Datasets:

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ftopal

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huggingface-datasets

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[ "# Dataset Card for Evaluation run of jingyeom/KoSoLAR-10.7B-v0.2_1.4_dedup\n\n\n\nDataset automatically created during the evaluation run of model jingyeom/KoSoLAR-10.7B-v0.2_1.4_dedup 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 2024-02-12T08:24:49.664707(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 jingyeom/KoSoLAR-10.7B-v0.2_1.4_dedup\n\n\n\nDataset automatically created during the evaluation run of model jingyeom/KoSoLAR-10.7B-v0.2_1.4_dedup 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 2024-02-12T08:24:49.664707(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" ]

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[ "# Dataset Card for Evaluation run of eren23/dpo-binarized-NeutrixOmnibe-7B\n\n\n\nDataset automatically created during the evaluation run of model eren23/dpo-binarized-NeutrixOmnibe-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 2024-02-12T08:32:59.622106(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 eren23/dpo-binarized-NeutrixOmnibe-7B\n\n\n\nDataset automatically created during the evaluation run of model eren23/dpo-binarized-NeutrixOmnibe-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 2024-02-12T08:32:59.622106(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" ]

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[ "# Dataset Card for Evaluation run of OpenBuddy/openbuddy-mixtral-7bx8-v18.1-32k\n\n\n\nDataset automatically created during the evaluation run of model OpenBuddy/openbuddy-mixtral-7bx8-v18.1-32k 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 2024-02-12T08:49:35.524384(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 OpenBuddy/openbuddy-mixtral-7bx8-v18.1-32k\n\n\n\nDataset automatically created during the evaluation run of model OpenBuddy/openbuddy-mixtral-7bx8-v18.1-32k 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 2024-02-12T08:49:35.524384(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" ]

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

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

[ "task_categories:text2text-generation", "size_categories:10K<n<100K", "language:id", "corpus", "indonesia", "text", "parquet", "region:us" ]

[]

[ "id" ]

[ "# Indonesian Corpus", "## Description\nThis dataset contains a corpus in the Indonesian language taken from Korpus Indonesia, provided by the Ministry of Education and Culture of the Republic of Indonesia. The corpus is a collection of text in sentence format covering various fields of study, such as Social, Health, Literature, Opinion, Sports, Culture, and others.", "## Contents\nThe dataset consists of texts in the Indonesian language grouped based on specific fields of study or topics. Each text is a collection of sentences sourced from the aforementioned provider.", "## Usage\nThis dataset can be used for various research and development purposes in the field of natural language processing (NLP), text analysis, text classification, and other research that requires text data in the Indonesian language.", "## License\nThe dataset is retrieved from Korpus Indonesia provided by the Ministry of Education and Culture of the Republic of Indonesia. Please make sure to check and comply with the applicable licensing terms from the original source.", "## References\nFor more information about Korpus Indonesia, please visit URL" ]

[ "TAGS\n#task_categories-text2text-generation #size_categories-10K<n<100K #language-Indonesian #corpus #indonesia #text #parquet #region-us \n", "# Indonesian Corpus", "## Description\nThis dataset contains a corpus in the Indonesian language taken from Korpus Indonesia, provided by the Ministry of Education and Culture of the Republic of Indonesia. The corpus is a collection of text in sentence format covering various fields of study, such as Social, Health, Literature, Opinion, Sports, Culture, and others.", "## Contents\nThe dataset consists of texts in the Indonesian language grouped based on specific fields of study or topics. Each text is a collection of sentences sourced from the aforementioned provider.", "## Usage\nThis dataset can be used for various research and development purposes in the field of natural language processing (NLP), text analysis, text classification, and other research that requires text data in the Indonesian language.", "## License\nThe dataset is retrieved from Korpus Indonesia provided by the Ministry of Education and Culture of the Republic of Indonesia. Please make sure to check and comply with the applicable licensing terms from the original source.", "## References\nFor more information about Korpus Indonesia, please visit URL" ]

[ "region:us" ]

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[ "# Dataset Card for \"domsdatabasen\"", "## Dataset Description\n\n- Point of Contact: Oliver Kinch\n- Size of dataset: 199 MB", "### Dataset Summary\n\nDomsdatabasen is a database where you can find and read selected judgments delivered by the Danish Courts. \n\nEach judgment/case consists of tabular data and a case-descriptive PDF. This dataset collects all these cases, with each sample describing a specific judgment/case.\n\nThe PDFs are anonymized to protect sensitive information. Therefore, each sample includes two text versions: \n- 'text_anon' (with anonymization tags: \\<anonym\\>\"Some sensitive text\"\\</anonym\\>).\n- 'text' (without anonymization tags).\n\n'text_anon' is read with Easyocr.\n\n'text' is read with Easyocr or Tika-python \ndepending on the PDF and the anonymization method used.\n\n'text_anon' will be empty if no anonymization is detected in the PDF.", "### Languages\n\nThe dataset is available in Danish ('da').", "## Dataset Structure\n\nAn example from the dataset looks as follows.", "### Data Fields\n\n- 'case_id': a 'string' feature.\n- 'tabular_data': a 'dict' feature.\n- 'text': a 'string' feature.\n- 'text_anon': a 'string' feature.\n- 'text_len': an 'int' feature.\n- 'text_anon_len': an 'int' feature.", "### Dataset Statistics", "#### Size of dataset\n\nWith the PDF texts being provided in two versions, 'text' and 'text_anon', the total size of all PDF texts is approximately ~199//2 MB.", "#### Number of samples\n\n- 3919", "#### PDF Text Length Distribution\n\nStatistics based on 'text'.\n\n- Minimum length: 192\n- Maximum length: 2101736\n\n!image/png", "## Potential Dataset Issues\n\nSee open issues.", "## Dataset Creation", "### Curation Rationale\n\nThere are not many large-scale law datasets in Danish.", "### Source Data\n\nThe dataset has been scraped from Domsdatabasen.", "## Additional Information", "### Dataset Curators\n\nOliver Kinch from the The Alexandra\nInstitute", "### Licensing Information\n\nThe dataset is licensed under the CC0\nlicense." ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"domsdatabasen\"", "## Dataset Description\n\n- Point of Contact: Oliver Kinch\n- Size of dataset: 199 MB", "### Dataset Summary\n\nDomsdatabasen is a database where you can find and read selected judgments delivered by the Danish Courts. \n\nEach judgment/case consists of tabular data and a case-descriptive PDF. This dataset collects all these cases, with each sample describing a specific judgment/case.\n\nThe PDFs are anonymized to protect sensitive information. Therefore, each sample includes two text versions: \n- 'text_anon' (with anonymization tags: \\<anonym\\>\"Some sensitive text\"\\</anonym\\>).\n- 'text' (without anonymization tags).\n\n'text_anon' is read with Easyocr.\n\n'text' is read with Easyocr or Tika-python \ndepending on the PDF and the anonymization method used.\n\n'text_anon' will be empty if no anonymization is detected in the PDF.", "### Languages\n\nThe dataset is available in Danish ('da').", "## Dataset Structure\n\nAn example from the dataset looks as follows.", "### Data Fields\n\n- 'case_id': a 'string' feature.\n- 'tabular_data': a 'dict' feature.\n- 'text': a 'string' feature.\n- 'text_anon': a 'string' feature.\n- 'text_len': an 'int' feature.\n- 'text_anon_len': an 'int' feature.", "### Dataset Statistics", "#### Size of dataset\n\nWith the PDF texts being provided in two versions, 'text' and 'text_anon', the total size of all PDF texts is approximately ~199//2 MB.", "#### Number of samples\n\n- 3919", "#### PDF Text Length Distribution\n\nStatistics based on 'text'.\n\n- Minimum length: 192\n- Maximum length: 2101736\n\n!image/png", "## Potential Dataset Issues\n\nSee open issues.", "## Dataset Creation", "### Curation Rationale\n\nThere are not many large-scale law datasets in Danish.", "### Source Data\n\nThe dataset has been scraped from Domsdatabasen.", "## Additional Information", "### Dataset Curators\n\nOliver Kinch from the The Alexandra\nInstitute", "### Licensing Information\n\nThe dataset is licensed under the CC0\nlicense." ]

[ "region:us" ]

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[ "# Dataset Card for \"wsd_myriade_synth_data_v1\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"wsd_myriade_synth_data_v1\"\n\nMore Information needed" ]

[ "region:us" ]

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[ "# Dataset Card for \"wsd_myriade_synth_data_v2\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"wsd_myriade_synth_data_v2\"\n\nMore Information needed" ]

[ "task_categories:feature-extraction", "task_categories:question-answering", "language:da", "license:unknown", "region:us" ]

[]

[ "da" ]

[ "# ELI5 question-answer pairs in Danish", "## About\n\nThis dataset is a version of the ELI5 question-answer pairs dataset machine-translated from English to Danish (link to original dataset).\n\nMachine translation is performed using the Helsinki NLP English-to-Danish OPUS-MT model.\n\nThe dataset contains ~209k question-answer pairs and can be used to train embedding and question-answer models. Each pair consists of one question ('query') and one passage containing the answer ('passage').", "## Usage\n\nUsing the HuggingFace datasets library:" ]

[ "TAGS\n#task_categories-feature-extraction #task_categories-question-answering #language-Danish #license-unknown #region-us \n", "# ELI5 question-answer pairs in Danish", "## About\n\nThis dataset is a version of the ELI5 question-answer pairs dataset machine-translated from English to Danish (link to original dataset).\n\nMachine translation is performed using the Helsinki NLP English-to-Danish OPUS-MT model.\n\nThe dataset contains ~209k question-answer pairs and can be used to train embedding and question-answer models. Each pair consists of one question ('query') and one passage containing the answer ('passage').", "## Usage\n\nUsing the HuggingFace datasets library:" ]

[ "region:us" ]

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[ "# Dataset Card for Evaluation run of TeeZee/DarkForest-20B-v1.2\n\n\n\nDataset automatically created during the evaluation run of model TeeZee/DarkForest-20B-v1.2 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 2024-02-12T09:58:29.626269(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 TeeZee/DarkForest-20B-v1.2\n\n\n\nDataset automatically created during the evaluation run of model TeeZee/DarkForest-20B-v1.2 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 2024-02-12T09:58:29.626269(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:feature-extraction", "task_categories:question-answering", "language:da", "license:cc-by-sa-4.0", "region:us" ]

[]

[ "da" ]

