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Unable to Download Hindi Wikipedia Dataset
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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I used the Dataset Library in Python to load the wikipedia dataset with the Hindi Config 20200501.hi along with something called beam_runner='DirectRunner' and it keeps giving me the error that the file is not found. I have attached the screenshot of the error and the code both. Please help me to understand how to resolve this issue. ![Code](https://user-images.githubusercontent.com/30871963/103437466-1f3a3300-4c4e-11eb-9d54-fc9601abfeec.png) ![Error](https://user-images.githubusercontent.com/30871963/103437407-7ee40e80-4c4d-11eb-8151-a86eb664e6be.png)
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I am trying to load the squad dataset. Fails on Windows 10 but succeeds in Colab. Transformers: 3.3.1 Datasets: 1.0.2 Windows 10 (also tested in WSL) ``` datasets.logging.set_verbosity_debug() datasets. train_dataset = load_dataset('squad', split='train') valid_dataset = load_dataset('squad', split='validation') train_dataset.features ``` ``` https://raw.githubusercontent.com/huggingface/datasets/1.0.2/datasets/squad/squad.py not found in cache or force_download set to True, downloading to C:\Users\simpl\.cache\huggingface\datasets\tmpzj_o_6u7 Downloading: 5.24k/? [00:00<00:00, 134kB/s] storing https://raw.githubusercontent.com/huggingface/datasets/1.0.2/datasets/squad/squad.py in cache at C:\Users\simpl\.cache\huggingface\datasets\f6877c8d2e01e8fcb60dc101be28b54a7522feac756deb9ac5c39c6d8ebef1ce.85f43de978b9b25921cb78d7a2f2b350c04acdbaedb9ecb5f7101cd7c0950e68.py creating metadata file for C:\Users\simpl\.cache\huggingface\datasets\f6877c8d2e01e8fcb60dc101be28b54a7522feac756deb9ac5c39c6d8ebef1ce.85f43de978b9b25921cb78d7a2f2b350c04acdbaedb9ecb5f7101cd7c0950e68.py Checking C:\Users\simpl\.cache\huggingface\datasets\f6877c8d2e01e8fcb60dc101be28b54a7522feac756deb9ac5c39c6d8ebef1ce.85f43de978b9b25921cb78d7a2f2b350c04acdbaedb9ecb5f7101cd7c0950e68.py for additional imports. Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.0.2/datasets/squad/squad.py at C:\Users\simpl\.cache\huggingface\modules\datasets_modules\datasets\squad Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.0.2/datasets/squad/squad.py at C:\Users\simpl\.cache\huggingface\modules\datasets_modules\datasets\squad\1244d044b266a5e4dbd4174d23cb995eead372fbca31a03edc3f8a132787af41 Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.0.2/datasets/squad/squad.py to C:\Users\simpl\.cache\huggingface\modules\datasets_modules\datasets\squad\1244d044b266a5e4dbd4174d23cb995eead372fbca31a03edc3f8a132787af41\squad.py Couldn't find dataset infos file at https://raw.githubusercontent.com/huggingface/datasets/1.0.2/datasets/squad\dataset_infos.json Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.0.2/datasets/squad/squad.py at C:\Users\simpl\.cache\huggingface\modules\datasets_modules\datasets\squad\1244d044b266a5e4dbd4174d23cb995eead372fbca31a03edc3f8a132787af41\squad.json No config specified, defaulting to first: squad/plain_text ``` Interrupting the jupyter kernel we are in a file lock. In Google Colab the download is ok. In contrast to a local run in colab dataset_infos.json is downloaded ``` https://raw.githubusercontent.com/huggingface/datasets/1.0.2/datasets/squad/dataset_infos.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/datasets/tmptl9ha_ad Downloading: 2.19k/? [00:00<00:00, 26.2kB/s] ```
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Hi I am getting this connection issue, resulting in large failure on cloud, @lhoestq I appreciate your help on this. If I want to keep the codes the same, so not using save_to_disk, load_from_disk, but save the datastes in the way load_dataset reads from and copy the files in the same folder the datasets library reads from, could you assist me how this can be done, thanks I tried to do read the data, save it to a path and then set HF_HOME, which does not work and this is still not reading from the old set path, could you assist me how to save the datasets in a path, and let dataset library read from this path to avoid connection issue. thanks ``` imdb = datasets.load_dataset("imdb") imdb.save_to_disk("/idiap/temp/rkarimi/hf_datasets/imdb") >>> os.environ["HF_HOME"]="/idiap/temp/rkarimi/hf_datasets/" >>> imdb = datasets.load_dataset("imdb") Reusing dataset imdb (/idiap/temp/rkarimi/cache_home_2/datasets/imdb/plain_text/1.0.0/90099cb476936b753383ba2ae6ab2eae419b2e87f71cd5189cb9c8e5814d12a3) ``` I tried afterwards to set HF_HOME in bash, this makes it read from it, but it cannot let dataset library load from the saved path and still downloading data. could you tell me how to fix this issue @lhoestq thanks Also this is on cloud, so I save them in a path, copy it to "another machine" to load the data ### Error stack ``` Traceback (most recent call last): File "./finetune_t5_trainer.py", line 344, in <module> main() File "./finetune_t5_trainer.py", line 232, in main for task in data_args.eval_tasks} if training_args.do_test else None File "./finetune_t5_trainer.py", line 232, in <dictcomp> for task in data_args.eval_tasks} if training_args.do_test else None File "/workdir/seq2seq/data/tasks.py", line 136, in get_dataset split = self.get_sampled_split(split, n_obs) File "/workdir/seq2seq/data/tasks.py", line 64, in get_sampled_split dataset = self.load_dataset(split) File "/workdir/seq2seq/data/tasks.py", line 454, in load_dataset split=split, script_version="master") File "/usr/local/lib/python3.6/dist-packages/datasets/load.py", line 589, in load_dataset path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True File "/usr/local/lib/python3.6/dist-packages/datasets/load.py", line 263, in prepare_module head_hf_s3(path, filename=name, dataset=dataset) File "/usr/local/lib/python3.6/dist-packages/datasets/utils/file_utils.py", line 200, in head_hf_s3 return http_head(hf_bucket_url(identifier=identifier, filename=filename, use_cdn=use_cdn, dataset=dataset)) File "/usr/local/lib/python3.6/dist-packages/datasets/utils/file_utils.py", line 403, in http_head url, proxies=proxies, headers=headers, cookies=cookies, allow_redirects=allow_redirects, timeout=timeout File "/usr/local/lib/python3.6/dist-packages/requests/api.py", line 104, in head return request('head', url, **kwargs) File "/usr/local/lib/python3.6/dist-packages/requests/api.py", line 61, in request return session.request(method=method, url=url, **kwargs) File "/usr/local/lib/python3.6/dist-packages/requests/sessions.py", line 542, in request resp = self.send(prep, **send_kwargs) File "/usr/local/lib/python3.6/dist-packages/requests/sessions.py", line 655, in send r = adapter.send(request, **kwargs) File "/usr/local/lib/python3.6/dist-packages/requests/adapters.py", line 504, in send raise ConnectTimeout(e, request=request) requests.exceptions.ConnectTimeout: HTTPSConnectionPool(host='s3.amazonaws.com', port=443): Max retries exceeded with url: /datasets.huggingface.co/datasets/datasets/glue/glue.py (Caused by ConnectTimeoutError(<urllib3.connection.HTTPSConnection object at 0x7ff6d6c60a20>, 'Connection to s3.amazonaws.com timed out. (connect timeout=10)')) ```
