation run of model FelixChao/Capricorn-7B-DPO on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T06:20:03.216862(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "task_categories:text-generation", "size_categories:1K<n<10K", "language:en", "license:cc-by-sa-4.0", "region:us" ]

[]

[ "en" ]

[ "# Dataset Card for Dataset Name\n\nThis dataset card provides an overview of the Research Phrases Dataset, designed for training and evaluating language models (LLMs) to generate contextually relevant phrases for various sections of research papers, particularly within the fields of biology and bioinformatics. The dataset includes structured inputs with metadata and prompts to guide the model in generating outputs tailored to the specific needs of academic writing.", "### Dataset Description\n\nThe Research Phrases Dataset comprises thousands of phrases structured to assist in the generation of academic content across different sections of research papers. Each entry is designed with a conditional generation approach, incorporating metadata such as the field of study, keywords, and structured prompts. This method aims to enhance the model's ability to produce section-specific text, making it a valuable resource for automating parts of the research writing process.", "## Uses\n\nThe Research Phrases Dataset is intended for direct use in training and evaluating language models geared towards academic writing assistance.", "### Direct Use\n\nIt can be particularly useful in applications such as:\n\nAutomated Writing Tools: Supporting the development of tools that assist researchers in drafting various sections of their papers by providing contextually relevant phrases and sentences.\nEducational Purposes: Aiding in the education of students and early-career researchers in the structuring and writing of academic papers by offering examples of how specific sections can be articulated.\nContent Generation: Facilitating the generation of draft content for research papers, abstracts, and proposals, especially in the fields of biology and bioinformatics." ]

[ "TAGS\n#task_categories-text-generation #size_categories-1K<n<10K #language-English #license-cc-by-sa-4.0 #region-us \n", "# Dataset Card for Dataset Name\n\nThis dataset card provides an overview of the Research Phrases Dataset, designed for training and evaluating language models (LLMs) to generate contextually relevant phrases for various sections of research papers, particularly within the fields of biology and bioinformatics. The dataset includes structured inputs with metadata and prompts to guide the model in generating outputs tailored to the specific needs of academic writing.", "### Dataset Description\n\nThe Research Phrases Dataset comprises thousands of phrases structured to assist in the generation of academic content across different sections of research papers. Each entry is designed with a conditional generation approach, incorporating metadata such as the field of study, keywords, and structured prompts. This method aims to enhance the model's ability to produce section-specific text, making it a valuable resource for automating parts of the research writing process.", "## Uses\n\nThe Research Phrases Dataset is intended for direct use in training and evaluating language models geared towards academic writing assistance.", "### Direct Use\n\nIt can be particularly useful in applications such as:\n\nAutomated Writing Tools: Supporting the development of tools that assist researchers in drafting various sections of their papers by providing contextually relevant phrases and sentences.\nEducational Purposes: Aiding in the education of students and early-career researchers in the structuring and writing of academic papers by offering examples of how specific sections can be articulated.\nContent Generation: Facilitating the generation of draft content for research papers, abstracts, and proposals, especially in the fields of biology and bioinformatics." ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"glaive-code-assist\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"glaive-code-assist\"\n\nMore Information needed" ]

[ "task_categories:text-classification", "task_categories:text-generation", "task_categories:text2text-generation", "task_categories:translation", "size_categories:n>1T", "language:uz", "license:mit", "region:us" ]

[]

[ "uz" ]

[ "# Dataset Card for Dataset Name\n\n\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#task_categories-text-classification #task_categories-text-generation #task_categories-text2text-generation #task_categories-translation #size_categories-n>1T #language-Uzbek #license-mit #region-us \n", "# Dataset Card for Dataset Name\n\n\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "task_categories:text2text-generation", "task_categories:translation", "size_categories:1K<n<10K", "language:lg", "language:en", "license:cc-by-4.0", "medical", "biology", "math", "science", "region:us" ]

[]

[ "lg", "en" ]

[ "# Luganda Sci-Math-Bio Translations\n\nThis dataset contains Luganda and English translations of biologicial, mathematical and scientific terms" ]

[ "TAGS\n#task_categories-text2text-generation #task_categories-translation #size_categories-1K<n<10K #language-Ganda #language-English #license-cc-by-4.0 #medical #biology #math #science #region-us \n", "# Luganda Sci-Math-Bio Translations\n\nThis dataset contains Luganda and English translations of biologicial, mathematical and scientific terms" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of Xenon1/Eclipse-13B-dpo\n\n\n\nDataset automatically created during the evaluation run of model Xenon1/Eclipse-13B-dpo on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T07:17:58.521396(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of Xenon1/Eclipse-13B-dpo\n\n\n\nDataset automatically created during the evaluation run of model Xenon1/Eclipse-13B-dpo on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T07:17:58.521396(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "task_categories:summarization", "size_categories:10K<n<100K", "language:uk", "license:cc-by-nc-4.0", "region:us" ]

[]

[ "uk" ]

[ "# Ukrainian News Summarization Dataset v1.1", "# Based on shamotskyi/ukr_pravda_2y News Dataset\n\nThis dataset contains news articles from the Ukrainian news website URL, summarized using the Gemini Pro model. The dataset is designed to support research in Ukrainian text summarization, news headline generation, and other NLP tasks.", "## Dataset Structure\n\nThe dataset is structured as a CSV file with the following columns:\n\n* text: The full text of the news article.\n* summary: The Gemini Pro generated summary of the news article via Gemini API", "## Usage Examples\n\nFine-tuning Summarization Models:\n\n\n\nEvaluating Summarization Quality:", "## Creation Process\n\n1. Web Scraping: shamotskyi/ukr_pravda_2y dataset was used as a base.\n2. Summarization: Each article's 'ukr_text' was summarized using the Gemini Pro model via Gemini API.\n3. Dataset Formatting: The data was compiled into a CSV format.", "## Licensing\n\nThis dataset is released under the [CC-BY-NC-4.0]. The rights to the original URL news articles remain with their respective authors.", "## Ethical Considerations\n\n* News article summarization comes with its own ethical concerns. Ensure this dataset is not used to generate misleading or deceptive content.\n* Always consider the potential biases and limitations of Gemini Pro as a summarization model.", "## Contributors\n\n* [d0p3]", "## Expanding the Dataset\n\nWe welcome contributions! If you'd like to expand the dataset by adding more articles or summaries from other Ukrainian news sources!" ]

[ "TAGS\n#task_categories-summarization #size_categories-10K<n<100K #language-Ukrainian #license-cc-by-nc-4.0 #region-us \n", "# Ukrainian News Summarization Dataset v1.1", "# Based on shamotskyi/ukr_pravda_2y News Dataset\n\nThis dataset contains news articles from the Ukrainian news website URL, summarized using the Gemini Pro model. The dataset is designed to support research in Ukrainian text summarization, news headline generation, and other NLP tasks.", "## Dataset Structure\n\nThe dataset is structured as a CSV file with the following columns:\n\n* text: The full text of the news article.\n* summary: The Gemini Pro generated summary of the news article via Gemini API", "## Usage Examples\n\nFine-tuning Summarization Models:\n\n\n\nEvaluating Summarization Quality:", "## Creation Process\n\n1. Web Scraping: shamotskyi/ukr_pravda_2y dataset was used as a base.\n2. Summarization: Each article's 'ukr_text' was summarized using the Gemini Pro model via Gemini API.\n3. Dataset Formatting: The data was compiled into a CSV format.", "## Licensing\n\nThis dataset is released under the [CC-BY-NC-4.0]. The rights to the original URL news articles remain with their respective authors.", "## Ethical Considerations\n\n* News article summarization comes with its own ethical concerns. Ensure this dataset is not used to generate misleading or deceptive content.\n* Always consider the potential biases and limitations of Gemini Pro as a summarization model.", "## Contributors\n\n* [d0p3]", "## Expanding the Dataset\n\nWe welcome contributions! If you'd like to expand the dataset by adding more articles or summaries from other Ukrainian news sources!" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of aloobun/Reyna-Mini-1.8B-v0.1\n\n\n\nDataset automatically created during the evaluation run of model aloobun/Reyna-Mini-1.8B-v0.1 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T07:29:36.560907(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of aloobun/Reyna-Mini-1.8B-v0.1\n\n\n\nDataset automatically created during the evaluation run of model aloobun/Reyna-Mini-1.8B-v0.1 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T07:29:36.560907(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"wsd_myriade_avocat\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"wsd_myriade_avocat\"\n\nMore Information needed" ]