[ "# SQuAD question-answer pairs in Danish", "## About\n\nThis dataset is a version of the SQuAD question-answer pairs dataset machine-translated from English to Danish (link to original dataset).\n\nMachine translation is performed using the Helsinki NLP English-to-Danish OPUS-MT model.\n\nThe dataset contains ~87k question-answer pairs and can be used to train embedding and question-answer models. Each pair consists of one question ('query') and one passage containing the answer ('passage').", "## Usage\n\nUsing the HuggingFace datasets library:" ]

[ "TAGS\n#task_categories-feature-extraction #task_categories-question-answering #language-Danish #license-cc-by-sa-4.0 #region-us \n", "# SQuAD question-answer pairs in Danish", "## About\n\nThis dataset is a version of the SQuAD question-answer pairs dataset machine-translated from English to Danish (link to original dataset).\n\nMachine translation is performed using the Helsinki NLP English-to-Danish OPUS-MT model.\n\nThe dataset contains ~87k question-answer pairs and can be used to train embedding and question-answer models. Each pair consists of one question ('query') and one passage containing the answer ('passage').", "## Usage\n\nUsing the HuggingFace datasets library:" ]

[ "region:us" ]

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[ "# Dataset Card for Evaluation run of Radu1999/Mistral-Instruct-Ukrainian-slerp\n\n\n\nDataset automatically created during the evaluation run of model Radu1999/Mistral-Instruct-Ukrainian-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 2024-02-12T11:11:52.976201(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 Radu1999/Mistral-Instruct-Ukrainian-slerp\n\n\n\nDataset automatically created during the evaluation run of model Radu1999/Mistral-Instruct-Ukrainian-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 2024-02-12T11:11:52.976201(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" ]

[ "region:us" ]

[]

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[ "# Dataset Card for Evaluation run of liminerity/Omningotex-7b-slerp\n\n\n\nDataset automatically created during the evaluation run of model liminerity/Omningotex-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 2024-02-12T12:08:20.064811(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 liminerity/Omningotex-7b-slerp\n\n\n\nDataset automatically created during the evaluation run of model liminerity/Omningotex-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 2024-02-12T12:08:20.064811(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:1M<n<10M", "language:ka", "license:mit", "region:us" ]

[]

[ "ka" ]

[ "# Georgian-Homonym-Disambiguation\nThis repository contains all the datasets for the Georgian homonym disambiguation task.\n\nFor more specific details you can read my <a href=\"URL", "## Dataset\nAt this point I've considered only the homonym: \"ბარი\" and it's different grammatical forms obtaining 7522 sentences.\n\nThe \"dataset.parquet\" includes:\n\n- 763 sentences using \"ბარი\" as a \"shovel\" labaled with 0\n- 1846 sentences using \"ბარი\" as a \"lowland\" labeld with 1\n- 3320 sentences using \"ბარი\" as a \"cafe\" labeled with 2 \n- 1593 sentences where the homonym is used in a different context, labeled with 3 (Although these sentences could be further classified by the definitions of the homonyms, for this project I've ignored other usages).\n\nthe column 'homonym_index' contains the index of the homonym in the sentence, that is, the index of the word which is the homonym.\n\nThe \"full-homonym-sentences-ბარ.txt\" includes the sentences which contain the homonym \"ბარი\" and it's various grammatical forms. These sentences were limited to a\nmaximum length of 13 words, with the homonym positioned in the middle of each sentence. They are around 28000 and are not labelled." ]

[ "TAGS\n#task_categories-text-classification #size_categories-1M<n<10M #language-Georgian #license-mit #region-us \n", "# Georgian-Homonym-Disambiguation\nThis repository contains all the datasets for the Georgian homonym disambiguation task.\n\nFor more specific details you can read my <a href=\"URL", "## Dataset\nAt this point I've considered only the homonym: \"ბარი\" and it's different grammatical forms obtaining 7522 sentences.\n\nThe \"dataset.parquet\" includes:\n\n- 763 sentences using \"ბარი\" as a \"shovel\" labaled with 0\n- 1846 sentences using \"ბარი\" as a \"lowland\" labeld with 1\n- 3320 sentences using \"ბარი\" as a \"cafe\" labeled with 2 \n- 1593 sentences where the homonym is used in a different context, labeled with 3 (Although these sentences could be further classified by the definitions of the homonyms, for this project I've ignored other usages).\n\nthe column 'homonym_index' contains the index of the homonym in the sentence, that is, the index of the word which is the homonym.\n\nThe \"full-homonym-sentences-ბარ.txt\" includes the sentences which contain the homonym \"ბარი\" and it's various grammatical forms. These sentences were limited to a\nmaximum length of 13 words, with the homonym positioned in the middle of each sentence. They are around 28000 and are not labelled." ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"test_dataset-0212\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"test_dataset-0212\"\n\nMore Information needed" ]

[ "region:us" ]

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[]

[ "# Dataset Card for Evaluation run of paulml/NMTOB-7B\n\n\n\nDataset automatically created during the evaluation run of model paulml/NMTOB-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 2024-02-12T12:41:06.200570(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 paulml/NMTOB-7B\n\n\n\nDataset automatically created during the evaluation run of model paulml/NMTOB-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 2024-02-12T12:41:06.200570(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 \"TestDataset-0212-1\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"TestDataset-0212-1\"\n\nMore Information needed" ]

[ "region:us" ]

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[]

[ "# Dataset Card for Evaluation run of paulml/DPOB-NMTOB-7B\n\n\n\nDataset automatically created during the evaluation run of model paulml/DPOB-NMTOB-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 2024-02-12T13:03:38.568467(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 paulml/DPOB-NMTOB-7B\n\n\n\nDataset automatically created during the evaluation run of model paulml/DPOB-NMTOB-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 2024-02-12T13:03:38.568467(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 \"live_ATC_GTI8938\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"live_ATC_GTI8938\"\n\nMore Information needed" ]

[ "region:us" ]

[]

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

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

[ "task_categories:question-answering", "size_categories:100K<n<1M", "language:da", "license:mit", "region:us" ]

[]

[ "da" ]

[ "# Dataset\n\nThis is a translated version of a subset from OpenHermes. Coding tasks and word-play such as anagrams have been removed.\n\nIt has been translated using SeamlessM4T v2 T2T." ]

[ "TAGS\n#task_categories-question-answering #size_categories-100K<n<1M #language-Danish #license-mit #region-us \n", "# Dataset\n\nThis is a translated version of a subset from OpenHermes. Coding tasks and word-play such as anagrams have been removed.\n\nIt has been translated using SeamlessM4T v2 T2T." ]

[ "region:us" ]

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[ "# chatml-OpenHermes2.5-dpo-binarized-alpha\n\nThis is a DPO dataset based on argilla/OpenHermes2.5-dpo-binarized-alpha. It implements the following features:\n\n* ChatML format: you can directly use this dataset without the need to apply a chat template.\n* Filter out low scores: removed samples with delta scores < 1 (530 in the training set, 66 in the test set).\n* Curriculum learning: sort the dataset by the 'delta_score' column in descending order.", "## Code\n\nCode to reproduce this dataset:" ]

[ "TAGS\n#region-us \n", "# chatml-OpenHermes2.5-dpo-binarized-alpha\n\nThis is a DPO dataset based on argilla/OpenHermes2.5-dpo-binarized-alpha. It implements the following features:\n\n* ChatML format: you can directly use this dataset without the need to apply a chat template.\n* Filter out low scores: removed samples with delta scores < 1 (530 in the training set, 66 in the test set).\n* Curriculum learning: sort the dataset by the 'delta_score' column in descending order.", "## Code\n\nCode to reproduce this dataset:" ]

[ "region:us" ]

[]

[]

[]

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

[ "region:us" ]

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[ "# Dataset Card for Evaluation run of eren23/merged-dpo-binarized-NeutrixOmnibe-7B\n\n\n\nDataset automatically created during the evaluation run of model eren23/merged-dpo-binarized-NeutrixOmnibe-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 2024-02-12T13:35:30.829046(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 eren23/merged-dpo-binarized-NeutrixOmnibe-7B\n\n\n\nDataset automatically created during the evaluation run of model eren23/merged-dpo-binarized-NeutrixOmnibe-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 2024-02-12T13:35:30.829046(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" ]

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[]

[ "# Dataset Card for Evaluation run of AbacusResearch/haLLAwa2\n\n\n\nDataset automatically created during the evaluation run of model AbacusResearch/haLLAwa2 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 2024-02-12T13:50:58.490257(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 AbacusResearch/haLLAwa2\n\n\n\nDataset automatically created during the evaluation run of model AbacusResearch/haLLAwa2 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 2024-02-12T13:50:58.490257(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:automatic-speech-recognition", "size_categories:1K<n<10K", "language:jv", "license:mit", "region:us" ]

[]

[ "jv" ]

[]

[ "TAGS\n#task_categories-automatic-speech-recognition #size_categories-1K<n<10K #language-Javanese #license-mit #region-us \n" ]

[ "region:us" ]

[]

[]

[]

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

[ "task_categories:text-classification", "size_categories:1K<n<10K", "language:id", "license:apache-2.0", "region:us" ]

[]

[ "id" ]

[]

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

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of Eurdem/Megatron-Mx\n\n\n\nDataset automatically created during the evaluation run of model Eurdem/Megatron-Mx 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 2024-02-12T14:27:26.866749(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 Eurdem/Megatron-Mx\n\n\n\nDataset automatically created during the evaluation run of model Eurdem/Megatron-Mx 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 2024-02-12T14:27:26.866749(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" ]

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

[]

[]