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I've been working with wiki_dpr and noticed that the dataset processing is seriously impaired in performance [1]. It takes about 12h to process the entire dataset. Most of this time is simply loading and processing the data, but the actual indexing is also quite slow (3h). I won't repeat the concerns around multiprocessing as they are addressed in other issues (#786), but this is the first obvious thing to do. Using cython to speed up the text manipulation may be also help. Loading and processing a dataset of this size in under 15 minutes does not seem unreasonable on a modern multi-core machine. I have hit such targets myself on similar tasks. Would love to see this improve. The other issue is that it takes 3h to construct the FAISS index. If only we could use GPUs with HNSW, but we can't. My sharded GPU indexing code can build an IVF + PQ index in 10 minutes on 20 million vectors. Still, 3h seems slow even for the CPU. It looks like HF is adding only 1000 vectors at a time by default [2], whereas the faiss benchmarks adds 1 million vectors at a time (effectively) [3]. It's possible the runtime could be reduced with a larger batch. Also, it looks like project dependencies ultimately use OpenBLAS, but this is known to have issues when combined with OpenMP, which HNSW does [3]. A workaround is to set the environment variable `OMP_WAIT_POLICY=PASSIVE` via `os.environ` or similar. References: [1] https://github.com/huggingface/datasets/blob/master/datasets/wiki_dpr/wiki_dpr.py [2] https://github.com/huggingface/datasets/blob/master/src/datasets/search.py [3] https://github.com/facebookresearch/faiss/blob/master/benchs/bench_hnsw.py [4] https://github.com/facebookresearch/faiss/issues/422
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I've been working with wiki_dpr and noticed that the dataset processing is seriously impaired in performance [1]. It takes about 12h to process the entire dataset. Most of this time is simply loading and processing the data, but the actual indexing is also quite slow (3h). I won't repeat the concerns around multiprocessing as they are addressed in other issues (#786), but this is the first obvious thing to do. Using cython to speed up the text manipulation may be also help. Loading and processing a dataset of this size in under 15 minutes does not seem unreasonable on a modern multi-core machine. I have hit such targets myself on similar tasks. Would love to see this improve. The other issue is that it takes 3h to construct the FAISS index. If only we could use GPUs with HNSW, but we can't. My sharded GPU indexing code can build an IVF + PQ index in 10 minutes on 20 million vectors. Still, 3h seems slow even for the CPU. It looks like HF is adding only 1000 vectors at a time by default [2], whereas the faiss benchmarks adds 1 million vectors at a time (effectively) [3]. It's possible the runtime could be reduced with a larger batch. Also, it looks like project dependencies ultimately use OpenBLAS, but this is known to have issues when combined with OpenMP, which HNSW does [3]. A workaround is to set the environment variable `OMP_WAIT_POLICY=PASSIVE` via `os.environ` or similar. References: [1] https://github.com/huggingface/datasets/blob/master/datasets/wiki_dpr/wiki_dpr.py [2] https://github.com/huggingface/datasets/blob/master/src/datasets/search.py [3] https://github.com/facebookresearch/faiss/blob/master/benchs/bench_hnsw.py [4] https://github.com/facebookresearch/faiss/issues/422
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xed_en_fi dataset Cleanup
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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Fix ClassLabel feature type and minor mistakes in the dataset card
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Fix NER metric example in Overview notebook
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Fix errors in `NER metric example` section in `Overview.ipynb`. ``` --------------------------------------------------------------------------- ImportError Traceback (most recent call last) <ipython-input-37-ee559b166e25> in <module>() ----> 1 ner_metric = load_metric('seqeval') 2 references = [['O', 'O', 'O', 'B-MISC', 'I-MISC', 'I-MISC', 'O'], ['B-PER', 'I-PER', 'O']] 3 predictions = [['O', 'O', 'B-MISC', 'I-MISC', 'I-MISC', 'I-MISC', 'O'], ['B-PER', 'I-PER', 'O']] 4 ner_metric.compute(predictions, references) /usr/local/lib/python3.6/dist-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs) 340 if needs_to_be_installed: 341 raise ImportError( --> 342 f"To be able to use this {module_type}, you need to install the following dependencies" 343 f"{[lib_name for lib_name, lib_path in needs_to_be_installed]} using 'pip install " 344 f"{' '.join([lib_path for lib_name, lib_path in needs_to_be_installed])}' for instance'" ImportError: To be able to use this metric, you need to install the following dependencies['seqeval'] using 'pip install seqeval' for instance' ``` ``` ValueError Traceback (most recent call last) <ipython-input-39-ee559b166e25> in <module>() 2 references = [['O', 'O', 'O', 'B-MISC', 'I-MISC', 'I-MISC', 'O'], ['B-PER', 'I-PER', 'O']] 3 predictions = [['O', 'O', 'B-MISC', 'I-MISC', 'I-MISC', 'I-MISC', 'O'], ['B-PER', 'I-PER', 'O']] ----> 4 ner_metric.compute(predictions, references) /usr/local/lib/python3.6/dist-packages/datasets/metric.py in compute(self, *args, **kwargs) 378 """ 379 if args: --> 380 raise ValueError("Please call `compute` using keyword arguments.") 381 382 predictions = kwargs.pop("predictions", None) ValueError: Please call `compute` using keyword arguments. ```
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Add language to dataset card for Makhzan dataset.