[ "region:us" ]

[]

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[ "# Dataset Card for Evaluation run of tyson0420/mixtral_stack_llama\n\n\n\nDataset automatically created during the evaluation run of model tyson0420/mixtral_stack_llama on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T08:21:27.970055(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of tyson0420/mixtral_stack_llama\n\n\n\nDataset automatically created during the evaluation run of model tyson0420/mixtral_stack_llama on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T08:21:27.970055(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[]

[ "TAGS\n#region-us \n" ]

[ "task_categories:question-answering", "task_categories:text-generation", "size_categories:10K<n<100K", "language:bn", "license:apache-2.0", "instruction-finetuning", "bengali", "bangla", "region:us" ]

[]

[ "bn" ]

[ "# Dataset Card for Alpaca-Cleaned-bn\n\n\n\nThis is a cleaned bengali translated version of the original Alpaca Dataset released by Stanford.", "## Uses", "## Dataset Structure" ]

[ "TAGS\n#task_categories-question-answering #task_categories-text-generation #size_categories-10K<n<100K #language-Bengali #license-apache-2.0 #instruction-finetuning #bengali #bangla #region-us \n", "# Dataset Card for Alpaca-Cleaned-bn\n\n\n\nThis is a cleaned bengali translated version of the original Alpaca Dataset released by Stanford.", "## Uses", "## Dataset Structure" ]

[ "region:us" ]

[]

[]

[]

[ "TAGS\n#region-us \n" ]

[ "region:us" ]

[]

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[ "# Sources\n\n* Binary classification for DWT-DCT-SVD watermarks\n* Blind watermark based on DWT-DCT-SVD" ]

[ "TAGS\n#region-us \n", "# Sources\n\n* Binary classification for DWT-DCT-SVD watermarks\n* Blind watermark based on DWT-DCT-SVD" ]

[ "task_categories:text-classification", "size_categories:1K<n<10K", "language:zh", "license:mit", "art", "Spam detection", "region:us" ]

[]

[ "zh" ]

[ "# Description\nThe Spam Douban Movie Reviews Dataset is a collection of movie reviews scraped from Douban, a popular Chinese social networking platform for movie enthusiasts. This dataset consists of reviews that have been manually classified as either spam or genuine by human reviewers. It contains a total of 1,600 data. \nThis dataset is created for our project Spam Movie Reviews Detection through Supervised Learning." ]

[ "TAGS\n#task_categories-text-classification #size_categories-1K<n<10K #language-Chinese #license-mit #art #Spam detection #region-us \n", "# Description\nThe Spam Douban Movie Reviews Dataset is a collection of movie reviews scraped from Douban, a popular Chinese social networking platform for movie enthusiasts. This dataset consists of reviews that have been manually classified as either spam or genuine by human reviewers. It contains a total of 1,600 data. \nThis dataset is created for our project Spam Movie Reviews Detection through Supervised Learning." ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"wsd_myriade_synth_data_id_label_test\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"wsd_myriade_synth_data_id_label_test\"\n\nMore Information needed" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"wsd_myriade_synth_data_id_label_total\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"wsd_myriade_synth_data_id_label_total\"\n\nMore Information needed" ]

[ "task_categories:translation", "size_categories:1K<n<10K", "language:udm", "license:apache-2.0", "region:us" ]

[]

[ "udm" ]

[]

[ "TAGS\n#task_categories-translation #size_categories-1K<n<10K #language-Udmurt #license-apache-2.0 #region-us \n" ]

[ "size_categories:10K<n<100K", "language:ja", "license:mit", "region:us" ]

[]

[ "ja" ]

[]

[ "TAGS\n#size_categories-10K<n<100K #language-Japanese #license-mit #region-us \n" ]

[ "region:us" ]

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[ "# Dataset Card for Evaluation run of Yuma42/KangalKhan-Sapphire-7B\n\n\n\nDataset automatically created during the evaluation run of model Yuma42/KangalKhan-Sapphire-7B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T11:23:46.531546(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of Yuma42/KangalKhan-Sapphire-7B\n\n\n\nDataset automatically created during the evaluation run of model Yuma42/KangalKhan-Sapphire-7B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T11:23:46.531546(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of nlpguy/AlloyIngotNeoX\n\n\n\nDataset automatically created during the evaluation run of model nlpguy/AlloyIngotNeoX on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T11:28:14.890311(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of nlpguy/AlloyIngotNeoX\n\n\n\nDataset automatically created during the evaluation run of model nlpguy/AlloyIngotNeoX on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T11:28:14.890311(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"RomancesTradicionales\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"RomancesTradicionales\"\n\nMore Information needed" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"wsd_myriade_synth_data_id_label_pc2\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"wsd_myriade_synth_data_id_label_pc2\"\n\nMore Information needed" ]

[ "size_categories:10K<n<100K", "language:uk", "license:mit", "arxiv:2306.02707", "arxiv:2301.13688", "region:us" ]

[ "2306.02707", "2301.13688" ]

[ "uk" ]

[ "# Slim Orca(40K) Translated to Ukrainian 🇺🇦", "## Dataset Description\nA Ukrainian language dataset comprising 40,000+ records translated from the SlimOrca dataset. \n\nThis dataset is suitable for various natural language processing tasks.\n\nStay tuned for extended versions of dataset ;)\n\nСлава Україні!", "## Disclaimer\nPrepare data before your usage. There are some errors in texts, so be carefull.", "## How to Use\nThis dataset can be loaded using the Hugging Face Datasets library:\n\nfrom original SlimOrca" ]

[ "TAGS\n#size_categories-10K<n<100K #language-Ukrainian #license-mit #arxiv-2306.02707 #arxiv-2301.13688 #region-us \n", "# Slim Orca(40K) Translated to Ukrainian 🇺🇦", "## Dataset Description\nA Ukrainian language dataset comprising 40,000+ records translated from the SlimOrca dataset. \n\nThis dataset is suitable for various natural language processing tasks.\n\nStay tuned for extended versions of dataset ;)\n\nСлава Україні!", "## Disclaimer\nPrepare data before your usage. There are some errors in texts, so be carefull.", "## How to Use\nThis dataset can be loaded using the Hugging Face Datasets library:\n\nfrom original SlimOrca" ]

[ "region:us" ]

[]

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[ "# Dataset Card for \"samantar1per_cent_merged_with_train_val\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"samantar1per_cent_merged_with_train_val\"\n\nMore Information needed" ]