[ "# Dataset Card for \"arabic_punctuation\"", "## Dataset Details", "### Dataset Description\n\n\nThis is a curated dataset, specifically designed to facilitate the study of punctuation. It has undergone rigorous manual annotation and verification on the basis of sentence structure, with sentence boundaries clearly marked. The dataset is in three folders:\n\n1. The ABC component of the Arabic Punctuation Dataset: This folder features the manually annotated punctuation gold standard. It consists of one chapter extracted from each of 45 non-fiction books by 36 authors from 19 different fields of study. It contains 45 text files with a total of 149K tokens in 13K sentences. \n\n2. The CBT component: This folder has 1085 text files in 60 sub-folders, the full text of complete book translations that had been rendered from English into Arabic independently of this project. Their punctuation, we found out, mirrors the English source language texts; i.e., the sentence terminals in these Arabic texts follow the rules of English. In this folder are close to 3M words in more than 170K properly punctuated sentences.\n\n3. The SSAC-UNPC component: This folder constitutes the third part of the Arabic Punctuation Dataset. It has close to 12M disconnected, disordered, complete sentences in 79 text files. These scrambled sentences were extracted from the predominantly legal Arabic subcorpus of the United Nations Parallel Corpus (UNPC). The punctuation here is authentic. It was done by the UN translators as part of their work. We consider this to be an excellent punctuation corpus because it mirrors the rule-governed punctuation of the English source documents, especially in relation to sentence terminals. These scrambled sentences total more than 309M words.", "### Steps to reproduce\n\nThe ABC component was manually annotated and verified.\nThe CBT dataset was translated books extracted from an online library.\nThe SSAC-UNPC dataset was full sentences extracted from the Arabic component of the United Nations Parallel Corpus." ]

[ "TAGS\n#license-cc-by-4.0 #region-us \n", "# Dataset Card for \"arabic_punctuation\"", "## Dataset Details", "### Dataset Description\n\n\nThis is a curated dataset, specifically designed to facilitate the study of punctuation. It has undergone rigorous manual annotation and verification on the basis of sentence structure, with sentence boundaries clearly marked. The dataset is in three folders:\n\n1. The ABC component of the Arabic Punctuation Dataset: This folder features the manually annotated punctuation gold standard. It consists of one chapter extracted from each of 45 non-fiction books by 36 authors from 19 different fields of study. It contains 45 text files with a total of 149K tokens in 13K sentences. \n\n2. The CBT component: This folder has 1085 text files in 60 sub-folders, the full text of complete book translations that had been rendered from English into Arabic independently of this project. Their punctuation, we found out, mirrors the English source language texts; i.e., the sentence terminals in these Arabic texts follow the rules of English. In this folder are close to 3M words in more than 170K properly punctuated sentences.\n\n3. The SSAC-UNPC component: This folder constitutes the third part of the Arabic Punctuation Dataset. It has close to 12M disconnected, disordered, complete sentences in 79 text files. These scrambled sentences were extracted from the predominantly legal Arabic subcorpus of the United Nations Parallel Corpus (UNPC). The punctuation here is authentic. It was done by the UN translators as part of their work. We consider this to be an excellent punctuation corpus because it mirrors the rule-governed punctuation of the English source documents, especially in relation to sentence terminals. These scrambled sentences total more than 309M words.", "### Steps to reproduce\n\nThe ABC component was manually annotated and verified.\nThe CBT dataset was translated books extracted from an online library.\nThe SSAC-UNPC dataset was full sentences extracted from the Arabic component of the United Nations Parallel Corpus." ]

[ "task_categories:summarization", "task_categories:feature-extraction", "task_categories:text-generation", "task_categories:text2text-generation", "size_categories:1K<n<10K", "language:en", "math", "semantic", "extraction", "graph", "relations", "science", "synthetic", "region:us" ]

[]

[ "en" ]

[ "# Dataset Card for \"Semantic Relations Extraction\"", "## Dataset Description", "### Repository\nThe \"Semantic Relations Extraction\" dataset is hosted on the Hugging Face platform, and was created with code from this GitHub repository.", "### Purpose\nThe \"Semantic Relations Extraction\" dataset was created for the purpose of fine-tuning smaller LLama2 (7B) models to speed up and reduce the costs of extracting semantic relations between entities in texts. This repository is part of a larger project aimed at creating a low-cost system for preprocessing documents in order to build a knowledge graph used for question answering and automated alerting.", "### Data Sources\nThe dataset was built using the following source:\n- 'datasets/scientific_papers'", "### Files in the Dataset\nThe repository contains 4 files:\n1. 'extracted_relations.csv' -> A dataset of generated relations between entities containing columns for ['summary', 'article part', 'output json', 'database', 'abstract', 'list_of_contents'].\n2. 'core_extracted_relations.csv' -> The same dataset but without the original abstracts and lists_of_contents. It contains columns for ['summary', 'article part', 'output json'].\n3. 'llama2_prompts.csv' -> Multiple variants of the prompt with a response that can be used for fine-tuning the model. It is created by concatenating data in 'core_extracted_relations.csv'.\n4. 'synthetic_data_12_02_24-URL' -> A backup of the whole PostgreSQL database used during data generation. It is the source for all the other files, exported by the 'airflow' user in custom format, with compression level 6 and UTF-8 encoding.", "### Database Schema\nThe dataset includes a database schema illustration, which provides an overview of how the data is organized within the database.\n\n!Database Schema", "### GitHub Repository\nSynthetic data was generated using an Airflow data pipeline. The entire codebase can be accessed in this GitHub repository.", "### Generation Process\nThis data was generated based on the 'datasets/scientific_papers' dataset. This dataset contains a list of scientific articles with separate 'abstracts' and 'lists of contents'. Here is the synthetic data generation overview:\n\n1. All the 'abstracts' and 'lists of contents' were inserted into the database.\n2. The main content of every article was split into overlapping segments of 1k LLaMA tokens with a 200-token overlap.\n3. 10k of the 'abstracts' + 'lists of contents' were summarized by LLaMA 13b.\n4. Generated 'summaries' + 'split text segments' were transformed by LLaMA 13b into unprocessed JSONs.\n5. All generated JSONs were validated and cleaned up.\n6. Validated JSONs were reformatted into datasets that may be used for fine-tuning.", "### Example of output data", "### Expected output JSON schema", "### Example of preprocessed fine-tuning data\nThis document details the preprocessing of fine-tuning data within the 'URL' file, showcasing six distinct prompt formats designed to explore the optimal structure for training models on the task of semantic relation extraction:\n1. 'prompt_with_summary_and_schema': Incorporates both a concise summary of the content and a structured schema outlining the expected JSON.\n2. 'prompt_with_summary': Features a summary of the content without an explicit schema.\n3. 'prompt_with_merged_text': Presents data as a unified text block, merging summary with extraction text.\n4. 'prompt_with_merged_text_and_schema': Combines the merged text approach with a schema to guide the extraction process.\n5. 'prompt_no_summary_with_schema': Excludes the summary but includes a schema, emphasizing the JSON structure.\n6. 'prompt_no_summary': Provides the raw data without any summary or schema, offering the most unstructured form of the content. Model is expected to learn schema just from output.\n\nThese variations are crafted from the same underlying data but are differentiated by their structural modifications or the omission of sections. Empirical testing is necessary to determine the degree of structure and guidance required for models to effectively learn and perform the extraction task. This approach aims to identify the optimal data presentation format that balances informational completeness with processing efficiency, thereby enhancing the model's learning effectiveness in semantic relation extraction.", "## Decisions\n1. There is a whole section of the database with extracted relations and entities, mostly for estimating the connectivity and scale of the extracted data.\n2. I chose 'datasets/scientific_papers' as it already provided a good base for summaries (i.e., Abstracts) and did not require me to iteratively summarize all the contents, which would require additional time.\n3. This project does not use ChatGPT or other external APIs; all processing was done locally on 2x3090RTX + some OrangePIs. The goal is to generate a fine-tuned model that can be hosted more cheaply, and also provide the same utility as this two-step LLaMA 13b process. OpenAI does not allow using the results of generation for fine-tuning other models; hence, all this data was generated locally with LLaMA 2, as the license permits improving LLaMA 2 with data generated with LLaMA 2. This is not perfect, but as long as I use 'datasets/scientific_papers', there is still the issue of licensing; it all will need to be regenerated in the future with a more open stack.\n4. The goal is to create a small 3B-7B model that can be used for the task of extracting entities and semantic relations, which may be run on a small ARM board like OrangePI, with minimal cost at a reasonable speed.\n5. I used LLaMA 2 Chat because, in the past, I was able to achieve the most stable results with that model.\n6. I set the temperature to 0.7 to allow the model to infer some missing information and generate better summaries, but the trade-off of using a non-zero temperature is more involved result cleanup. Still, almost 88% of the generated data had a fixable structure.", "## Future Plans for the Project\n1. Fine-tune LLaMA 2 7B with synthetic data (try and evaluate the speed and quality of generation).\n2. Generate more synthetic data, clean it, and fine-tune the model further.\n3. Build a system for mixed querying of the data (I've built a prototype; now, I would like to recreate it as a whole standalone service).\n4. After running it successfully, regenerate data based on the Wikipedia dataset or another fully open-source dataset, and replace LLaMA with a truly open-source model.", "## Statistics\n1. I ran the generation on 4 instances of LLaMA 2-chat on 2x3090RTX + i7 4790K. The processing averaged around 1 result per minute (either a summary or JSON). The whole process, excluding coding and experimentation, took approximately 20,000 minutes, which is roughly 14 days of compute time, and required about 120 kWh of power. In the near future, I need to upgrade the CPU + RAM to remove that bottleneck.\n\n2. I tested hosting on ARM boards; a 13b model quantized to q4 was able to be hosted with stable speed for an extended time, achieving a speed of 2.34 tokens/s per one OrangePI. With an RTX 3090 paired with my somewhat outdated CPU, an i7 4790K, I was able to achieve up to 20 tokens/s. I have 5 OrangePIs 5 16GB, and by running models on all of them, I achieved around 11.7 tokens/s for approximately 50W of power.", "### Use Cases\nThe \"Semantic Relations Extraction\" dataset is ideal for researchers and developers aiming to create automated systems for extracting systematized knowledge from text. It is particularly useful for projects focused on building knowledge graphs, enhancing question answering systems, and developing tools for automated alerting based on semantic analysis.", "### Licensing Information\nThis dataset is derived from the 'scientific_papers' dataset, which unfortunately does not have a clear license. Future plans involve regenerating the entire dataset using the Wikipedia dataset and fully open-source models to ensure broader accessibility and compliance with open-source licensing standards." ]