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Add language to dataset card.
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Add language to dataset card for Counter dataset.
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Add language.
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removed \n in labels
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updated social_i_qa labels as per #1633
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update saving and loading methods for faiss index so to accept path l…
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- Update saving and loading methods for faiss index so to accept path like objects from pathlib The current code only supports using a string type to save and load a faiss index. This change makes it possible to use a string type OR a Path from [pathlib](https://docs.python.org/3/library/pathlib.html). The codes becomes a more intuitive this way I think.
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Arrow file is too large when saving vector data
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I computed the sentence embedding of each sentence of bookcorpus data using bert base and saved them to disk. I used 20M sentences and the obtained arrow file is about 59GB while the original text file is only about 1.3GB. Are there any ways to reduce the size of the arrow file?
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updated dataset cards
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added dataset instance in the card.
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This PR updates the dataset cards/readmes for the 4 approved PRs I submitted in the previous sprint.
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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Added the citation information to the README file
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added dataset summary
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Added information in the dataset card
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added dataset summary
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NarrativeQA fails to load with `load_dataset`
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When loading the NarrativeQA dataset with `load_dataset('narrativeqa')` as given in the documentation [here](https://huggingface.co/datasets/narrativeqa), I receive a cascade of exceptions, ending with FileNotFoundError: Couldn't find file locally at narrativeqa/narrativeqa.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/narrativeqa/narrativeqa.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/narrativeqa/narrativeqa.py Workaround: manually copy the `narrativeqa.py` builder into my local directory with curl https://raw.githubusercontent.com/huggingface/datasets/master/datasets/narrativeqa/narrativeqa.py -o narrativeqa.py and load the dataset as `load_dataset('narrativeqa.py')` everything works fine. I'm on datasets v1.1.3 using Python 3.6.10.
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Add missing homepage in some dataset cards
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In some dataset cards the homepage field in the `Dataset Description` section was missing/empty
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Rename "part-of-speech-tagging" tag in some dataset cards
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`part-of-speech-tagging` was not part of the tagging taxonomy under `structure-prediction`
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HoVeR dataset fails to load
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Hi! I'm getting an error when trying to load **HoVeR** dataset. Another one (**SQuAD**) does work for me. I'm using the latest (1.1.3) version of the library. Steps to reproduce the error: ```python >>> from datasets import load_dataset >>> dataset = load_dataset("hover") Traceback (most recent call last): File "/Users/urikz/anaconda/envs/mentionmemory/lib/python3.7/site-packages/datasets/load.py", line 267, in prepare_module local_path = cached_path(file_path, download_config=download_config) File "/Users/urikz/anaconda/envs/mentionmemory/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 308, in cached_path use_etag=download_config.use_etag, File "/Users/urikz/anaconda/envs/mentionmemory/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 486, in get_from_cache raise FileNotFoundError("Couldn't find file at {}".format(url)) FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/hover/hover.py During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/Users/urikz/anaconda/envs/mentionmemory/lib/python3.7/site-packages/datasets/load.py", line 278, in prepare_module local_path = cached_path(file_path, download_config=download_config) File "/Users/urikz/anaconda/envs/mentionmemory/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 308, in cached_path use_etag=download_config.use_etag, File "/Users/urikz/anaconda/envs/mentionmemory/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 486, in get_from_cache raise FileNotFoundError("Couldn't find file at {}".format(url)) FileNotFoundError: Couldn't find file at https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/hover/hover.py During handling of the above exception, another exception occurred: Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/Users/urikz/anaconda/envs/mentionmemory/lib/python3.7/site-packages/datasets/load.py", line 589, in load_dataset path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True File "/Users/urikz/anaconda/envs/mentionmemory/lib/python3.7/site-packages/datasets/load.py", line 282, in prepare_module combined_path, github_file_path, file_path FileNotFoundError: Couldn't find file locally at hover/hover.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/hover/hover.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/hover/hover.py ```
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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``` >>> from datasets import load_dataset >>> dataset = load_dataset("social_bias_frames") ... Downloading and preparing dataset social_bias_frames/default ... ~/.pyenv/versions/3.7.6/lib/python3.7/site-packages/datasets/utils/file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag) 484 ) 485 elif response is not None and response.status_code == 404: --> 486 raise FileNotFoundError("Couldn't find file at {}".format(url)) 487 raise ConnectionError("Couldn't reach {}".format(url)) 488 FileNotFoundError: Couldn't find file at https://homes.cs.washington.edu/~msap/social-bias-frames/SocialBiasFrames_v2.tgz ``` [Here](https://homes.cs.washington.edu/~msap/social-bias-frames/) we find button `Download data` with the correct URL for the data: https://homes.cs.washington.edu/~msap/social-bias-frames/SBIC.v2.tgz
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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This is the dataset used to train the Ollie open information extraction algorithm. It has over 21M sentences. See http://knowitall.github.io/ollie/ for more details.