[ "license:cc-by-nc-nd-4.0", "region:us" ]

[]

[]

[ "# Dataset Description\n\nThis dataset was used to evaluate different models on the masking exercise, measuring how well the different models can recover the original character.", "## Dataset Overview\n\nThe dataset is compiled from the RefSeq database and other sources, focusing on ESKAPE pathogens. The genomic features were sampled randomly, followed by contiguous segmentation. This dataset contains various segments with lengths: [128, 256, 512, 1024]. The segments were randomly selected, and one of the characters was replaced by '*' (masked_segment column) to create a masking task. The reference_segment contains the original, non-replaced nucleotides. We performed 10,000 maskings per set, with a maximum of 2,000 genomic features. Only the genomic features: 'CDS', 'intergenic', 'pseudogene', and 'ncRNA' were considered.", "## Data Fields\n\n- 'reference_segment_id': A mapping of segment identifiers to their respective reference IDs in the database.\n- 'masked_segment': The DNA sequence of the segment with certain positions masked (marked with '*') for prediction or testing purposes.\n- 'position_to_mask': The specific position(s) in the sequence that have been masked, indicated by index numbers.\n- 'masked_segment_id': Unique identifiers assigned to the masked segments. (unique only with respect to length)\n- 'contig_id': Identifier of the contig to which the segment belongs.\n- 'segment_id': Unique identifier for each genomic segment (same as reference segment id).\n- 'strand': The DNA strand of the segment, indicated as '+' (positive) or '-' (negative).\n- 'seq_start': Starting position of the segment within the contig.\n- 'seq_end': Ending position of the segment within the contig.\n- 'segment_start': Starting position of the genomic segment in the sequence.\n- 'segment_end': Ending position of the genomic segment in the sequence.\n- 'label': Category label for the genomic segment (e.g., 'CDS', 'intergenic').\n- 'segment_length': The length of the genomic segment.\n- 'original_segment': The original genomic sequence without any masking.", "## Usage\n\nThis dataset is intended for academic and research purposes. Users are encouraged to use this dataset in the development and evaluation of bioinformatics models, especially those related to genomic studies.", "## Contact Information\n\nFor any questions, feedback, or contributions regarding the datasets or ProkBERT, please feel free to reach out:\n\n- Name: Balázs Ligeti\n- Email: obalasz@URL\n\nWe welcome your input and collaboration to improve our resources and research.\n\n\n\n'''bibtex\n@Article{ProkBERT2024,\n author = {Ligeti, Balázs et al.},\n journal = {Frontiers in Microbiology},\n title = {{ProkBERT} family: genomic language models},\n year = {2024},\n volume = {14},\n URL = {URL\n DOI = {10.3389/fmicb.2023.1331233}\n}" ]

[ "TAGS\n#license-cc-by-nc-nd-4.0 #region-us \n", "# Dataset Description\n\nThis dataset was used to evaluate different models on the masking exercise, measuring how well the different models can recover the original character.", "## Dataset Overview\n\nThe dataset is compiled from the RefSeq database and other sources, focusing on ESKAPE pathogens. The genomic features were sampled randomly, followed by contiguous segmentation. This dataset contains various segments with lengths: [128, 256, 512, 1024]. The segments were randomly selected, and one of the characters was replaced by '*' (masked_segment column) to create a masking task. The reference_segment contains the original, non-replaced nucleotides. We performed 10,000 maskings per set, with a maximum of 2,000 genomic features. Only the genomic features: 'CDS', 'intergenic', 'pseudogene', and 'ncRNA' were considered.", "## Data Fields\n\n- 'reference_segment_id': A mapping of segment identifiers to their respective reference IDs in the database.\n- 'masked_segment': The DNA sequence of the segment with certain positions masked (marked with '*') for prediction or testing purposes.\n- 'position_to_mask': The specific position(s) in the sequence that have been masked, indicated by index numbers.\n- 'masked_segment_id': Unique identifiers assigned to the masked segments. (unique only with respect to length)\n- 'contig_id': Identifier of the contig to which the segment belongs.\n- 'segment_id': Unique identifier for each genomic segment (same as reference segment id).\n- 'strand': The DNA strand of the segment, indicated as '+' (positive) or '-' (negative).\n- 'seq_start': Starting position of the segment within the contig.\n- 'seq_end': Ending position of the segment within the contig.\n- 'segment_start': Starting position of the genomic segment in the sequence.\n- 'segment_end': Ending position of the genomic segment in the sequence.\n- 'label': Category label for the genomic segment (e.g., 'CDS', 'intergenic').\n- 'segment_length': The length of the genomic segment.\n- 'original_segment': The original genomic sequence without any masking.", "## Usage\n\nThis dataset is intended for academic and research purposes. Users are encouraged to use this dataset in the development and evaluation of bioinformatics models, especially those related to genomic studies.", "## Contact Information\n\nFor any questions, feedback, or contributions regarding the datasets or ProkBERT, please feel free to reach out:\n\n- Name: Balázs Ligeti\n- Email: obalasz@URL\n\nWe welcome your input and collaboration to improve our resources and research.\n\n\n\n'''bibtex\n@Article{ProkBERT2024,\n author = {Ligeti, Balázs et al.},\n journal = {Frontiers in Microbiology},\n title = {{ProkBERT} family: genomic language models},\n year = {2024},\n volume = {14},\n URL = {URL\n DOI = {10.3389/fmicb.2023.1331233}\n}" ]

[ "task_categories:text-classification", "size_categories:n<1K", "language:tr", "language:en", "region:us" ]

[]

[ "tr", "en" ]

[ "# Dataset Card for Dataset Name\n\n\n\n\nThis dataset is the translation of the prompt injections from Gandalf by Lakera.\n\nUsing Google's translation API, the dataset was translated from English to Turkish.", "## Uses\n\n\nThis dataset could be used to train a classifier model to detect Prompt Jailbreaking.", "## Bias, Risks, and Limitations\n\n\n\nThe dataset may contain some offensive messages as no content filter was applied." ]

[ "TAGS\n#task_categories-text-classification #size_categories-n<1K #language-Turkish #language-English #region-us \n", "# Dataset Card for Dataset Name\n\n\n\n\nThis dataset is the translation of the prompt injections from Gandalf by Lakera.\n\nUsing Google's translation API, the dataset was translated from English to Turkish.", "## Uses\n\n\nThis dataset could be used to train a classifier model to detect Prompt Jailbreaking.", "## Bias, Risks, and Limitations\n\n\n\nThe dataset may contain some offensive messages as no content filter was applied." ]

[ "license:cc-by-nc-sa-4.0", "region:us" ]

[]

[]

[]

[ "TAGS\n#license-cc-by-nc-sa-4.0 #region-us \n" ]

[ "task_categories:text-classification", "size_categories:1K<n<10K", "language:en", "license:cc-by-4.0", "invoices", "data extraction", "invoice", "FATURA2", "arxiv:2311.11856", "region:us" ]

[ "2311.11856" ]

[ "en" ]

[]

[ "TAGS\n#task_categories-text-classification #size_categories-1K<n<10K #language-English #license-cc-by-4.0 #invoices #data extraction #invoice #FATURA2 #arxiv-2311.11856 #region-us \n" ]

[ "size_categories:n<1K", "language:da", "license:cc0-1.0", "region:us" ]

[]

[ "da" ]