[ "TAGS\n#task_categories-summarization #task_categories-feature-extraction #task_categories-text-generation #task_categories-text2text-generation #size_categories-1K<n<10K #language-English #math #semantic #extraction #graph #relations #science #synthetic #region-us \n", "# Dataset Card for \"Semantic Relations Extraction\"", "## Dataset Description", "### Repository\nThe \"Semantic Relations Extraction\" dataset is hosted on the Hugging Face platform, and was created with code from this GitHub repository.", "### Purpose\nThe \"Semantic Relations Extraction\" dataset was created for the purpose of fine-tuning smaller LLama2 (7B) models to speed up and reduce the costs of extracting semantic relations between entities in texts. This repository is part of a larger project aimed at creating a low-cost system for preprocessing documents in order to build a knowledge graph used for question answering and automated alerting.", "### Data Sources\nThe dataset was built using the following source:\n- 'datasets/scientific_papers'", "### Files in the Dataset\nThe repository contains 4 files:\n1. 'extracted_relations.csv' -> A dataset of generated relations between entities containing columns for ['summary', 'article part', 'output json', 'database', 'abstract', 'list_of_contents'].\n2. 'core_extracted_relations.csv' -> The same dataset but without the original abstracts and lists_of_contents. It contains columns for ['summary', 'article part', 'output json'].\n3. 'llama2_prompts.csv' -> Multiple variants of the prompt with a response that can be used for fine-tuning the model. It is created by concatenating data in 'core_extracted_relations.csv'.\n4. 'synthetic_data_12_02_24-URL' -> A backup of the whole PostgreSQL database used during data generation. It is the source for all the other files, exported by the 'airflow' user in custom format, with compression level 6 and UTF-8 encoding.", "### Database Schema\nThe dataset includes a database schema illustration, which provides an overview of how the data is organized within the database.\n\n!Database Schema", "### GitHub Repository\nSynthetic data was generated using an Airflow data pipeline. The entire codebase can be accessed in this GitHub repository.", "### Generation Process\nThis data was generated based on the 'datasets/scientific_papers' dataset. This dataset contains a list of scientific articles with separate 'abstracts' and 'lists of contents'. Here is the synthetic data generation overview:\n\n1. All the 'abstracts' and 'lists of contents' were inserted into the database.\n2. The main content of every article was split into overlapping segments of 1k LLaMA tokens with a 200-token overlap.\n3. 10k of the 'abstracts' + 'lists of contents' were summarized by LLaMA 13b.\n4. Generated 'summaries' + 'split text segments' were transformed by LLaMA 13b into unprocessed JSONs.\n5. All generated JSONs were validated and cleaned up.\n6. Validated JSONs were reformatted into datasets that may be used for fine-tuning.", "### Example of output data", "### Expected output JSON schema", "### Example of preprocessed fine-tuning data\nThis document details the preprocessing of fine-tuning data within the 'URL' file, showcasing six distinct prompt formats designed to explore the optimal structure for training models on the task of semantic relation extraction:\n1. 'prompt_with_summary_and_schema': Incorporates both a concise summary of the content and a structured schema outlining the expected JSON.\n2. 'prompt_with_summary': Features a summary of the content without an explicit schema.\n3. 'prompt_with_merged_text': Presents data as a unified text block, merging summary with extraction text.\n4. 'prompt_with_merged_text_and_schema': Combines the merged text approach with a schema to guide the extraction process.\n5. 'prompt_no_summary_with_schema': Excludes the summary but includes a schema, emphasizing the JSON structure.\n6. 'prompt_no_summary': Provides the raw data without any summary or schema, offering the most unstructured form of the content. Model is expected to learn schema just from output.\n\nThese variations are crafted from the same underlying data but are differentiated by their structural modifications or the omission of sections. Empirical testing is necessary to determine the degree of structure and guidance required for models to effectively learn and perform the extraction task. This approach aims to identify the optimal data presentation format that balances informational completeness with processing efficiency, thereby enhancing the model's learning effectiveness in semantic relation extraction.", "## Decisions\n1. There is a whole section of the database with extracted relations and entities, mostly for estimating the connectivity and scale of the extracted data.\n2. I chose 'datasets/scientific_papers' as it already provided a good base for summaries (i.e., Abstracts) and did not require me to iteratively summarize all the contents, which would require additional time.\n3. This project does not use ChatGPT or other external APIs; all processing was done locally on 2x3090RTX + some OrangePIs. The goal is to generate a fine-tuned model that can be hosted more cheaply, and also provide the same utility as this two-step LLaMA 13b process. OpenAI does not allow using the results of generation for fine-tuning other models; hence, all this data was generated locally with LLaMA 2, as the license permits improving LLaMA 2 with data generated with LLaMA 2. This is not perfect, but as long as I use 'datasets/scientific_papers', there is still the issue of licensing; it all will need to be regenerated in the future with a more open stack.\n4. The goal is to create a small 3B-7B model that can be used for the task of extracting entities and semantic relations, which may be run on a small ARM board like OrangePI, with minimal cost at a reasonable speed.\n5. I used LLaMA 2 Chat because, in the past, I was able to achieve the most stable results with that model.\n6. I set the temperature to 0.7 to allow the model to infer some missing information and generate better summaries, but the trade-off of using a non-zero temperature is more involved result cleanup. Still, almost 88% of the generated data had a fixable structure.", "## Future Plans for the Project\n1. Fine-tune LLaMA 2 7B with synthetic data (try and evaluate the speed and quality of generation).\n2. Generate more synthetic data, clean it, and fine-tune the model further.\n3. Build a system for mixed querying of the data (I've built a prototype; now, I would like to recreate it as a whole standalone service).\n4. After running it successfully, regenerate data based on the Wikipedia dataset or another fully open-source dataset, and replace LLaMA with a truly open-source model.", "## Statistics\n1. I ran the generation on 4 instances of LLaMA 2-chat on 2x3090RTX + i7 4790K. The processing averaged around 1 result per minute (either a summary or JSON). The whole process, excluding coding and experimentation, took approximately 20,000 minutes, which is roughly 14 days of compute time, and required about 120 kWh of power. In the near future, I need to upgrade the CPU + RAM to remove that bottleneck.\n\n2. I tested hosting on ARM boards; a 13b model quantized to q4 was able to be hosted with stable speed for an extended time, achieving a speed of 2.34 tokens/s per one OrangePI. With an RTX 3090 paired with my somewhat outdated CPU, an i7 4790K, I was able to achieve up to 20 tokens/s. I have 5 OrangePIs 5 16GB, and by running models on all of them, I achieved around 11.7 tokens/s for approximately 50W of power.", "### Use Cases\nThe \"Semantic Relations Extraction\" dataset is ideal for researchers and developers aiming to create automated systems for extracting systematized knowledge from text. It is particularly useful for projects focused on building knowledge graphs, enhancing question answering systems, and developing tools for automated alerting based on semantic analysis.", "### Licensing Information\nThis dataset is derived from the 'scientific_papers' dataset, which unfortunately does not have a clear license. Future plans involve regenerating the entire dataset using the Wikipedia dataset and fully open-source models to ensure broader accessibility and compliance with open-source licensing standards." ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"german-law-dataset-with-embeddings\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"german-law-dataset-with-embeddings\"\n\nMore Information needed" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of paulml/DPOB-INMTOB-7B\n\n\n\nDataset automatically created during the evaluation run of model paulml/DPOB-INMTOB-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 2024-02-12T16:00:35.894215(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 paulml/DPOB-INMTOB-7B\n\n\n\nDataset automatically created during the evaluation run of model paulml/DPOB-INMTOB-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 2024-02-12T16:00:35.894215(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" ]

[]

[]

[ "# distilabel-truthy-dpo-v0.1\n\nA DPO dataset built with distilabel on top of Jon Durbin's jondurbin/truthy-dpo-v0.1 dataset.\n\nInterestingly, it swaps a lot of chosen and rejected answers.\n\n<p align=\"center\">\n <a href=\"URL\n <img src=\"URL alt=\"Built with Distilabel\" width=\"200\" height=\"32\"/>\n </a>\n</p>" ]

[ "TAGS\n#region-us \n", "# distilabel-truthy-dpo-v0.1\n\nA DPO dataset built with distilabel on top of Jon Durbin's jondurbin/truthy-dpo-v0.1 dataset.\n\nInterestingly, it swaps a lot of chosen and rejected answers.\n\n<p align=\"center\">\n <a href=\"URL\n <img src=\"URL alt=\"Built with Distilabel\" width=\"200\" height=\"32\"/>\n </a>\n</p>" ]

[ "size_categories:100K<n<1M", "language:es", "license:apache-2.0", "argentina", "law", "government", "region:us" ]

[]

[ "es" ]

[ "# Boletín Oficial de la República Argentina\nEste dataset se actualiza diariamente a través de URL, usando la librería de SandboxAI", "# Formato\nEl formato del dataset es el siguiente:" ]

[ "TAGS\n#size_categories-100K<n<1M #language-Spanish #license-apache-2.0 #argentina #law #government #region-us \n", "# Boletín Oficial de la República Argentina\nEste dataset se actualiza diariamente a través de URL, usando la librería de SandboxAI", "# Formato\nEl formato del dataset es el siguiente:" ]

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

[]

[ "en" ]

[]

[ "TAGS\n#size_categories-100K<n<1M #language-English #license-apache-2.0 #code #region-us \n" ]

[ "task_categories:text-classification", "size_categories:1K<n<10K", "language:en", "license:apache-2.0", "region:us" ]

[]

[ "en" ]

[]

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

[ "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" ]

[ "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" ]

[ "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" ]

[ "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" ]

[ "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" ]

[ "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" ]

[ "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" ]

[]

[]

[]

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

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of kidyu/Moza-7B-v1.0\n\n\n\nDataset automatically created during the evaluation run of model kidyu/Moza-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 2024-02-12T17:21:30.595988(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 kidyu/Moza-7B-v1.0\n\n\n\nDataset automatically created during the evaluation run of model kidyu/Moza-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 2024-02-12T17:21:30.595988(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/Lucie-7b\n\n\n\nDataset automatically created during the evaluation run of model BarraHome/Lucie-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 2024-02-12T17:31:04.894348(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/Lucie-7b\n\n\n\nDataset automatically created during the evaluation run of model BarraHome/Lucie-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 2024-02-12T17:31:04.894348(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 Radu1999/Mister\n\n\n\nDataset automatically created during the evaluation run of model Radu1999/Mister 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 2024-02-12T17:41:45.329847(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 Radu1999/Mister\n\n\n\nDataset automatically created during the evaluation run of model Radu1999/Mister 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 2024-02-12T17:41:45.329847(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 \"fashion_image_caption-100-v2\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"fashion_image_caption-100-v2\"\n\nMore Information needed" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of Qwen/Qwen1.5-4B-Chat\n\n\n\nDataset automatically created during the evaluation run of model Qwen/Qwen1.5-4B-Chat 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 2024-02-12T18:02:11.797174(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 Qwen/Qwen1.5-4B-Chat\n\n\n\nDataset automatically created during the evaluation run of model Qwen/Qwen1.5-4B-Chat 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 2024-02-12T18:02:11.797174(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 Qwen/Qwen1.5-7B-Chat\n\n\n\nDataset automatically created during the evaluation run of model Qwen/Qwen1.5-7B-Chat 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 2024-02-12T18:09:38.337578(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 Qwen/Qwen1.5-7B-Chat\n\n\n\nDataset automatically created during the evaluation run of model Qwen/Qwen1.5-7B-Chat 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 2024-02-12T18:09:38.337578(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 \"MarkedDataset\"\n\nMore Information needed" ]