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muchocine dataset cannot be dowloaded
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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```python --------------------------------------------------------------------------- FileNotFoundError Traceback (most recent call last) /usr/local/lib/python3.6/dist-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs) 267 try: --> 268 local_path = cached_path(file_path, download_config=download_config) 269 except FileNotFoundError: 7 frames FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/1.0.2/datasets/muchocine/muchocine.py During handling of the above exception, another exception occurred: FileNotFoundError Traceback (most recent call last) FileNotFoundError: Couldn't find file at https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/muchocine/muchocine.py During handling of the above exception, another exception occurred: FileNotFoundError Traceback (most recent call last) /usr/local/lib/python3.6/dist-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs) 281 raise FileNotFoundError( 282 "Couldn't find file locally at {}, or remotely at {} or {}".format( --> 283 combined_path, github_file_path, file_path 284 ) 285 ) FileNotFoundError: Couldn't find file locally at muchocine/muchocine.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.0.2/datasets/muchocine/muchocine.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/muchocine/muchocine.py ```
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Fix "'BertTokenizerFast' object has no attribute 'max_len'"
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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Tensorflow 2.3.0 gives: FutureWarning: The `max_len` attribute has been deprecated and will be removed in a future version, use `model_max_length` instead. Tensorflow 2.4.0 gives: AttributeError 'BertTokenizerFast' object has no attribute 'max_len'
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bug with sst2 in glue
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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Hi I am getting very low accuracy on SST2 I investigate this and observe that for this dataset sentences are tokenized, while this is correct for the other datasets in GLUE, please see below. Is there any alternatives I could get untokenized sentences? I am unfortunately under time pressure to report some results on this dataset. thank you for your help. @lhoestq ``` >>> a = datasets.load_dataset('glue', 'sst2', split="validation", script_version="master") Reusing dataset glue (/julia/datasets/glue/sst2/1.0.0/7c99657241149a24692c402a5c3f34d4c9f1df5ac2e4c3759fadea38f6cb29c4) >>> a[:10] {'idx': [0, 1, 2, 3, 4, 5, 6, 7, 8, 9], 'label': [1, 0, 1, 1, 0, 1, 0, 0, 1, 0], 'sentence': ["it 's a charming and often affecting journey . ", 'unflinchingly bleak and desperate ', 'allows us to hope that nolan is poised to embark a major career as a commercial yet inventive filmmaker . ', "the acting , costumes , music , cinematography and sound are all astounding given the production 's austere locales . ", "it 's slow -- very , very slow . ", 'although laced with humor and a few fanciful touches , the film is a refreshingly serious look at young women . ', 'a sometimes tedious film . ', "or doing last year 's taxes with your ex-wife . ", "you do n't have to know about music to appreciate the film 's easygoing blend of comedy and romance . ", "in exactly 89 minutes , most of which passed as slowly as if i 'd been sitting naked on an igloo , formula 51 sank from quirky to jerky to utter turkey . "]} ```
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Add id_puisi dataset
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Puisi (poem) is an Indonesian poetic form. The dataset contains 7223 Indonesian puisi with its title and author. :)
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Added `pn_summary` dataset
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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#1635 You did a great job with the fluent procedure regarding adding a dataset. I took the chance to add the dataset on my own. Thank you for your awesome job, and I hope this dataset found the researchers happy, specifically those interested in Persian Language (Farsi)!
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winogrande cannot be dowloaded
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Hi, I am getting this error when trying to run the codes on the cloud. Thank you for any suggestion and help on this @lhoestq ``` File "./finetune_trainer.py", line 318, in <module> main() File "./finetune_trainer.py", line 148, in main for task in data_args.tasks] File "./finetune_trainer.py", line 148, in <listcomp> for task in data_args.tasks] File "/workdir/seq2seq/data/tasks.py", line 65, in get_dataset dataset = self.load_dataset(split=split) File "/workdir/seq2seq/data/tasks.py", line 466, in load_dataset return datasets.load_dataset('winogrande', 'winogrande_l', split=split) File "/usr/local/lib/python3.6/dist-packages/datasets/load.py", line 589, in load_dataset path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True File "/usr/local/lib/python3.6/dist-packages/datasets/load.py", line 267, in prepare_module local_path = cached_path(file_path, download_config=download_config) File "/usr/local/lib/python3.6/dist-packages/datasets/utils/file_utils.py", line 308, in cached_path use_etag=download_config.use_etag, File "/usr/local/lib/python3.6/dist-packages/datasets/utils/file_utils.py", line 487, in get_from_cache raise ConnectionError("Couldn't reach {}".format(url)) ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/winogrande/winogrande.py yo/0 I1224 14:17:46.419031 31226 main shadow.py:122 > Traceback (most recent call last): File "/usr/lib/python3.6/runpy.py", line 193, in _run_module_as_main "__main__", mod_spec) File "/usr/lib/python3.6/runpy.py", line 85, in _run_code exec(code, run_globals) File "/usr/local/lib/python3.6/dist-packages/torch/distributed/launch.py", line 260, in <module> main() File "/usr/local/lib/python3.6/dist-packages/torch/distributed/launch.py", line 256, in main cmd=cmd) ```
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Persian Abstractive/Extractive Text Summarization
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Assembling datasets tailored to different tasks and languages is a precious target. This would be great to have this dataset included. ## Adding a Dataset - **Name:** *pn-summary* - **Description:** *A well-structured summarization dataset for the Persian language consists of 93,207 records. It is prepared for Abstractive/Extractive tasks (like cnn_dailymail for English). It can also be used in other scopes like Text Generation, Title Generation, and News Category Classification.* - **Paper:** *https://arxiv.org/abs/2012.11204* - **Data:** *https://github.com/hooshvare/pn-summary/#download* - **Motivation:** *It is the first Persian abstractive/extractive Text summarization dataset (like cnn_dailymail for English)!* Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
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Inspecting datasets per category
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Hi Is there a way I could get all NLI datasets/all QA datasets to get some understanding of available datasets per category? this is hard for me to inspect the datasets one by one in the webpage, thanks for the suggestions @lhoestq
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social_i_qa wrong format of labels
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Hi, there is extra "\n" in labels of social_i_qa datasets, no big deal, but I was wondering if you could remove it to make it consistent. so label is 'label': '1\n', not '1' thanks ``` >>> import datasets >>> from datasets import load_dataset >>> dataset = load_dataset( ... 'social_i_qa') cahce dir /julia/cache/datasets Downloading: 4.72kB [00:00, 3.52MB/s] cahce dir /julia/cache/datasets Downloading: 2.19kB [00:00, 1.81MB/s] Using custom data configuration default Reusing dataset social_i_qa (/julia/datasets/social_i_qa/default/0.1.0/4a4190cc2d2482d43416c2167c0c5dccdd769d4482e84893614bd069e5c3ba06) >>> dataset['train'][0] {'answerA': 'like attending', 'answerB': 'like staying home', 'answerC': 'a good friend to have', 'context': 'Cameron decided to have a barbecue and gathered her friends together.', 'label': '1\n', 'question': 'How would Others feel as a result?'} ```