[ "# Dataset Card for \"danish-citizen-tests\"", "## Dataset Description\n\n- Point of Contact: Dan Saattrup Nielsen\n- Size of dataset: 126 KB\n- Repository: URL", "### Dataset Summary\n\nThis dataset contains tests for citizenship (\"indfødsretsprøven\") and permanent residence (\"medborgerskabsprøven\") in Denmark, from the years 2016-2023.", "### Languages\n\nThe dataset is available in Danish ('da').", "## Dataset Structure\n\nAn example from the dataset looks as follows.", "### Data Fields\n\n- 'question': a 'string' feature.\n- 'option_a': a 'string' feature.\n- 'option_b': a 'string' feature.\n- 'option_c': a 'string' feature.\n- 'answer': a 'string' feature.\n- 'test_type': a 'string' feature.\n- 'year': an 'int64' feature.\n- 'version': a 'string' feature.\n- 'question_id': an 'int64' feature.", "## Dataset Creation", "### Curation Rationale\n\nThere is not a publicly available dataset testing the knowledge about the Danish society.", "### Source Data\n\nThese tests are all available as PDFs at this https URL, and extracted using this Python script.", "## Additional Information", "### Dataset Curators\n\nDan Saattrup Nielsen from the The Alexandra\nInstitute", "### Licensing Information\n\nThe dataset is licensed under the CC0\nlicense." ]

[ "TAGS\n#size_categories-n<1K #language-Danish #license-cc0-1.0 #region-us \n", "# Dataset Card for \"danish-citizen-tests\"", "## Dataset Description\n\n- Point of Contact: Dan Saattrup Nielsen\n- Size of dataset: 126 KB\n- Repository: URL", "### Dataset Summary\n\nThis dataset contains tests for citizenship (\"indfødsretsprøven\") and permanent residence (\"medborgerskabsprøven\") in Denmark, from the years 2016-2023.", "### Languages\n\nThe dataset is available in Danish ('da').", "## Dataset Structure\n\nAn example from the dataset looks as follows.", "### Data Fields\n\n- 'question': a 'string' feature.\n- 'option_a': a 'string' feature.\n- 'option_b': a 'string' feature.\n- 'option_c': a 'string' feature.\n- 'answer': a 'string' feature.\n- 'test_type': a 'string' feature.\n- 'year': an 'int64' feature.\n- 'version': a 'string' feature.\n- 'question_id': an 'int64' feature.", "## Dataset Creation", "### Curation Rationale\n\nThere is not a publicly available dataset testing the knowledge about the Danish society.", "### Source Data\n\nThese tests are all available as PDFs at this https URL, and extracted using this Python script.", "## Additional Information", "### Dataset Curators\n\nDan Saattrup Nielsen from the The Alexandra\nInstitute", "### Licensing Information\n\nThe dataset is licensed under the CC0\nlicense." ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"QUIZBOT_AI_DATASET\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"QUIZBOT_AI_DATASET\"\n\nMore Information needed" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of abhishekchohan/SOLAR-10.7B-Instruct-Forest-DPO-v1\n\n\n\nDataset automatically created during the evaluation run of model abhishekchohan/SOLAR-10.7B-Instruct-Forest-DPO-v1 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T16:19:12.135901(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of abhishekchohan/SOLAR-10.7B-Instruct-Forest-DPO-v1\n\n\n\nDataset automatically created during the evaluation run of model abhishekchohan/SOLAR-10.7B-Instruct-Forest-DPO-v1 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T16:19:12.135901(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of yleo/ParrotOgno-7B\n\n\n\nDataset automatically created during the evaluation run of model yleo/ParrotOgno-7B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T16:28:55.072793(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of yleo/ParrotOgno-7B\n\n\n\nDataset automatically created during the evaluation run of model yleo/ParrotOgno-7B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T16:28:55.072793(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of RaduGabriel/SirUkrainian\n\n\n\nDataset automatically created during the evaluation run of model RaduGabriel/SirUkrainian on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T16:52:40.545415(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of RaduGabriel/SirUkrainian\n\n\n\nDataset automatically created during the evaluation run of model RaduGabriel/SirUkrainian on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T16:52:40.545415(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of uukuguy/speechless-thoughts-mistral-7b-v1.0\n\n\n\nDataset automatically created during the evaluation run of model uukuguy/speechless-thoughts-mistral-7b-v1.0 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T17:05:22.470377(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of uukuguy/speechless-thoughts-mistral-7b-v1.0\n\n\n\nDataset automatically created during the evaluation run of model uukuguy/speechless-thoughts-mistral-7b-v1.0 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T17:05:22.470377(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "language:ms", "language:en", "region:us" ]

[]

[ "ms", "en" ]

[ "# Title Context Pairs\n\nAll notebooks at URL" ]

[ "TAGS\n#language-Malay (macrolanguage) #language-English #region-us \n", "# Title Context Pairs\n\nAll notebooks at URL" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"train_ds_noise\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"train_ds_noise\"\n\nMore Information needed" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"test_ds_noise\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"test_ds_noise\"\n\nMore Information needed" ]

[ "size_categories:1K<n<10K", "language:en", "license:apache-2.0", "prompts", "text-to-image", "stable diffusion", "region:us" ]

[]

[ "en" ]

[ "# The dataset of the most popular text-to-image prompts.", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: URL\n- Funded by [optional]: \n- Shared by [optional]: URL\n- License: apache-2.0", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses\n\nFree to use.", "## Dataset Structure\n\nCSV file columns *name* and *count*.", "### Source Data\n\nThe prompts from URL.", "## Dataset Card Contact\n\ndata@URL" ]

[ "TAGS\n#size_categories-1K<n<10K #language-English #license-apache-2.0 #prompts #text-to-image #stable diffusion #region-us \n", "# The dataset of the most popular text-to-image prompts.", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: URL\n- Funded by [optional]: \n- Shared by [optional]: URL\n- License: apache-2.0", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses\n\nFree to use.", "## Dataset Structure\n\nCSV file columns *name* and *count*.", "### Source Data\n\nThe prompts from URL.", "## Dataset Card Contact\n\ndata@URL" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of CorticalStack/mistral-7b-alpaca-sft\n\n\n\nDataset automatically created during the evaluation run of model CorticalStack/mistral-7b-alpaca-sft on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T19:16:07.365309(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of CorticalStack/mistral-7b-alpaca-sft\n\n\n\nDataset automatically created during the evaluation run of model CorticalStack/mistral-7b-alpaca-sft on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-02-15T19:16:07.365309(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"chess_world_lichess_elite\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"chess_world_lichess_elite\"\n\nMore Information needed" ]

[ "language:uk", "license:cc-by-nc-4.0", "arxiv:1511.02301", "region:us" ]

[ "1511.02301" ]

[ "uk" ]

[ "# Dataset Card for Dataset Name\n\nUA-CBT is a dataset inspired by Children's Book Test (URL containing machine-generated (and human-corrected) stories with gaps, and multiple possible options for words to fill the gaps.\n\nThe text is in Ukrainian language, and the options have been inflected to grammatically match the original ones. Gaps are of three types: named entities, common nouns, and verbs.", "## Dataset Details", "### Dataset Description\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?\n\n- Serhii Hamotskyi\n- TODO\n- Mariia Tkachenko\n- Daria Kravets", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#language-Ukrainian #license-cc-by-nc-4.0 #arxiv-1511.02301 #region-us \n", "# Dataset Card for Dataset Name\n\nUA-CBT is a dataset inspired by Children's Book Test (URL containing machine-generated (and human-corrected) stories with gaps, and multiple possible options for words to fill the gaps.\n\nThe text is in Ukrainian language, and the options have been inflected to grammatically match the original ones. Gaps are of three types: named entities, common nouns, and verbs.", "## Dataset Details", "### Dataset Description\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?\n\n- Serhii Hamotskyi\n- TODO\n- Mariia Tkachenko\n- Daria Kravets", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "autotrain", "evaluation", "region:us" ]