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

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

[]

[]

[]

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

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of paulml/OGNO-7B\n\n\n\nDataset automatically created during the evaluation run of model paulml/OGNO-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 2024-02-12T18:37:16.795511(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 paulml/OGNO-7B\n\n\n\nDataset automatically created during the evaluation run of model paulml/OGNO-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 2024-02-12T18:37:16.795511(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 \"CASFMarked\"\n\nMore Information needed" ]

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

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

[]

[ "da" ]

[]

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

[ "region:us" ]

[]

[]

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

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

[ "region:us" ]

[]

[]

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

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

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

[]

[]

[ "# Credit Card Fraud Detection\n\nThis dataset was downloaded from URL adn uploaded for educational purposes." ]

[ "TAGS\n#license-mit #region-us \n", "# Credit Card Fraud Detection\n\nThis dataset was downloaded from URL adn uploaded for educational purposes." ]

[ "task_categories:text-generation", "language:de", "license:apache-2.0", "math", "region:us" ]

[]

[ "de" ]

[]

[ "TAGS\n#task_categories-text-generation #language-German #license-apache-2.0 #math #region-us \n" ]

[ "region:us" ]

[]

[]

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

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

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of shahzebnaveed/codeparrot-ds\n\n\n\nDataset automatically created during the evaluation run of model shahzebnaveed/codeparrot-ds 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 2024-02-12T19:38:09.822527(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 shahzebnaveed/codeparrot-ds\n\n\n\nDataset automatically created during the evaluation run of model shahzebnaveed/codeparrot-ds 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 2024-02-12T19:38:09.822527(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 indischepartij/MiniCPM-3B-Hercules-v2.0\n\n\n\nDataset automatically created during the evaluation run of model indischepartij/MiniCPM-3B-Hercules-v2.0 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 2024-02-12T19:38:09.464033(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 indischepartij/MiniCPM-3B-Hercules-v2.0\n\n\n\nDataset automatically created during the evaluation run of model indischepartij/MiniCPM-3B-Hercules-v2.0 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 2024-02-12T19:38:09.464033(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:mit", "region:us" ]

[]

[]

[]

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

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of indischepartij/MiniCPM-3B-OpenHermes-2.5-v2\n\n\n\nDataset automatically created during the evaluation run of model indischepartij/MiniCPM-3B-OpenHermes-2.5-v2 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 2024-02-12T20:03:47.867498(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 indischepartij/MiniCPM-3B-OpenHermes-2.5-v2\n\n\n\nDataset automatically created during the evaluation run of model indischepartij/MiniCPM-3B-OpenHermes-2.5-v2 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 2024-02-12T20:03:47.867498(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:n<1K", "language:en", "fine-tuning", "touch rugby", "region:us" ]

[]

[ "en" ]

[ "# World Health Organization (WHO) Epidemiological Update - Edition 163 (for embeddings)\n\nURL is taken from the WHO website\n\nURL was generated by GPT-3.5-turbo\n\nAll text is chunked to a length of 500 tokens with 10% overlap." ]

[ "TAGS\n#task_categories-text-generation #size_categories-n<1K #language-English #fine-tuning #touch rugby #region-us \n", "# World Health Organization (WHO) Epidemiological Update - Edition 163 (for embeddings)\n\nURL is taken from the WHO website\n\nURL was generated by GPT-3.5-turbo\n\nAll text is chunked to a length of 500 tokens with 10% overlap." ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of andysalerno/rainbowfish-7B-v9\n\n\n\nDataset automatically created during the evaluation run of model andysalerno/rainbowfish-7B-v9 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 2024-02-12T20:14:46.042064(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 andysalerno/rainbowfish-7B-v9\n\n\n\nDataset automatically created during the evaluation run of model andysalerno/rainbowfish-7B-v9 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 2024-02-12T20:14:46.042064(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 Dataset Name\n\n\n\n\n Tokenizer: mbert\n\n Dataset: TASTEset\n\n Unshuffled ratio: 0\n\n Shuffled ratio: 1\n\n Drop duplicates: True\n\n Dataset path = /home/pgajo/working/food/data/TASTEset/data/EW-TASTE/URL", "## 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 Dataset Name\n\n\n\n\n Tokenizer: mbert\n\n Dataset: TASTEset\n\n Unshuffled ratio: 0\n\n Shuffled ratio: 1\n\n Drop duplicates: True\n\n Dataset path = /home/pgajo/working/food/data/TASTEset/data/EW-TASTE/URL", "## 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" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Dataset Name\n\n\n\n\n Tokenizer: mdeberta\n\n Dataset: TASTEset\n\n Unshuffled ratio: 0\n\n Shuffled ratio: 1\n\n Drop duplicates: True\n\n Dataset path = /home/pgajo/working/food/data/TASTEset/data/EW-TASTE/URL", "## 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 Dataset Name\n\n\n\n\n Tokenizer: mdeberta\n\n Dataset: TASTEset\n\n Unshuffled ratio: 0\n\n Shuffled ratio: 1\n\n Drop duplicates: True\n\n Dataset path = /home/pgajo/working/food/data/TASTEset/data/EW-TASTE/URL", "## 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:pl", "license:mit", "art", "region:us" ]

[]

[ "pl" ]

[ "# Dataset consisting of polish jokes", "## Warning: Jokes were not curated, some may be offensive, stupid or simply not funny. It's highly recommended to filter jokes before training, e.g., based on downvotes\n\nThis dataset consists of all (9k) jokes dumped from URL on 2024-02-14. Jokes are submitted by the community. Besides _the funny_ text itself, I included upvotes and downvotes. You can use them for filtering. \nDefault sorting is based on a combination of downvotes and upvotes. \nIf used for training LLMs, it's recommended to use a tokenizer that supports line breaks, as these are often important for readability of the jokes.", "## Where to find me\n\n- Github\n- Linkedin\n- E-mail\n- Telegram" ]

[ "TAGS\n#task_categories-text-generation #size_categories-1K<n<10K #language-Polish #license-mit #art #region-us \n", "# Dataset consisting of polish jokes", "## Warning: Jokes were not curated, some may be offensive, stupid or simply not funny. It's highly recommended to filter jokes before training, e.g., based on downvotes\n\nThis dataset consists of all (9k) jokes dumped from URL on 2024-02-14. Jokes are submitted by the community. Besides _the funny_ text itself, I included upvotes and downvotes. You can use them for filtering. \nDefault sorting is based on a combination of downvotes and upvotes. \nIf used for training LLMs, it's recommended to use a tokenizer that supports line breaks, as these are often important for readability of the jokes.", "## Where to find me\n\n- Github\n- Linkedin\n- E-mail\n- Telegram" ]

[ "task_categories:text-generation", "task_categories:question-answering", "task_categories:conversational", "language:en", "license:other", "region:us" ]

[]

[ "en" ]

[ "# Hercules-v3.0\n\n!image/png\n\n- Dataset Name: Hercules-v3.0\n- Version: 3.0\n- Release Date: 2024-2-14\n- Number of Examples: 1,637,895\n- Domains: Math, Science, Biology, Physics, Instruction Following, Conversation, Computer Science, Roleplay, and more\n- Languages: Mostly English, but others can be detected.\n- Task Types: Question Answering, Conversational Modeling, Instruction Following, Code Generation, Roleplay", "## Data Source Description\nHercules-v3.0 is an extensive and diverse dataset that combines various domains to create a powerful tool for training artificial intelligence models. The data sources include conversations, coding examples, scientific explanations, and more. The dataset is sourced from multiple high-quality repositories, each contributing to the robustness of Hercules-v3.0 in different knowledge domains.", "## Included Data Sources\n- 'cognitivecomputations/dolphin'\n- 'Evol Instruct 70K & 140K'\n- 'teknium/GPT4-LLM-Cleaned'\n- 'jondurbin/airoboros-3.2'\n- 'AlekseyKorshuk/camel-chatml'\n- 'CollectiveCognition/chats-data-2023-09-22'\n- 'Nebulous/lmsys-chat-1m-smortmodelsonly'\n- 'glaiveai/glaive-code-assistant-v2'\n- 'glaiveai/glaive-code-assistant'\n- 'glaiveai/glaive-function-calling-v2'\n- 'garage-bAInd/Open-Platypus'\n- 'meta-math/MetaMathQA'\n- 'teknium/GPTeacher-General-Instruct'\n- 'GPTeacher roleplay datasets'\n- 'BI55/MedText'\n- 'pubmed_qa labeled subset'\n- 'Unnatural Instructions'\n- 'M4-ai/LDJnr_combined_inout_format'\n- 'CollectiveCognition/chats-data-2023-09-27'\n- 'CollectiveCognition/chats-data-2023-10-16'\n- 'NobodyExistsOnTheInternet/sharegptPIPPA'\n- 'yuekai/openchat_sharegpt_v3_vicuna_format'\n- 'ise-uiuc/Magicoder-Evol-Instruct-110K'\n- 'Squish42/bluemoon-fandom-1-1-rp-cleaned'\n- 'sablo/oasst2_curated'", "## Data Characteristics\nThe dataset amalgamates text from various domains, including structured and unstructured data. It contains dialogues, instructional texts, scientific explanations, coding tasks, and more.", "## Intended Use\nHercules-v3.0 is designed for training and evaluating AI models capable of handling complex tasks across multiple domains. It is suitable for researchers and developers in academia and industry working on advanced conversational agents, instruction-following models, and knowledge-intensive applications.", "## Data Quality\nThe data was collected from reputable sources with an emphasis on diversity and quality. It is expected to be relatively clean but may require additional preprocessing for specific tasks.", "## Limitations and Bias\n- The dataset may have inherent biases from the original data sources.\n- Some domains may be overrepresented due to the nature of the source datasets.", "## X-rated Content Disclaimer\nHercules-v3.0 contains X-rated content. Users are solely responsible for the use of the dataset and must ensure that their use complies with all applicable laws and regulations. The dataset maintainers are not responsible for the misuse of the dataset.", "## Usage Agreement\nBy using the Hercules-v3.0 dataset, users agree to the following:\n- The dataset is used at the user's own risk.\n- The dataset maintainers are not liable for any damages arising from the use of the dataset.\n- Users will not hold the dataset maintainers responsible for any claims, liabilities, losses, or expenses.\n\nPlease make sure to read the license for more information." ]