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SICK dataset
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Hi, this would be great to have this dataset included. I might be missing something, but I could not find it in the list of already included datasets. Thank you. ## Adding a Dataset - **Name:** SICK - **Description:** SICK consists of about 10,000 English sentence pairs that include many examples of the lexical, syntactic, and semantic phenomena. - **Paper:** https://www.aclweb.org/anthology/L14-1314/ - **Data:** http://marcobaroni.org/composes/sick.html - **Motivation:** This dataset is well-known in the NLP community used for recognizing entailment between sentences. Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
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Update README.md
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I made small change for citation
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Adding UKP Argument Aspect Similarity Corpus
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Hi, this would be great to have this dataset included. ## Adding a Dataset - **Name:** UKP Argument Aspect Similarity Corpus - **Description:** The UKP Argument Aspect Similarity Corpus (UKP ASPECT) includes 3,595 sentence pairs over 28 controversial topics. Each sentence pair was annotated via crowdsourcing as either “high similarity”, “some similarity”, “no similarity” or “not related” with respect to the topic. - **Paper:** https://www.aclweb.org/anthology/P19-1054/ - **Data:** https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/1998 - **Motivation:** this is one of the datasets currently used frequently in recent adapter papers like https://arxiv.org/pdf/2005.00247.pdf Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md). Thank you
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add wongnai_reviews test set labels
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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- add test set labels provided by @ekapolc - refactor `star_rating` to a `datasets.features.ClassLabel` field
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made suggested changes to hate-speech-and-offensive-language
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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`Dataset.map` disable progress bar
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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I can't find anything to turn off the `tqdm` progress bars while running a preprocessing function using `Dataset.map`. I want to do akin to `disable_tqdm=True` in the case of `transformers`. Is there something like that?
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Fix dataset_dict.shuffle with single seed
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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Fix #1610 I added support for single integer used in `DatasetDict.shuffle`. Previously only a dictionary of seed was allowed. Moreover I added the missing `seed` parameter. Previously only `seeds` was allowed.
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Fixed bug in the shape property
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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Fix to the bug reported in issue #1622. Just replaced `return tuple(self._indices.num_rows, self._data.num_columns)` by `return (self._indices.num_rows, self._data.num_columns)`.
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Cannot download ade_corpus_v2
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I tried this to get the dataset following this url : https://huggingface.co/datasets/ade_corpus_v2 but received this error : `Traceback (most recent call last): File "/opt/anaconda3/lib/python3.7/site-packages/datasets/load.py", line 267, in prepare_module local_path = cached_path(file_path, download_config=download_config) File "/opt/anaconda3/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 308, in cached_path use_etag=download_config.use_etag, File "/opt/anaconda3/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 486, in get_from_cache raise FileNotFoundError("Couldn't find file at {}".format(url)) FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/ade_corpus_v2/ade_corpus_v2.py During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/opt/anaconda3/lib/python3.7/site-packages/datasets/load.py", line 278, in prepare_module local_path = cached_path(file_path, download_config=download_config) File "/opt/anaconda3/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 308, in cached_path use_etag=download_config.use_etag, File "/opt/anaconda3/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 486, in get_from_cache raise FileNotFoundError("Couldn't find file at {}".format(url)) FileNotFoundError: Couldn't find file at https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/ade_corpus_v2/ade_corpus_v2.py During handling of the above exception, another exception occurred: Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/opt/anaconda3/lib/python3.7/site-packages/datasets/load.py", line 589, in load_dataset path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True File "/opt/anaconda3/lib/python3.7/site-packages/datasets/load.py", line 282, in prepare_module combined_path, github_file_path, file_path FileNotFoundError: Couldn't find file locally at ade_corpus_v2/ade_corpus_v2.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/ade_corpus_v2/ade_corpus_v2.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/ade_corpus_v2/ade_corpus_v2.py`
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Add CLIMATE-FEVER dataset
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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As suggested by @SBrandeis , fresh PR that adds CLIMATE-FEVER. Replaces PR #1579. --- A dataset adopting the FEVER methodology that consists of 1,535 real-world claims regarding climate-change collected on the internet. Each claim is accompanied by five manually annotated evidence sentences retrieved from the English Wikipedia that support, refute or do not give enough information to validate the claim totalling in 7,675 claim-evidence pairs. The dataset features challenging claims that relate multiple facets and disputed cases of claims where both supporting and refuting evidence are present. More information can be found at: * Homepage: http://climatefever.ai * Paper: https://arxiv.org/abs/2012.00614
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Can't call shape on the output of select()
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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I get the error `TypeError: tuple expected at most 1 argument, got 2` when calling `shape` on the output of `select()`. It's line 531 in shape in arrow_dataset.py that causes the problem: ``return tuple(self._indices.num_rows, self._data.num_columns)`` This makes sense, since `tuple(num1, num2)` is not a valid call. Full code to reproduce: ```python dataset = load_dataset("cnn_dailymail", "3.0.0") train_set = dataset["train"] t = train_set.select(range(10)) print(t.shape)
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updated dutch_social.py for loading jsonl (lines instead of list) files
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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the data_loader is modified to load files on the fly. Earlier it was reading the entire file and then processing the records Pls refer to previous PR #1321
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Adding myPOS2017 dataset
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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myPOS Corpus (Myanmar Part-of-Speech Corpus) for Myanmar language NLP Research and Developments
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data loader for reading comprehension task
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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added doc2dial data loader and dummy data for reading comprehension task.