[]

[]

[ "# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: autoevaluate/summarization-not-evaluated\n* Dataset: autoevaluate/xsum-sample\n* Config: autoevaluate--xsum-sample\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.", "## Contributions\n\nThanks to @lewtun for evaluating this model." ]

[ "TAGS\n#autotrain #evaluation #region-us \n", "# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: autoevaluate/summarization-not-evaluated\n* Dataset: autoevaluate/xsum-sample\n* Config: autoevaluate--xsum-sample\n* Split: test\n\nTo run new evaluation jobs, visit Hugging Face's automatic model evaluator.", "## Contributions\n\nThanks to @lewtun for evaluating this model." ]

[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]

[]

[]

[ "### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.", "### Raw Text Version", "### Table Version" ]

[ "TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n", "### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.", "### Raw Text Version", "### Table Version" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"c_x86_avx2_extension_filtered\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"c_x86_avx2_extension_filtered\"\n\nMore Information needed" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of wang7776/Mistral-7B-Instruct-v0.2-sparsity-20\n\n\n\nDataset automatically created during the evaluation run of model wang7776/Mistral-7B-Instruct-v0.2-sparsity-20 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-15T10:42:05.147679(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of wang7776/Mistral-7B-Instruct-v0.2-sparsity-20\n\n\n\nDataset automatically created during the evaluation run of model wang7776/Mistral-7B-Instruct-v0.2-sparsity-20 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-15T10:42:05.147679(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of uukuguy/speechless-nl2sql-ds-6.7b\n\n\n\nDataset automatically created during the evaluation run of model uukuguy/speechless-nl2sql-ds-6.7b on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-15T10:49:31.946178(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of uukuguy/speechless-nl2sql-ds-6.7b\n\n\n\nDataset automatically created during the evaluation run of model uukuguy/speechless-nl2sql-ds-6.7b on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-15T10:49:31.946178(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of cloudyu/Qwen-72Bx2-MoE-120B\n\n\n\nDataset automatically created during the evaluation run of model cloudyu/Qwen-72Bx2-MoE-120B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-15T10:51:00.615971(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of cloudyu/Qwen-72Bx2-MoE-120B\n\n\n\nDataset automatically created during the evaluation run of model cloudyu/Qwen-72Bx2-MoE-120B on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-15T10:51:00.615971(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of wang7776/Mistral-7B-Instruct-v0.2-sparsity-30\n\n\n\nDataset automatically created during the evaluation run of model wang7776/Mistral-7B-Instruct-v0.2-sparsity-30 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-15T11:11:23.952137(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of wang7776/Mistral-7B-Instruct-v0.2-sparsity-30\n\n\n\nDataset automatically created during the evaluation run of model wang7776/Mistral-7B-Instruct-v0.2-sparsity-30 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-15T11:11:23.952137(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "size_categories:1M<n<10M", "language:en", "license:cc-by-nc-4.0", "code", "region:us" ]

[]

[ "en" ]

[ "# CommitBench: A Benchmark for Commit Message Generation", "## EXECUTIVE SUMMARY\nWe provide CommitBench as an open-source, reproducible and privacy- and license-aware benchmark for commit message generation. The dataset is gathered from GitHub repositories with licenses that permit redistribution. We provide six programming languages, Java, Python, Go, JavaScript, PHP, and Ruby. The commit messages in natural language are restricted to English, as it is the working language in many software development projects. The dataset has 1,664,590 examples that were generated by using extensive quality-focused filtering techniques (e.g., excluding bot commits). Additionally, we provide a version with longer sequences for benchmarking models with more extended sequence input.", "## CURATION RATIONALE\nWe created this dataset due to quality and legal issues with previous commit message generation datasets. Given a git diff displaying code changes between two file versions, the task is to predict the accompanying commit message describing these changes in natural language. We base our GitHub repository selection on that of a previous dataset, CodeSearchNet, but apply a large number of filtering techniques to improve the data quality and eliminate noise. Due to the original repository selection, we are also restricted to the aforementioned programming languages. It was important to us, however, to provide some number of programming languages to accommodate any changes in the task due to the degree of hardware-relatedness of a language. The dataset is provided as a large CSV file containing all samples. We provide the following fields: Diff, Commit Message, Hash, Project, Split.", "## DOCUMENTATION FOR SOURCE DATASETS\nRepository selection based on CodeSearchNet, which can be found under URL", "## LANGUAGE VARIETIES\nSince GitHub hosts software projects from all over the world, there is no single uniform variety of English used across all commit messages. This means that phrasing can be regional or subject to influences from the programmer's native language. It also means that different spelling conventions may co-exist and that different terms may be used for the same concept. Any model trained on this data should take these factors into account.", "### Overview of split by programming language for CommitBench:\n- Java: 153,119\n- Ruby: 233,710\n- Go: 137,998\n- JavaScript: 373,598\n- Python: 472,469\n- PHP: 294,394", "## SPEAKER DEMOGRAPHIC\nDue to the extremely diverse (geographically, but also socio-economically) backgrounds of the software development community, there is no single demographic the data comes from. Globally, the average software developer tends to be male and has obtained higher education. Due to the anonymous nature of GitHub profiles, gender distribution information cannot be extracted.", "## ANNOTATOR DEMOGRAPHIC\nDue to the automated generation of the dataset, no annotators were used.", "## SPEECH SITUATION AND CHARACTERISTICS\nThe public nature and often business-related creation of the data by the original GitHub users fosters a more neutral, information-focused, and formal language. As it is not uncommon for developers to find the writing of commit messages tedious, there can also be commit messages representing the frustration or boredom of the commit author. While our filtering is supposed to catch these types of messages, there can be some instances still in the dataset.", "## PREPROCESSING AND DATA FORMATTING\nSee our paper for all preprocessing steps. We do not provide the un-processed raw data due to privacy concerns, but it can be obtained via CodeSearchNet or requested from the authors.", "## CAPTURE QUALITY\nWhile our dataset is completely reproducible at the time of writing, there are external dependencies that could restrict this. If GitHub shuts down and someone with a software project in the dataset deletes their repository, there can be instances that are non-reproducible.", "## LIMITATIONS\nWhile our filters are meant to ensure a high quality for each data sample in the dataset, we cannot ensure that only low-quality examples were removed. Similarly, we cannot guarantee that our extensive filtering methods catch all low-quality examples. Some might remain in the dataset. Another limitation of our dataset is the low number of programming languages (there are many more) as well as our focus on English commit messages.", "## METADATA\n- License: Dataset under the CC BY-NC 4.0 license, code under the MIT license", "## DISCLOSURES AND ETHICAL REVIEW\nWhile we put substantial effort into removing privacy-sensitive information, our solutions cannot find 100% of such cases. This means that researchers and anyone using the data need to incorporate their own safeguards to effectively reduce the amount of personal information that can be exposed.", "## ABOUT THIS DOCUMENT\nA data statement is a characterization of a dataset that provides context to allow developers and users to better understand how experimental results might generalize, how software might be appropriately deployed, and what biases might be reflected in systems built on the software.\n\nThis data statement was written based on the template for the Data Statements Version 2 schema. The template was prepared by Angelina McMillan-Major, Emily M. Bender, and Batya Friedman and can be found at URL and was updated from the community Version 1 Markdown template by Leon Derczynski." ]