[ "TAGS\n#task_categories-text-generation #task_categories-question-answering #task_categories-conversational #language-English #license-other #region-us \n", "# Hercules-v3.0\n\n!image/png\n\n- Dataset Name: Hercules-v3.0\n- Version: 3.0\n- Release Date: 2024-2-14\n- Number of Examples: 1,637,895\n- Domains: Math, Science, Biology, Physics, Instruction Following, Conversation, Computer Science, Roleplay, and more\n- Languages: Mostly English, but others can be detected.\n- Task Types: Question Answering, Conversational Modeling, Instruction Following, Code Generation, Roleplay", "## Data Source Description\nHercules-v3.0 is an extensive and diverse dataset that combines various domains to create a powerful tool for training artificial intelligence models. The data sources include conversations, coding examples, scientific explanations, and more. The dataset is sourced from multiple high-quality repositories, each contributing to the robustness of Hercules-v3.0 in different knowledge domains.", "## Included Data Sources\n- 'cognitivecomputations/dolphin'\n- 'Evol Instruct 70K & 140K'\n- 'teknium/GPT4-LLM-Cleaned'\n- 'jondurbin/airoboros-3.2'\n- 'AlekseyKorshuk/camel-chatml'\n- 'CollectiveCognition/chats-data-2023-09-22'\n- 'Nebulous/lmsys-chat-1m-smortmodelsonly'\n- 'glaiveai/glaive-code-assistant-v2'\n- 'glaiveai/glaive-code-assistant'\n- 'glaiveai/glaive-function-calling-v2'\n- 'garage-bAInd/Open-Platypus'\n- 'meta-math/MetaMathQA'\n- 'teknium/GPTeacher-General-Instruct'\n- 'GPTeacher roleplay datasets'\n- 'BI55/MedText'\n- 'pubmed_qa labeled subset'\n- 'Unnatural Instructions'\n- 'M4-ai/LDJnr_combined_inout_format'\n- 'CollectiveCognition/chats-data-2023-09-27'\n- 'CollectiveCognition/chats-data-2023-10-16'\n- 'NobodyExistsOnTheInternet/sharegptPIPPA'\n- 'yuekai/openchat_sharegpt_v3_vicuna_format'\n- 'ise-uiuc/Magicoder-Evol-Instruct-110K'\n- 'Squish42/bluemoon-fandom-1-1-rp-cleaned'\n- 'sablo/oasst2_curated'", "## Data Characteristics\nThe dataset amalgamates text from various domains, including structured and unstructured data. It contains dialogues, instructional texts, scientific explanations, coding tasks, and more.", "## Intended Use\nHercules-v3.0 is designed for training and evaluating AI models capable of handling complex tasks across multiple domains. It is suitable for researchers and developers in academia and industry working on advanced conversational agents, instruction-following models, and knowledge-intensive applications.", "## Data Quality\nThe data was collected from reputable sources with an emphasis on diversity and quality. It is expected to be relatively clean but may require additional preprocessing for specific tasks.", "## Limitations and Bias\n- The dataset may have inherent biases from the original data sources.\n- Some domains may be overrepresented due to the nature of the source datasets.", "## X-rated Content Disclaimer\nHercules-v3.0 contains X-rated content. Users are solely responsible for the use of the dataset and must ensure that their use complies with all applicable laws and regulations. The dataset maintainers are not responsible for the misuse of the dataset.", "## Usage Agreement\nBy using the Hercules-v3.0 dataset, users agree to the following:\n- The dataset is used at the user's own risk.\n- The dataset maintainers are not liable for any damages arising from the use of the dataset.\n- Users will not hold the dataset maintainers responsible for any claims, liabilities, losses, or expenses.\n\nPlease make sure to read the license for more information." ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"live_ATC_QTR908\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"live_ATC_QTR908\"\n\nMore Information needed" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for \"live_ATC_ENY3808\"\n\nMore Information needed" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"live_ATC_ENY3808\"\n\nMore Information needed" ]

[ "task_categories:text-generation", "task_categories:conversational", "task_categories:question-answering", "size_categories:1K<n<10K", "language:hu", "license:apache-2.0", "gpt4", "hungarian", "instruction-finetuning", "region:us" ]

[]

[ "hu" ]

[ "# Budapest-v0.1 Dataset README", "## Overview\n\nThe Budapest-v0.1 dataset is a cutting-edge resource specifically designed for fine-tuning large language models (LLMs). Created using GPT-4, this dataset is presented in a message-response format, making it particularly suitable for a variety of natural language processing tasks. The primary focus of Budapest-v0.1 is to aid in the development and enhancement of algorithms capable of performing summarization, question answering, writing messages, and addressing open-ended questions. This dataset is fully Hungarian, catering to the development of Hungarian language models or the enhancement of multilingual models with Hungarian language capabilities.", "## Dataset Composition\n\n- Format: The dataset is structured in a message-response style, where each entry consists of an input message followed by the model-generated response. This format is particularly useful for training models on conversational tasks and other natural language understanding and generation challenges.\n \n - Input: The input message provides context or a prompt for the model to respond to.\n \n - Output: The model-generated response is the output of the language model, providing a completion or answer to the input message.\n\n - Category: The dataset is designed to support a variety of tasks, including text generation, conversational modeling, and question answering.\n\n- Language: Fully in Hungarian, Budapest-v0.1 provides a valuable resource for Hungarian natural language processing tasks, contributing to the diversity of language representation in AI models.\n\n- Generation: Entirely generated by GPT-4, ensuring high-quality, contextually relevant, and syntactically varied data entries that can be used to fine-tune models for improved performance on specified tasks.", "## Intended Use Cases\n\nThe dataset is tailored for several key tasks in natural language processing:\n\n- Summary: Training models to condense information into concise summaries, capturing the essence of messages or documents.\n \n- Question Answering: Enhancing the ability of models to understand and accurately respond to questions based on provided or inferred information.\n \n- Writing Messages: Improving model performance in generating coherent, contextually appropriate messages in various formats (e.g., emails, chat responses).\n \n- Open-Ended Questions: Enabling models to handle and respond to open-ended queries, fostering creative and contextually relevant outputs.", "## Testing and Experimentation\n\nBudapest-v0.1 is intended for testing and experimental purposes. Researchers and developers are encouraged to use this dataset to test the capabilities of their models, explore the nuances of language understanding and generation, and innovate in the realm of Hungarian natural language processing.", "## Future Directions\n\nWhile Budapest-v0.1 is currently focused on supporting a select set of tasks in Hungarian, there is potential for expansion. Future versions may include a broader range of tasks, cover additional languages, or provide more diverse data types to support a wider array of NLP applications.", "## Contribution and Feedback\n\nContributions to the dataset and feedback on its use are welcome. Researchers and developers are encouraged to share their findings, suggest improvements, and discuss potential expansions that could enhance the dataset's utility for the NLP community.", "## Note\n\nThis README was also generated by GPT-4." ]

[ "TAGS\n#task_categories-text-generation #task_categories-conversational #task_categories-question-answering #size_categories-1K<n<10K #language-Hungarian #license-apache-2.0 #gpt4 #hungarian #instruction-finetuning #region-us \n", "# Budapest-v0.1 Dataset README", "## Overview\n\nThe Budapest-v0.1 dataset is a cutting-edge resource specifically designed for fine-tuning large language models (LLMs). Created using GPT-4, this dataset is presented in a message-response format, making it particularly suitable for a variety of natural language processing tasks. The primary focus of Budapest-v0.1 is to aid in the development and enhancement of algorithms capable of performing summarization, question answering, writing messages, and addressing open-ended questions. This dataset is fully Hungarian, catering to the development of Hungarian language models or the enhancement of multilingual models with Hungarian language capabilities.", "## Dataset Composition\n\n- Format: The dataset is structured in a message-response style, where each entry consists of an input message followed by the model-generated response. This format is particularly useful for training models on conversational tasks and other natural language understanding and generation challenges.\n \n - Input: The input message provides context or a prompt for the model to respond to.\n \n - Output: The model-generated response is the output of the language model, providing a completion or answer to the input message.\n\n - Category: The dataset is designed to support a variety of tasks, including text generation, conversational modeling, and question answering.\n\n- Language: Fully in Hungarian, Budapest-v0.1 provides a valuable resource for Hungarian natural language processing tasks, contributing to the diversity of language representation in AI models.\n\n- Generation: Entirely generated by GPT-4, ensuring high-quality, contextually relevant, and syntactically varied data entries that can be used to fine-tune models for improved performance on specified tasks.", "## Intended Use Cases\n\nThe dataset is tailored for several key tasks in natural language processing:\n\n- Summary: Training models to condense information into concise summaries, capturing the essence of messages or documents.\n \n- Question Answering: Enhancing the ability of models to understand and accurately respond to questions based on provided or inferred information.\n \n- Writing Messages: Improving model performance in generating coherent, contextually appropriate messages in various formats (e.g., emails, chat responses).\n \n- Open-Ended Questions: Enabling models to handle and respond to open-ended queries, fostering creative and contextually relevant outputs.", "## Testing and Experimentation\n\nBudapest-v0.1 is intended for testing and experimental purposes. Researchers and developers are encouraged to use this dataset to test the capabilities of their models, explore the nuances of language understanding and generation, and innovate in the realm of Hungarian natural language processing.", "## Future Directions\n\nWhile Budapest-v0.1 is currently focused on supporting a select set of tasks in Hungarian, there is potential for expansion. Future versions may include a broader range of tasks, cover additional languages, or provide more diverse data types to support a wider array of NLP applications.", "## Contribution and Feedback\n\nContributions to the dataset and feedback on its use are welcome. Researchers and developers are encouraged to share their findings, suggest improvements, and discuss potential expansions that could enhance the dataset's utility for the NLP community.", "## Note\n\nThis README was also generated by GPT-4." ]