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Can't filter language:EN on https://huggingface.co/datasets
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When visiting https://huggingface.co/datasets, I don't see an obvious way to filter only English datasets. This is unexpected for me, am I missing something? I'd expect English to be selectable in the language widget. This problem reproduced on Mozilla Firefox and MS Edge: ![screenshot](https://user-images.githubusercontent.com/4547987/102792244-892e1f00-43a8-11eb-9e89-4826ca201a87.png)
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cifar10 initial commit
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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CIFAR-10 dataset. Didn't add the tagging since there are no vision related tags.
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added TurkishMovieSentiment dataset
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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This PR adds the **TurkishMovieSentiment: This dataset contains turkish movie reviews.** - **Homepage:** [https://www.kaggle.com/mustfkeskin/turkish-movie-sentiment-analysis-dataset/tasks](https://www.kaggle.com/mustfkeskin/turkish-movie-sentiment-analysis-dataset/tasks) - **Point of Contact:** [Mustafa Keskin](https://www.linkedin.com/in/mustfkeskin/)
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Bug: Can't download TriviaQA with `load_dataset` - custom `cache_dir`
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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Hello, I'm having issue downloading TriviaQA dataset with `load_dataset`. ## Environment info - `datasets` version: 1.1.3 - Platform: Linux-4.19.129-aufs-1-x86_64-with-debian-10.1 - Python version: 3.7.3 ## The code I'm running: ```python import datasets dataset = datasets.load_dataset("trivia_qa", "rc", cache_dir = "./datasets") ``` ## The output: 1. Download begins: ``` Downloading and preparing dataset trivia_qa/rc (download: 2.48 GiB, generated: 14.92 GiB, post-processed: Unknown size, total: 17.40 GiB) to /cs/labs/gabis/sapirweissbuch/tr ivia_qa/rc/1.1.0/e734e28133f4d9a353af322aa52b9f266f6f27cbf2f072690a1694e577546b0d... Downloading: 17%|███████████████████▉ | 446M/2.67G [00:37<04:45, 7.77MB/s] ``` 2. 100% is reached 3. It got stuck here for about an hour, and added additional 30G of data to "./datasets" directory. I killed the process eventually. A similar issue can be observed in Google Colab: https://colab.research.google.com/drive/1nn1Lw02GhfGFylzbS2j6yksGjPo7kkN-?usp=sharing ## Expected behaviour: The dataset "TriviaQA" should be successfully downloaded.
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Add id_clickbait
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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This is the CLICK-ID dataset, a collection of annotated clickbait Indonesian news headlines that was collected from 12 local online news
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Adding wiki asp dataset as new PR
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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Hi @lhoestq, Adding wiki asp as new branch because #1539 has other commits. This version has dummy data for each domain <20/30KB.
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shuffle with torch generator
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Hi I need to shuffle mutliple large datasets with `generator = torch.Generator()` for a distributed sampler which needs to make sure datasets are consistent across different cores, for this, this is really necessary for me to use torch generator, based on documentation this generator is not supported with datasets, I really need to make shuffle work with this generator and I was wondering what I can do about this issue, thanks for your help @lhoestq
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shuffle does not accept seed
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Hi I need to shuffle the dataset, but this needs to be based on epoch+seed to be consistent across the cores, when I pass seed to shuffle, this does not accept seed, could you assist me with this? thanks @lhoestq
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Not able to use 'jigsaw_toxicity_pred' dataset
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When trying to use jigsaw_toxicity_pred dataset, like this in a [colab](https://colab.research.google.com/drive/1LwO2A5M2X5dvhkAFYE4D2CUT3WUdWnkn?usp=sharing): ``` from datasets import list_datasets, list_metrics, load_dataset, load_metric ds = load_dataset("jigsaw_toxicity_pred") ``` I see below error: > FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/jigsaw_toxicity_pred/jigsaw_toxicity_pred.py During handling of the above exception, another exception occurred: FileNotFoundError Traceback (most recent call last) FileNotFoundError: Couldn't find file at https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/jigsaw_toxicity_pred/jigsaw_toxicity_pred.py During handling of the above exception, another exception occurred: FileNotFoundError Traceback (most recent call last) /usr/local/lib/python3.6/dist-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs) 280 raise FileNotFoundError( 281 "Couldn't find file locally at {}, or remotely at {} or {}".format( --> 282 combined_path, github_file_path, file_path 283 ) 284 ) FileNotFoundError: Couldn't find file locally at jigsaw_toxicity_pred/jigsaw_toxicity_pred.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/jigsaw_toxicity_pred/jigsaw_toxicity_pred.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/jigsaw_toxicity_pred/jigsaw_toxicity_pred.py
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adding ted_talks_iwslt
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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UPDATE2: (2nd Jan) Wrote a long writeup on the slack channel. I don't think this approach is correct. Basically this created language pairs (109*108) Running the `pytest `went for more than 40+ hours and it was still running! So working on a different approach, such that the number of configs = number of languages. Will make a new pull request with that. UPDATE: This requires manual download dataset This is a draft version
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modified tweets hate speech detection
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added Semantic Scholar Open Research Corpus
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I picked up this dataset [Semantic Scholar Open Research Corpus](https://allenai.org/data/s2orc) but it contains 6000 files to be downloaded. I tried the current code with 100 files and it worked fine (took ~15GB space). For 6000 files it would occupy ~900GB space which I don’t have. Can someone from the HF team with that much of disk space help me with generate dataset_infos and dummy_data?