[ "TAGS\n#size_categories-1M<n<10M #language-English #license-cc-by-nc-4.0 #code #region-us \n", "# CommitBench: A Benchmark for Commit Message Generation", "## EXECUTIVE SUMMARY\nWe provide CommitBench as an open-source, reproducible and privacy- and license-aware benchmark for commit message generation. The dataset is gathered from GitHub repositories with licenses that permit redistribution. We provide six programming languages, Java, Python, Go, JavaScript, PHP, and Ruby. The commit messages in natural language are restricted to English, as it is the working language in many software development projects. The dataset has 1,664,590 examples that were generated by using extensive quality-focused filtering techniques (e.g., excluding bot commits). Additionally, we provide a version with longer sequences for benchmarking models with more extended sequence input.", "## CURATION RATIONALE\nWe created this dataset due to quality and legal issues with previous commit message generation datasets. Given a git diff displaying code changes between two file versions, the task is to predict the accompanying commit message describing these changes in natural language. We base our GitHub repository selection on that of a previous dataset, CodeSearchNet, but apply a large number of filtering techniques to improve the data quality and eliminate noise. Due to the original repository selection, we are also restricted to the aforementioned programming languages. It was important to us, however, to provide some number of programming languages to accommodate any changes in the task due to the degree of hardware-relatedness of a language. The dataset is provided as a large CSV file containing all samples. We provide the following fields: Diff, Commit Message, Hash, Project, Split.", "## DOCUMENTATION FOR SOURCE DATASETS\nRepository selection based on CodeSearchNet, which can be found under URL", "## LANGUAGE VARIETIES\nSince GitHub hosts software projects from all over the world, there is no single uniform variety of English used across all commit messages. This means that phrasing can be regional or subject to influences from the programmer's native language. It also means that different spelling conventions may co-exist and that different terms may be used for the same concept. Any model trained on this data should take these factors into account.", "### Overview of split by programming language for CommitBench:\n- Java: 153,119\n- Ruby: 233,710\n- Go: 137,998\n- JavaScript: 373,598\n- Python: 472,469\n- PHP: 294,394", "## SPEAKER DEMOGRAPHIC\nDue to the extremely diverse (geographically, but also socio-economically) backgrounds of the software development community, there is no single demographic the data comes from. Globally, the average software developer tends to be male and has obtained higher education. Due to the anonymous nature of GitHub profiles, gender distribution information cannot be extracted.", "## ANNOTATOR DEMOGRAPHIC\nDue to the automated generation of the dataset, no annotators were used.", "## SPEECH SITUATION AND CHARACTERISTICS\nThe public nature and often business-related creation of the data by the original GitHub users fosters a more neutral, information-focused, and formal language. As it is not uncommon for developers to find the writing of commit messages tedious, there can also be commit messages representing the frustration or boredom of the commit author. While our filtering is supposed to catch these types of messages, there can be some instances still in the dataset.", "## PREPROCESSING AND DATA FORMATTING\nSee our paper for all preprocessing steps. We do not provide the un-processed raw data due to privacy concerns, but it can be obtained via CodeSearchNet or requested from the authors.", "## CAPTURE QUALITY\nWhile our dataset is completely reproducible at the time of writing, there are external dependencies that could restrict this. If GitHub shuts down and someone with a software project in the dataset deletes their repository, there can be instances that are non-reproducible.", "## LIMITATIONS\nWhile our filters are meant to ensure a high quality for each data sample in the dataset, we cannot ensure that only low-quality examples were removed. Similarly, we cannot guarantee that our extensive filtering methods catch all low-quality examples. Some might remain in the dataset. Another limitation of our dataset is the low number of programming languages (there are many more) as well as our focus on English commit messages.", "## METADATA\n- License: Dataset under the CC BY-NC 4.0 license, code under the MIT license", "## DISCLOSURES AND ETHICAL REVIEW\nWhile we put substantial effort into removing privacy-sensitive information, our solutions cannot find 100% of such cases. This means that researchers and anyone using the data need to incorporate their own safeguards to effectively reduce the amount of personal information that can be exposed.", "## ABOUT THIS DOCUMENT\nA data statement is a characterization of a dataset that provides context to allow developers and users to better understand how experimental results might generalize, how software might be appropriately deployed, and what biases might be reflected in systems built on the software.\n\nThis data statement was written based on the template for the Data Statements Version 2 schema. The template was prepared by Angelina McMillan-Major, Emily M. Bender, and Batya Friedman and can be found at URL and was updated from the community Version 1 Markdown template by Leon Derczynski." ]

[ "task_categories:text-to-image", "size_categories:n<1K", "license:mit", "art", "not-for-all-audiences", "region:us" ]

[]

[]

[ "### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.", "### Raw Text Version", "### Table Version" ]

[ "TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n", "### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.", "### Raw Text Version", "### Table Version" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"code-instructions-ita-dpo-small\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"code-instructions-ita-dpo-small\"\n\nMore Information needed" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of alnrg2arg/test2\n\n\n\nDataset automatically created during the evaluation run of model alnrg2arg/test2 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-15T11:22:11.663514(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of alnrg2arg/test2\n\n\n\nDataset automatically created during the evaluation run of model alnrg2arg/test2 on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-15T11:22:11.663514(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of naseerfaheem/SOLAR-10.7B-Instruct-ties\n\n\n\nDataset automatically created during the evaluation run of model naseerfaheem/SOLAR-10.7B-Instruct-ties on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-15T11:26:12.738490(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Evaluation run of naseerfaheem/SOLAR-10.7B-Instruct-ties\n\n\n\nDataset automatically created during the evaluation run of model naseerfaheem/SOLAR-10.7B-Instruct-ties on the Open LLM Leaderboard.\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:", "## Latest results\n\nThese are the latest results from run 2024-01-15T11:26:12.738490(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):", "## Dataset Details", "### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:", "### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:", "## Uses", "### Direct Use", "### Out-of-Scope Use", "## Dataset Structure", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Data Collection and Processing", "#### Who are the source data producers?", "### Annotations [optional]", "#### Annotation process", "#### Who are the annotators?", "#### Personal and Sensitive Information", "## Bias, Risks, and Limitations", "### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:", "## Glossary [optional]", "## More Information [optional]", "## Dataset Card Authors [optional]", "## Dataset Card Contact" ]

[ "size_categories:n<1K", "language:en", "license:mit", "region:us" ]

[]

[ "en" ]

[]

[ "TAGS\n#size_categories-n<1K #language-English #license-mit #region-us \n" ]