[ "task_categories:text-to-image", "size_categories:n<1K", "license:cc-by-4.0", "art", "not-for-all-audiences", "region:us" ]

[]

[]

[ "### Disclaimer\n\n\n* This dataset is intented to be used in generative AI - text-to-image models, it was created with the intended purpose of making a Stable-diffusion LoRA model.\n* the dataset was built upon the Dreambooth caption method, the dataset follows this structure:\n\n\nLicense\n=======\n\n\nThis dataset is provided under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license." ]

[ "TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-cc-by-4.0 #art #not-for-all-audiences #region-us \n", "### Disclaimer\n\n\n* This dataset is intented to be used in generative AI - text-to-image models, it was created with the intended purpose of making a Stable-diffusion LoRA model.\n* the dataset was built upon the Dreambooth caption method, the dataset follows this structure:\n\n\nLicense\n=======\n\n\nThis dataset is provided under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license." ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Educational Course Descriptions Dataset", "## Dataset Details", "### Dataset Description\n\n- Curated by: Unknown\n- Language(s) (NLP): chinese\n- License: MIT\n\nThis dataset comprises a diverse collection of educational course descriptions from various fields, including medicine, engineering, social sciences, and more. Each record contains an identification number, a course label, a detailed text describing the course, and the subject category. The texts offer insights into course content, objectives, and distinctive features, emphasizing each course's relevance and application in its respective field.", "## Uses", "### Direct Use\n\nThe dataset is ideal for analyzing and categorizing educational content, understanding curriculum structures, and developing educational resources or recommendation systems. It can be used in natural language processing to train models for text classification, summarization, and recommendation systems.", "### Out-of-Scope Use\n\nMisuse could include using the data for purposes other than educational analysis, such as commercial exploitation without proper licensing or using it to promote biased views in education.", "## Dataset Structure\n\n- ID: Unique identification number for each course\n- Label: Name or title of the course\n- Text: Description of the course including objectives and content\n- Subject Category: Field or domain to which the course belongs", "## Dataset Creation", "### Curation Rationale\n\nThe dataset is curated to provide a comprehensive overview of various educational courses, which can be instrumental in academic research, curriculum development, and educational analysis.", "### Source Data", "#### Data Collection and Processing\n\nDetails on the data collection and processing methodologies are not provided.", "## Bias, Risks, and Limitations\n\nUsers should be aware of potential biases in the representation of courses or subjects. The dataset's applicability might be limited by its scope, the diversity of courses, and the depth of descriptions.", "### Recommendations\n\nFurther information is needed to provide specific recommendations regarding the dataset's use, taking into account its biases, risks, and limitations.", "## More Information\n\nAdditional details about the dataset's origin, curation, and intended use are required for a comprehensive understanding and responsible application." ]

[ "TAGS\n#region-us \n", "# Dataset Card for Educational Course Descriptions Dataset", "## Dataset Details", "### Dataset Description\n\n- Curated by: Unknown\n- Language(s) (NLP): chinese\n- License: MIT\n\nThis dataset comprises a diverse collection of educational course descriptions from various fields, including medicine, engineering, social sciences, and more. Each record contains an identification number, a course label, a detailed text describing the course, and the subject category. The texts offer insights into course content, objectives, and distinctive features, emphasizing each course's relevance and application in its respective field.", "## Uses", "### Direct Use\n\nThe dataset is ideal for analyzing and categorizing educational content, understanding curriculum structures, and developing educational resources or recommendation systems. It can be used in natural language processing to train models for text classification, summarization, and recommendation systems.", "### Out-of-Scope Use\n\nMisuse could include using the data for purposes other than educational analysis, such as commercial exploitation without proper licensing or using it to promote biased views in education.", "## Dataset Structure\n\n- ID: Unique identification number for each course\n- Label: Name or title of the course\n- Text: Description of the course including objectives and content\n- Subject Category: Field or domain to which the course belongs", "## Dataset Creation", "### Curation Rationale\n\nThe dataset is curated to provide a comprehensive overview of various educational courses, which can be instrumental in academic research, curriculum development, and educational analysis.", "### Source Data", "#### Data Collection and Processing\n\nDetails on the data collection and processing methodologies are not provided.", "## Bias, Risks, and Limitations\n\nUsers should be aware of potential biases in the representation of courses or subjects. The dataset's applicability might be limited by its scope, the diversity of courses, and the depth of descriptions.", "### Recommendations\n\nFurther information is needed to provide specific recommendations regarding the dataset's use, taking into account its biases, risks, and limitations.", "## More Information\n\nAdditional details about the dataset's origin, curation, and intended use are required for a comprehensive understanding and responsible application." ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of huseyinatahaninan/phi-2-dpo\n\n\n\nDataset automatically created during the evaluation run of model huseyinatahaninan/phi-2-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 2024-02-12T21:58:15.192256(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 huseyinatahaninan/phi-2-dpo\n\n\n\nDataset automatically created during the evaluation run of model huseyinatahaninan/phi-2-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 2024-02-12T21:58:15.192256(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", "task_categories:feature-extraction", "language:en", "language:es", "language:fr", "language:de", "language:pt", "language:pl", "language:it", "language:zh", "language:ru", "language:ja", "language:nl", "language:sv", "language:ta", "language:sr", "language:cs", "language:ca", "language:he", "language:tr", "language:fi", "language:eo", "language:el", "language:hu", "language:uk", "language:no", "language:ar", "language:fa", "language:ko", "language:ro", "language:bg", "language:bs", "language:li", "language:sq", "language:th", "license:cc-by-2.5", "arxiv:2305.14256", "region:us" ]

[ "2305.14256" ]

[ "en", "es", "fr", "de", "pt", "pl", "it", "zh", "ru", "ja", "nl", "sv", "ta", "sr", "cs", "ca", "he", "tr", "fi", "eo", "el", "hu", "uk", "no", "ar", "fa", "ko", "ro", "bg", "bs", "li", "sq", "th" ]

[ "### Example raw datasets", "### Variables\n\n\nEach data point includes following variables:", "### Dataset Description\n\n\n* Curated by: Fumika Isono, Primer AI\n* Language(s) (NLP): en, es, fr, de, pt, pl, it, zh, ru, ja, nl, sv, ta, sr, cs, ca, he, tr, fi, eo, el, hu, uk, 'no', ar, fa, ko, ro, bg, bs, li, sq, th\n* License: cc-by-2.5", "### Dataset Sources\n\n\n* Repository: Github\n* Paper: ArXiv Linear Cross-Lingual Mapping of Sentence Embeddings\n\n\nUses\n----", "### Weakly aligned multilingual pararell sentence datasets\n\n\nWeakly aligned multilingual pararell sentence datasets can be constructed by comparing the titles and/or contents of the WikiNews pages that are linked to the same English WikiNews page (in the dataset, they have the same pageid).\nFollowing is the example case where titles of the same pageid are retrieved. These five phrases (news titles) are the news titles of the same incident.\n\n\nNews title: Bomb blast in Delhi kills 12, injures 62, Language: English, type: title\nNews title: چندین کشته بر اثر انفجار بمب در مقابل دادگاه عالی هند, Language: Farsi, type: title\nNews title: 9 נהרגו בפיגוע מחוץ לבית המשפט העליון של הודו, Language: Hebrew, type: title\nNews title: У Индији 11 мртвих, 64 повређених, Language: Serbian, type: title\nNews title: தில்லி உயர்நீதிமன்றத்தில் குண்டு வெடிப்பு, 10 பேர் உயிரிழப்பு, Language: Tamil, type: title", "### Direct Use\n\n\n* Multilingual embeddings\n* Language comparison", "### Source Data\n\n\nWikinews\n\n\nDataset Card Authors\n--------------------\n\n\nFumika Isono" ]

[ "TAGS\n#task_categories-text-classification #task_categories-feature-extraction #language-English #language-Spanish #language-French #language-German #language-Portuguese #language-Polish #language-Italian #language-Chinese #language-Russian #language-Japanese #language-Dutch #language-Swedish #language-Tamil #language-Serbian #language-Czech #language-Catalan #language-Hebrew #language-Turkish #language-Finnish #language-Esperanto #language-Modern Greek (1453-) #language-Hungarian #language-Ukrainian #language-Norwegian #language-Arabic #language-Persian #language-Korean #language-Romanian #language-Bulgarian #language-Bosnian #language-Limburgan #language-Albanian #language-Thai #license-cc-by-2.5 #arxiv-2305.14256 #region-us \n", "### Example raw datasets", "### Variables\n\n\nEach data point includes following variables:", "### Dataset Description\n\n\n* Curated by: Fumika Isono, Primer AI\n* Language(s) (NLP): en, es, fr, de, pt, pl, it, zh, ru, ja, nl, sv, ta, sr, cs, ca, he, tr, fi, eo, el, hu, uk, 'no', ar, fa, ko, ro, bg, bs, li, sq, th\n* License: cc-by-2.5", "### Dataset Sources\n\n\n* Repository: Github\n* Paper: ArXiv Linear Cross-Lingual Mapping of Sentence Embeddings\n\n\nUses\n----", "### Weakly aligned multilingual pararell sentence datasets\n\n\nWeakly aligned multilingual pararell sentence datasets can be constructed by comparing the titles and/or contents of the WikiNews pages that are linked to the same English WikiNews page (in the dataset, they have the same pageid).\nFollowing is the example case where titles of the same pageid are retrieved. These five phrases (news titles) are the news titles of the same incident.\n\n\nNews title: Bomb blast in Delhi kills 12, injures 62, Language: English, type: title\nNews title: چندین کشته بر اثر انفجار بمب در مقابل دادگاه عالی هند, Language: Farsi, type: title\nNews title: 9 נהרגו בפיגוע מחוץ לבית המשפט העליון של הודו, Language: Hebrew, type: title\nNews title: У Индији 11 мртвих, 64 повређених, Language: Serbian, type: title\nNews title: தில்லி உயர்நீதிமன்றத்தில் குண்டு வெடிப்பு, 10 பேர் உயிரிழப்பு, Language: Tamil, type: title", "### Direct Use\n\n\n* Multilingual embeddings\n* Language comparison", "### Source Data\n\n\nWikinews\n\n\nDataset Card Authors\n--------------------\n\n\nFumika Isono" ]

[ "region:us" ]

[]

[]