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Navigation version breaking
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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Hi, when navigating docs (Chrome, Ubuntu) (e.g. on this page: https://huggingface.co/docs/datasets/loading_metrics.html#using-a-custom-metric-script) the version control dropdown has the wrong string displayed as the current version: ![image](https://user-images.githubusercontent.com/3007947/102632187-02cad080-414f-11eb-813b-28f3c8d80def.png) **Edit:** this actually happens _only_ if you open a link to a concrete subsection. IMO, the best way to fix this without getting too deep into the intricacies of retrieving version numbers from the URL would be to change [this](https://github.com/huggingface/datasets/blob/master/docs/source/_static/js/custom.js#L112) line to: ``` let label = (version in versionMapping) ? version : stableVersion ``` which delegates the check to the (already maintained) keys of the version mapping dictionary & should be more robust. There's a similar ternary expression [here](https://github.com/huggingface/datasets/blob/master/docs/source/_static/js/custom.js#L97) which should also fail in this case. I'd also suggest swapping this [block](https://github.com/huggingface/datasets/blob/master/docs/source/_static/js/custom.js#L80-L90) to `string.contains(version) for version in versionMapping` which might be more robust. I'd add a PR myself but I'm by no means competent in JS :) I also have a side question wrt. docs versioning: I'm trying to make docs for a project which are versioned alike to your dropdown versioning. I was wondering how do you handle storage of multiple doc versions on your server? Do you update what `https://huggingface.co/docs/datasets` points to for every stable release & manually create new folders for each released version? So far I'm building & publishing (scping) the docs to the server with a github action which works well for a single version, but would ideally need to reorder the public files triggered on a new release.
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Add tests for the download functions ?
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AFAIK the download functions in `DownloadManager` are not tested yet. It could be good to add some to ensure behavior is as expected.
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Add retries to HTTP requests
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## What does this PR do ? Adding retries to HTTP GET & HEAD requests, when they fail with a `ConnectTimeout` exception. The "canonical" way to do this is to use [urllib's Retry class](https://urllib3.readthedocs.io/en/latest/reference/urllib3.util.html#urllib3.util.Retry) and wrap it in a [HttpAdapter](https://requests.readthedocs.io/en/master/api/#requests.adapters.HTTPAdapter). Seems a bit overkill to me, plus it forces us to use the `requests.Session` object. I prefer this simpler implementation. I'm open to remarks and suggestions @lhoestq @yjernite Fixes #1102
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second update of id_newspapers_2018
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The feature "url" is currently set wrongly to data["date"], this PR fix it to data["url"]. I added also an additional POC.
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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The feature "url" is currently set wrongly to data["date"], this PR fix it to data["url"]. I added also an additional POC.
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The following code fails with "'DatasetDict' object has no attribute 'train_test_split'" - am I doing something wrong? ``` from datasets import load_dataset dataset = load_dataset('csv', data_files='data.txt') dataset = dataset.train_test_split(test_size=0.1) ``` > AttributeError: 'DatasetDict' object has no attribute 'train_test_split'
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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Hi I am hitting to this error, thanks ``` > Traceback (most recent call last): File "finetune_t5_trainer.py", line 379, in <module> main() File "finetune_t5_trainer.py", line 208, in main if training_args.do_eval or training_args.evaluation_strategy != EvaluationStrategy.NO File "finetune_t5_trainer.py", line 207, in <dictcomp> for task in data_args.eval_tasks} File "/workdir/seq2seq/data/tasks.py", line 70, in get_dataset dataset = self.load_dataset(split=split) File "/workdir/seq2seq/data/tasks.py", line 66, in load_dataset return datasets.load_dataset(self.task.name, split=split, script_version="master") File "/usr/local/lib/python3.6/dist-packages/datasets/load.py", line 589, in load_dataset path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True File "/usr/local/lib/python3.6/dist-packages/datasets/load.py", line 267, in prepare_module local_path = cached_path(file_path, download_config=download_config) File "/usr/local/lib/python3.6/dist-packages/datasets/utils/file_utils.py", line 308, in cached_path use_etag=download_config.use_etag, File "/usr/local/lib/python3.6/dist-packages/datasets/utils/file_utils.py", line 487, in get_from_cache raise ConnectionError("Couldn't reach {}".format(url)) ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/master/datasets/boolq/boolq.py el/0 I1217 01:11:33.898849 354161 main shadow.py:210 Current job status: FINISHED ```
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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It is possible that we want to do different things in the `map` function (and possibly other functions too) of a `DatasetDict`, depending on the key. I understand that `DatasetDict.map` is a really thin wrapper of `Dataset.map`, so it is easy to directly implement this functionality in the client code. Still, it'd be nice if there can be a flag, similar to `with_indices`, that allows the callable to know the key inside `DatasetDict`.
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## Using datasets.Metric with Trainer() Hi team, I was quite surprised in the [Metric documentation](https://huggingface.co/docs/datasets/using_metrics.html) I don't see how it can be used with `Trainer()`. That would be the most intuitive use case instead of having to iterate the batches and add predictions and references to the metric, then compute the metric manually. Ideally, any pre-built metrics can be added to `compute_metrics` argument of `Trainer()` and they will be calculated at an interval specified by `TrainingArguments.evaluation_strategy`. Is this option available but just not mentioned in the documentation or it's not possible at the moment? I notice in the [Transformer | Training and fine-tuning](https://huggingface.co/transformers/training.html) tutorial, you are using custom scripts to calculate the accuracy, P/R/F, which are already in the pre-built metrics.
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``` FileNotFoundError: Couldn't find file at https://wit3.fbk.eu/archive/2017-01-trnmted//texts/DeEnItNlRo/DeEnItNlRo/DeEnItNlRo-DeEnItNlRo.tgz ```
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Add helper to resolve namespace collision
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Many projects use a module called `datasets`, however this is incompatible with huggingface datasets. It would be great if there if there was some helper or similar function to resolve such a common conflict.
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Update doc2dial.py
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Added data loader for machine reading comprehension tasks proposed in the Doc2Dial EMNLP 2020 paper.
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Modified hind encorp
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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description added, unnecessary comments removed from .py and readme.md reformated @lhoestq for #1584
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Add nq_open question answering dataset
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this is pr is a copy of #1506 due to messed up git history in that pr.