[ "annotations_creators:crowdsourced", "language_creators:crowdsourced", "multilinguality:multilingual", "language:ab", "language:af", "language:am", "language:ar", "language:as", "language:ast", "language:az", "language:ba", "language:bas", "language:be", "language:bg", "language:bn", "language:br", "language:ca", "language:ckb", "language:cnh", "language:cs", "language:cv", "language:cy", "language:da", "language:de", "language:dv", "language:dyu", "language:el", "language:en", "language:eo", "language:es", "language:et", "language:eu", "language:fa", "language:fi", "language:fr", "language:fy", "language:ga", "language:gl", "language:gn", "language:ha", "language:he", "language:hi", "language:hsb", "language:hu", "language:hy", "language:ia", "language:id", "language:ig", "language:is", "language:it", "language:ja", "language:ka", "language:kab", "language:kk", "language:kmr", "language:ko", "language:ky", "language:lg", "language:lij", "language:lo", "language:lt", "language:ltg", "language:lv", "language:mdf", "language:mhr", "language:mk", "language:ml", "language:mn", "language:mr", "language:mrj", "language:mt", "language:myv", "language:nan", "language:ne", "language:nhi", "language:nl", "language:nn", "language:oc", "language:or", "language:os", "language:pa", "language:pl", "language:ps", "language:pt", "language:quy", "language:rm", "language:ro", "language:ru", "language:rw", "language:sah", "language:sat", "language:sc", "language:sk", "language:skr", "language:sl", "language:sq", "language:sr", "language:sv", "language:sw", "language:ta", "language:te", "language:th", "language:ti", "language:tig", "language:tk", "language:tok", "language:tr", "language:tt", "language:tw", "language:ug", "language:uk", "language:ur", "language:uz", "language:vi", "language:vot", "language:yi", "language:yo", "language:yue", "language:zgh", "language:zh", "license:cc0-1.0", "arxiv:1912.06670", "region:us" ]

[ "1912.06670" ]

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[ "# Dataset Card for Common Voice Corpus 16", "## Table of Contents\n- Dataset Description\n - Dataset Summary\n - Supported Tasks and Leaderboards\n - Languages\n- Dataset Structure\n - Data Instances\n - Data Fields\n - Data Splits\n- Dataset Creation\n - Curation Rationale\n - Source Data\n - Annotations\n - Personal and Sensitive Information\n- Considerations for Using the Data\n - Social Impact of Dataset\n - Discussion of Biases\n - Other Known Limitations\n- Additional Information\n - Dataset Curators\n - Licensing Information\n - Citation Information\n - Contributions", "## Dataset Description\n\n- Homepage: URL\n- Repository: URL\n- Paper: URL\n- Leaderboard: URL\n- Point of Contact: Vaibhav Srivastav", "### Dataset Summary\n\nThe Common Voice dataset consists of a unique MP3 and corresponding text file. \nMany of the 30328 recorded hours in the dataset also include demographic metadata like age, sex, and accent \nthat can help improve the accuracy of speech recognition engines.\n\nThe dataset currently consists of 19673 validated hours in 120 languages, but more voices and languages are always added. \nTake a look at the Languages page to request a language or start contributing.", "### Languages", "## How to use\n\nThe 'datasets' library allows you to load and pre-process your dataset in pure Python, at scale. The dataset can be downloaded and prepared in one call to your local drive by using the 'load_dataset' function. \n\nFor example, to download the Hindi config, simply specify the corresponding language config name (i.e., \"hi\" for Hindi):\n\n\nUsing the datasets library, you can also stream the dataset on-the-fly by adding a 'streaming=True' argument to the 'load_dataset' function call. Loading a dataset in streaming mode loads individual samples of the dataset at a time, rather than downloading the entire dataset to disk.\n\n\n*Bonus*: create a PyTorch dataloader directly with your own datasets (local/streamed).", "### Local", "### Streaming\n\n\n\nTo find out more about loading and preparing audio datasets, head over to URL", "### Example scripts\n\nTrain your own CTC or Seq2Seq Automatic Speech Recognition models on Common Voice 16 with 'transformers' - here.", "## Dataset Structure", "### Data Instances\n\nA typical data point comprises the 'path' to the audio file and its 'sentence'. \nAdditional fields include 'accent', 'age', 'client_id', 'up_votes', 'down_votes', 'gender', 'locale' and 'segment'.", "### Data Fields\n\n'client_id' ('string'): An id for which client (voice) made the recording\n\n'path' ('string'): The path to the audio file\n\n'audio' ('dict'): A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling rate. Note that when accessing the audio column: 'dataset[0][\"audio\"]' the audio file is automatically decoded and resampled to 'dataset.features[\"audio\"].sampling_rate'. Decoding and resampling of a large number of audio files might take a significant amount of time. Thus it is important to first query the sample index before the '\"audio\"' column, *i.e.* 'dataset[0][\"audio\"]' should always be preferred over 'dataset[\"audio\"][0]'.\n\n'sentence' ('string'): The sentence the user was prompted to speak\n\n'up_votes' ('int64'): How many upvotes the audio file has received from reviewers\n\n'down_votes' ('int64'): How many downvotes the audio file has received from reviewers\n\n'age' ('string'): The age of the speaker (e.g. 'teens', 'twenties', 'fifties')\n\n'gender' ('string'): The gender of the speaker\n\n'accent' ('string'): Accent of the speaker\n\n'locale' ('string'): The locale of the speaker\n\n'segment' ('string'): Usually an empty field", "### Data Splits\n\nThe speech material has been subdivided into portions for dev, train, test, validated, invalidated, reported and other.\n\nThe validated data is data that has been validated with reviewers and received upvotes that the data is of high quality.\n\nThe invalidated data is data has been invalidated by reviewers\nand received downvotes indicating that the data is of low quality.\n\nThe reported data is data that has been reported, for different reasons.\n\nThe other data is data that has not yet been reviewed.\n\nThe dev, test, train are all data that has been reviewed, deemed of high quality and split into dev, test and train.", "## Data Preprocessing Recommended by Hugging Face\n\nThe following are data preprocessing steps advised by the Hugging Face team. They are accompanied by an example code snippet that shows how to put them to practice. \n\nMany examples in this dataset have trailing quotations marks, e.g _“the cat sat on the mat.“_. These trailing quotation marks do not change the actual meaning of the sentence, and it is near impossible to infer whether a sentence is a quotation or not a quotation from audio data alone. In these cases, it is advised to strip the quotation marks, leaving: _the cat sat on the mat_.\n\nIn addition, the majority of training sentences end in punctuation ( . or ? or ! ), whereas just a small proportion do not. In the dev set, almost all sentences end in punctuation. Thus, it is recommended to append a full-stop ( . ) to the end of the small number of training examples that do not end in punctuation.", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Initial Data Collection and Normalization", "#### Who are the source language producers?", "### Annotations", "#### Annotation process", "#### Who are the annotators?", "### Personal and Sensitive Information\n\nThe dataset consists of people who have donated their voice online. You agree to not attempt to determine the identity of speakers in the Common Voice dataset.", "## Considerations for Using the Data", "### Social Impact of Dataset\n\nThe dataset consists of people who have donated their voice online. You agree to not attempt to determine the identity of speakers in the Common Voice dataset.", "### Discussion of Biases", "### Other Known Limitations", "## Additional Information", "### Dataset Curators", "### Licensing Information\n\nPublic Domain, CC-0" ]