[ "## Licensing Information\n\nAll rights belong to their respective authors noted in reference column. Usage of this dataset is possible only for personal purposes on a non-commercial basis." ]

[ "TAGS\n#region-us \n", "## Licensing Information\n\nAll rights belong to their respective authors noted in reference column. Usage of this dataset is possible only for personal purposes on a non-commercial basis." ]

[ "task_categories:text2text-generation", "size_categories:10K<n<100K", "language:id", "corpus", "indonesia", "text", "parquet", "region:us" ]

[]

[ "id" ]

[ "# Indonesian Literature Corpus", "## Description\nThis dataset contains a corpus in the Indonesian language taken from Korpus Indonesia, provided by the Ministry of Education and Culture of the Republic of Indonesia. The corpus specifically focuses on literature texts, including various genres such as fiction, poetry, drama, and literary criticism.", "## Contents\nThe dataset consists of texts in the Indonesian language that are categorized under the field of literature. These texts encompass a wide range of literary works, including novels, short stories, poems, plays, and critical essays.", "## Usage\nThis dataset can be utilized for various research and development purposes related to Indonesian literature analysis, literary studies, authorship attribution, genre classification, sentiment analysis of literary texts, and other tasks within the domain of literature and humanities.", "## Compatibility with Other Datasets\nPlease note that there might be some overlap between this dataset and the dataset available at DamarJati/indocorpus-mix. Some sentences or passages in this dataset may also appear in the aforementioned dataset.", "## License\nThe dataset is retrieved from Korpus Indonesia provided by the Ministry of Education and Culture of the Republic of Indonesia. Please make sure to check and comply with the applicable licensing terms from the original source.", "## References\nFor more information about Korpus Indonesia, please visit URL" ]

[ "TAGS\n#task_categories-text2text-generation #size_categories-10K<n<100K #language-Indonesian #corpus #indonesia #text #parquet #region-us \n", "# Indonesian Literature Corpus", "## Description\nThis dataset contains a corpus in the Indonesian language taken from Korpus Indonesia, provided by the Ministry of Education and Culture of the Republic of Indonesia. The corpus specifically focuses on literature texts, including various genres such as fiction, poetry, drama, and literary criticism.", "## Contents\nThe dataset consists of texts in the Indonesian language that are categorized under the field of literature. These texts encompass a wide range of literary works, including novels, short stories, poems, plays, and critical essays.", "## Usage\nThis dataset can be utilized for various research and development purposes related to Indonesian literature analysis, literary studies, authorship attribution, genre classification, sentiment analysis of literary texts, and other tasks within the domain of literature and humanities.", "## Compatibility with Other Datasets\nPlease note that there might be some overlap between this dataset and the dataset available at DamarJati/indocorpus-mix. Some sentences or passages in this dataset may also appear in the aforementioned dataset.", "## License\nThe dataset is retrieved from Korpus Indonesia provided by the Ministry of Education and Culture of the Republic of Indonesia. Please make sure to check and comply with the applicable licensing terms from the original source.", "## References\nFor more information about Korpus Indonesia, please visit URL" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Dataset Name\n\n\n\n\n Tokenizer: mbert\n\n Dataset: TASTEset\n\n Unshuffled ratio: 0\n\n Shuffled ratio: 1\n\n Drop duplicates: True\n\n Dataset path = /home/pgajo/working/food/data/TASTEset/data/EW-TASTE/URL", "## 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 Dataset Name\n\n\n\n\n Tokenizer: mbert\n\n Dataset: TASTEset\n\n Unshuffled ratio: 0\n\n Shuffled ratio: 1\n\n Drop duplicates: True\n\n Dataset path = /home/pgajo/working/food/data/TASTEset/data/EW-TASTE/URL", "## 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 Dataset Name\n\n\n\n\n Tokenizer: mdeberta\n\n Dataset: TASTEset\n\n Unshuffled ratio: 0\n\n Shuffled ratio: 1\n\n Drop duplicates: True\n\n Dataset path = /home/pgajo/working/food/data/TASTEset/data/EW-TASTE/URL", "## 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 Dataset Name\n\n\n\n\n Tokenizer: mdeberta\n\n Dataset: TASTEset\n\n Unshuffled ratio: 0\n\n Shuffled ratio: 1\n\n Drop duplicates: True\n\n Dataset path = /home/pgajo/working/food/data/TASTEset/data/EW-TASTE/URL", "## 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 rombodawg/Everyone-LLM-7b-Base\n\n\n\nDataset automatically created during the evaluation run of model rombodawg/Everyone-LLM-7b-Base 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 2024-02-12T23:53:27.239989(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 rombodawg/Everyone-LLM-7b-Base\n\n\n\nDataset automatically created during the evaluation run of model rombodawg/Everyone-LLM-7b-Base 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 2024-02-12T23:53:27.239989(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 Dataset Name\n\n\n\n\n Tokenizer: mdeberta\n\n Dataset: TASTEset\n\n Unshuffled ratio: 0\n\n Shuffled ratio: 1\n\n Shuffle probability: 0.25\n\n Drop duplicates: True\n\n Dataset path = /home/pgajo/working/food/data/TASTEset/data/EW-TASTE/URL", "## 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 Dataset Name\n\n\n\n\n Tokenizer: mdeberta\n\n Dataset: TASTEset\n\n Unshuffled ratio: 0\n\n Shuffled ratio: 1\n\n Shuffle probability: 0.25\n\n Drop duplicates: True\n\n Dataset path = /home/pgajo/working/food/data/TASTEset/data/EW-TASTE/URL", "## 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 Dataset Name\n\n\n\nThis dataset contains ~13.8 million instances of taxi rides.", "### Dataset Description", "### Dataset Sources [optional]\n\nNew York City Taxi Fare Prediction" ]

[ "TAGS\n#region-us \n", "# Dataset Card for Dataset Name\n\n\n\nThis dataset contains ~13.8 million instances of taxi rides.", "### Dataset Description", "### Dataset Sources [optional]\n\nNew York City Taxi Fare Prediction" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Dataset Name\n\n\n\n\n Tokenizer: mdeberta\n\n Dataset: TASTEset\n\n Unshuffled ratio: 0\n\n Shuffled ratio: 1\n\n Shuffle probability: 0.75\n\n Drop duplicates: True\n\n Dataset path = /home/pgajo/working/food/data/TASTEset/data/EW-TASTE/URL", "## 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 Dataset Name\n\n\n\n\n Tokenizer: mdeberta\n\n Dataset: TASTEset\n\n Unshuffled ratio: 0\n\n Shuffled ratio: 1\n\n Shuffle probability: 0.75\n\n Drop duplicates: True\n\n Dataset path = /home/pgajo/working/food/data/TASTEset/data/EW-TASTE/URL", "## 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 Dataset Name\n\n\n\n\n Tokenizer: mbert\n\n Dataset: TASTEset\n\n Unshuffled ratio: 0\n\n Shuffled ratio: 1\n\n Shuffle probability: 0.75\n\n Drop duplicates: True\n\n Dataset path = /home/pgajo/working/food/data/TASTEset/data/EW-TASTE/URL", "## 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 Dataset Name\n\n\n\n\n Tokenizer: mbert\n\n Dataset: TASTEset\n\n Unshuffled ratio: 0\n\n Shuffled ratio: 1\n\n Shuffle probability: 0.75\n\n Drop duplicates: True\n\n Dataset path = /home/pgajo/working/food/data/TASTEset/data/EW-TASTE/URL", "## 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 Dataset Name\n\n\n\n\n Tokenizer: mbert\n\n Dataset: TASTEset\n\n Unshuffled ratio: 0\n\n Shuffled ratio: 1\n\n Shuffle probability: 0.25\n\n Drop duplicates: True\n\n Dataset path = /home/pgajo/working/food/data/TASTEset/data/EW-TASTE/URL", "## 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 Dataset Name\n\n\n\n\n Tokenizer: mbert\n\n Dataset: TASTEset\n\n Unshuffled ratio: 0\n\n Shuffled ratio: 1\n\n Shuffle probability: 0.25\n\n Drop duplicates: True\n\n Dataset path = /home/pgajo/working/food/data/TASTEset/data/EW-TASTE/URL", "## 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:mit", "region:us" ]

[]

[ "en" ]

[]

[ "TAGS\n#language-English #license-mit #region-us \n" ]

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of BarraHome/Lucie-7b-3e-5\n\n\n\nDataset automatically created during the evaluation run of model BarraHome/Lucie-7b-3e-5 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 2024-02-13T01:22:54.103083(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/Lucie-7b-3e-5\n\n\n\nDataset automatically created during the evaluation run of model BarraHome/Lucie-7b-3e-5 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 2024-02-13T01:22:54.103083(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 LHC88/DPOpenHermes-7B-v2-PerfLaser\n\n\n\nDataset automatically created during the evaluation run of model LHC88/DPOpenHermes-7B-v2-PerfLaser 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 2024-02-13T01:23:03.882958(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 LHC88/DPOpenHermes-7B-v2-PerfLaser\n\n\n\nDataset automatically created during the evaluation run of model LHC88/DPOpenHermes-7B-v2-PerfLaser 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 2024-02-13T01:23:03.882958(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 Gille/StrangeMerges_22-7B-slerp\n\n\n\nDataset automatically created during the evaluation run of model Gille/StrangeMerges_22-7B-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 2024-02-13T01:26:13.113566(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 Gille/StrangeMerges_22-7B-slerp\n\n\n\nDataset automatically created during the evaluation run of model Gille/StrangeMerges_22-7B-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 2024-02-13T01:26:13.113566(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 \"BIOGRID\"\n\nJan 24 version" ]

[ "TAGS\n#region-us \n", "# Dataset Card for \"BIOGRID\"\n\nJan 24 version" ]

[ "region:us" ]

[]

[]

[]

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

[ "region:us" ]

[]

[]

[ "# Dataset Card for Evaluation run of jsfs11/MoEv4Config-TestWeightedTIES-7b\n\n\n\nDataset automatically created during the evaluation run of model jsfs11/MoEv4Config-TestWeightedTIES-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 2024-02-13T02:02:25.718640(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 jsfs11/MoEv4Config-TestWeightedTIES-7b\n\n\n\nDataset automatically created during the evaluation run of model jsfs11/MoEv4Config-TestWeightedTIES-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 2024-02-13T02:02:25.718640(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" ]

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

[]

[ "en" ]

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[ "TAGS\n#language-English #license-wtfpl #region-us \n" ]