[ "TAGS\n#annotations_creators-crowdsourced #language_creators-crowdsourced #multilinguality-multilingual #language-Abkhazian #language-Afrikaans #language-Amharic #language-Arabic #language-Assamese #language-Asturian #language-Azerbaijani #language-Bashkir #language-Basa (Cameroon) #language-Belarusian #language-Bulgarian #language-Bengali #language-Breton #language-Catalan #language-Central Kurdish #language-Hakha Chin #language-Czech #language-Chuvash #language-Welsh #language-Danish #language-German #language-Dhivehi #language-Dyula #language-Modern Greek (1453-) #language-English #language-Esperanto #language-Spanish #language-Estonian #language-Basque #language-Persian #language-Finnish #language-French #language-Western Frisian #language-Irish #language-Galician #language-Guarani #language-Hausa #language-Hebrew #language-Hindi #language-Upper Sorbian #language-Hungarian #language-Armenian #language-Interlingua (International Auxiliary Language Association) #language-Indonesian #language-Igbo #language-Icelandic #language-Italian #language-Japanese #language-Georgian #language-Kabyle #language-Kazakh #language-Northern Kurdish #language-Korean #language-Kirghiz #language-Ganda #language-Ligurian #language-Lao #language-Lithuanian #language-Latgalian #language-Latvian #language-Moksha #language-Eastern Mari #language-Macedonian #language-Malayalam #language-Mongolian #language-Marathi #language-Western Mari #language-Maltese #language-Erzya #language-Min Nan Chinese #language-Nepali (macrolanguage) #language-Zacatlán-Ahuacatlán-Tepetzintla Nahuatl #language-Dutch #language-Norwegian Nynorsk #language-Occitan (post 1500) #language-Oriya (macrolanguage) #language-Ossetian #language-Panjabi #language-Polish #language-Pushto #language-Portuguese #language-Ayacucho Quechua #language-Romansh #language-Romanian #language-Russian #language-Kinyarwanda #language-Yakut #language-Santali #language-Sardinian #language-Slovak #language-Saraiki #language-Slovenian #language-Albanian #language-Serbian #language-Swedish #language-Swahili (macrolanguage) #language-Tamil #language-Telugu #language-Thai #language-Tigrinya #language-Tigre #language-Turkmen #language-Toki Pona #language-Turkish #language-Tatar #language-Twi #language-Uighur #language-Ukrainian #language-Urdu #language-Uzbek #language-Vietnamese #language-Votic #language-Yiddish #language-Yoruba #language-Yue Chinese #language-Standard Moroccan Tamazight #language-Chinese #license-cc0-1.0 #arxiv-1912.06670 #region-us \n", "# Dataset Card for Common Voice Corpus 16", "## Table of Contents\n- Dataset Description\n - Dataset Summary\n - Supported Tasks and Leaderboards\n - Languages\n- Dataset Structure\n - Data Instances\n - Data Fields\n - Data Splits\n- Dataset Creation\n - Curation Rationale\n - Source Data\n - Annotations\n - Personal and Sensitive Information\n- Considerations for Using the Data\n - Social Impact of Dataset\n - Discussion of Biases\n - Other Known Limitations\n- Additional Information\n - Dataset Curators\n - Licensing Information\n - Citation Information\n - Contributions", "## Dataset Description\n\n- Homepage: URL\n- Repository: URL\n- Paper: URL\n- Leaderboard: URL\n- Point of Contact: Vaibhav Srivastav", "### Dataset Summary\n\nThe Common Voice dataset consists of a unique MP3 and corresponding text file. \nMany of the 30328 recorded hours in the dataset also include demographic metadata like age, sex, and accent \nthat can help improve the accuracy of speech recognition engines.\n\nThe dataset currently consists of 19673 validated hours in 120 languages, but more voices and languages are always added. \nTake a look at the Languages page to request a language or start contributing.", "### Languages", "## How to use\n\nThe 'datasets' library allows you to load and pre-process your dataset in pure Python, at scale. The dataset can be downloaded and prepared in one call to your local drive by using the 'load_dataset' function. \n\nFor example, to download the Hindi config, simply specify the corresponding language config name (i.e., \"hi\" for Hindi):\n\n\nUsing the datasets library, you can also stream the dataset on-the-fly by adding a 'streaming=True' argument to the 'load_dataset' function call. Loading a dataset in streaming mode loads individual samples of the dataset at a time, rather than downloading the entire dataset to disk.\n\n\n*Bonus*: create a PyTorch dataloader directly with your own datasets (local/streamed).", "### Local", "### Streaming\n\n\n\nTo find out more about loading and preparing audio datasets, head over to URL", "### Example scripts\n\nTrain your own CTC or Seq2Seq Automatic Speech Recognition models on Common Voice 16 with 'transformers' - here.", "## Dataset Structure", "### Data Instances\n\nA typical data point comprises the 'path' to the audio file and its 'sentence'. \nAdditional fields include 'accent', 'age', 'client_id', 'up_votes', 'down_votes', 'gender', 'locale' and 'segment'.", "### Data Fields\n\n'client_id' ('string'): An id for which client (voice) made the recording\n\n'path' ('string'): The path to the audio file\n\n'audio' ('dict'): A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling rate. Note that when accessing the audio column: 'dataset[0][\"audio\"]' the audio file is automatically decoded and resampled to 'dataset.features[\"audio\"].sampling_rate'. Decoding and resampling of a large number of audio files might take a significant amount of time. Thus it is important to first query the sample index before the '\"audio\"' column, *i.e.* 'dataset[0][\"audio\"]' should always be preferred over 'dataset[\"audio\"][0]'.\n\n'sentence' ('string'): The sentence the user was prompted to speak\n\n'up_votes' ('int64'): How many upvotes the audio file has received from reviewers\n\n'down_votes' ('int64'): How many downvotes the audio file has received from reviewers\n\n'age' ('string'): The age of the speaker (e.g. 'teens', 'twenties', 'fifties')\n\n'gender' ('string'): The gender of the speaker\n\n'accent' ('string'): Accent of the speaker\n\n'locale' ('string'): The locale of the speaker\n\n'segment' ('string'): Usually an empty field", "### Data Splits\n\nThe speech material has been subdivided into portions for dev, train, test, validated, invalidated, reported and other.\n\nThe validated data is data that has been validated with reviewers and received upvotes that the data is of high quality.\n\nThe invalidated data is data has been invalidated by reviewers\nand received downvotes indicating that the data is of low quality.\n\nThe reported data is data that has been reported, for different reasons.\n\nThe other data is data that has not yet been reviewed.\n\nThe dev, test, train are all data that has been reviewed, deemed of high quality and split into dev, test and train.", "## Data Preprocessing Recommended by Hugging Face\n\nThe following are data preprocessing steps advised by the Hugging Face team. They are accompanied by an example code snippet that shows how to put them to practice. \n\nMany examples in this dataset have trailing quotations marks, e.g _“the cat sat on the mat.“_. These trailing quotation marks do not change the actual meaning of the sentence, and it is near impossible to infer whether a sentence is a quotation or not a quotation from audio data alone. In these cases, it is advised to strip the quotation marks, leaving: _the cat sat on the mat_.\n\nIn addition, the majority of training sentences end in punctuation ( . or ? or ! ), whereas just a small proportion do not. In the dev set, almost all sentences end in punctuation. Thus, it is recommended to append a full-stop ( . ) to the end of the small number of training examples that do not end in punctuation.", "## Dataset Creation", "### Curation Rationale", "### Source Data", "#### Initial Data Collection and Normalization", "#### Who are the source language producers?", "### Annotations", "#### Annotation process", "#### Who are the annotators?", "### Personal and Sensitive Information\n\nThe dataset consists of people who have donated their voice online. You agree to not attempt to determine the identity of speakers in the Common Voice dataset.", "## Considerations for Using the Data", "### Social Impact of Dataset\n\nThe dataset consists of people who have donated their voice online. You agree to not attempt to determine the identity of speakers in the Common Voice dataset.", "### Discussion of Biases", "### Other Known Limitations", "## Additional Information", "### Dataset Curators", "### Licensing Information\n\nPublic Domain, CC-0" ]