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added irc disentangle dataset
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added irc disentanglement dataset
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FileNotFoundError for `amazon_polarity`
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Version: `datasets==v1.1.3` ### Reproduction ```python from datasets import load_dataset data = load_dataset("amazon_polarity") ``` crashes with ```bash FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/amazon_polarity/amazon_polarity.py ``` and ```bash FileNotFoundError: Couldn't find file at https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/amazon_polarity/amazon_polarity.py ``` and ```bash FileNotFoundError: Couldn't find file locally at amazon_polarity/amazon_polarity.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/amazon_polarity/amazon_polarity.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/amazon_polarity/amazon_polarity.py ```
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Load hind encorp
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reformated well documented, yaml tags added, code
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Update metrics docstrings.
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#1478 Correcting the argument descriptions for metrics. Let me know if there's any issues.
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Adding wiki lingua dataset as new branch
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Adding the dataset as new branch as advised here: #1470
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Installing datasets and transformers in a tensorflow docker image throws Permission Error on 'import transformers'
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I am using a docker container, based on latest tensorflow-gpu image, to run transformers and datasets (4.0.1 and 1.1.3 respectively - Dockerfile attached below). Importing transformers throws a Permission Error to access `/.cache`: ``` $ docker run --gpus=all --rm -it -u $(id -u):$(id -g) -v $(pwd)/data:/root/data -v $(pwd):/root -v $(pwd)/models/:/root/models -v $(pwd)/saved_models/:/root/saved_models -e "HOST_HOSTNAME=$(hostname)" hf-error:latest /bin/bash ________ _______________ ___ __/__________________________________ ____/__ /________ __ __ / _ _ \_ __ \_ ___/ __ \_ ___/_ /_ __ /_ __ \_ | /| / / _ / / __/ / / /(__ )/ /_/ / / _ __/ _ / / /_/ /_ |/ |/ / /_/ \___//_/ /_//____/ \____//_/ /_/ /_/ \____/____/|__/ You are running this container as user with ID 1000 and group 1000, which should map to the ID and group for your user on the Docker host. Great! tf-docker /root > python Python 3.6.9 (default, Oct 8 2020, 12:12:24) [GCC 8.4.0] on linux Type "help", "copyright", "credits" or "license" for more information. >>> import transformers 2020-12-15 23:53:21.165827: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0 Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/usr/local/lib/python3.6/dist-packages/transformers/__init__.py", line 22, in <module> from .integrations import ( # isort:skip File "/usr/local/lib/python3.6/dist-packages/transformers/integrations.py", line 5, in <module> from .trainer_utils import EvaluationStrategy File "/usr/local/lib/python3.6/dist-packages/transformers/trainer_utils.py", line 25, in <module> from .file_utils import is_tf_available, is_torch_available, is_torch_tpu_available File "/usr/local/lib/python3.6/dist-packages/transformers/file_utils.py", line 88, in <module> import datasets # noqa: F401 File "/usr/local/lib/python3.6/dist-packages/datasets/__init__.py", line 26, in <module> from .arrow_dataset import Dataset, concatenate_datasets File "/usr/local/lib/python3.6/dist-packages/datasets/arrow_dataset.py", line 40, in <module> from .arrow_reader import ArrowReader File "/usr/local/lib/python3.6/dist-packages/datasets/arrow_reader.py", line 31, in <module> from .utils import cached_path, logging File "/usr/local/lib/python3.6/dist-packages/datasets/utils/__init__.py", line 20, in <module> from .download_manager import DownloadManager, GenerateMode File "/usr/local/lib/python3.6/dist-packages/datasets/utils/download_manager.py", line 25, in <module> from .file_utils import HF_DATASETS_CACHE, cached_path, get_from_cache, hash_url_to_filename File "/usr/local/lib/python3.6/dist-packages/datasets/utils/file_utils.py", line 118, in <module> os.makedirs(HF_MODULES_CACHE, exist_ok=True) File "/usr/lib/python3.6/os.py", line 210, in makedirs makedirs(head, mode, exist_ok) File "/usr/lib/python3.6/os.py", line 210, in makedirs makedirs(head, mode, exist_ok) File "/usr/lib/python3.6/os.py", line 220, in makedirs mkdir(name, mode) PermissionError: [Errno 13] Permission denied: '/.cache' ``` I've pinned the problem to `RUN pip install datasets`, and by commenting it you can actually import transformers correctly. Another workaround I've found is creating the directory and giving permissions to it directly on the Dockerfile. ``` FROM tensorflow/tensorflow:latest-gpu-jupyter WORKDIR /root EXPOSE 80 EXPOSE 8888 EXPOSE 6006 ENV SHELL /bin/bash ENV PATH="/root/.local/bin:${PATH}" ENV CUDA_CACHE_PATH="/root/cache/cuda" ENV CUDA_CACHE_MAXSIZE="4294967296" ENV TFHUB_CACHE_DIR="/root/cache/tfhub" RUN pip install --upgrade pip RUN apt update -y && apt upgrade -y RUN pip install transformers #Installing datasets will throw the error, try commenting and rebuilding RUN pip install datasets #Another workaround is creating the directory and give permissions explicitly #RUN mkdir /.cache #RUN chmod 777 /.cache ```
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made suggested changes in diplomacy_detection.py
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Adding CLIMATE-FEVER dataset
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This PR request the addition of the CLIMATE-FEVER dataset: A dataset adopting the FEVER methodology that consists of 1,535 real-world claims regarding climate-change collected on the internet. Each claim is accompanied by five manually annotated evidence sentences retrieved from the English Wikipedia that support, refute or do not give enough information to validate the claim totalling in 7,675 claim-evidence pairs. The dataset features challenging claims that relate multiple facets and disputed cases of claims where both supporting and refuting evidence are present. More information can be found at: - Homepage: <http://climatefever.ai> - Paper: <https://arxiv.org/abs/2012.00614>
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update multiwozv22 checksums
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a file was updated on the GitHub repo for the dataset
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Add comet metric
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Hey! I decided to add our new Crosslingual Optimized Metric for Evaluation of Translation (COMET) to the list of the available metrics. COMET was [presented at EMNLP20](https://www.aclweb.org/anthology/2020.emnlp-main.213/) and it is the highest performing metric, so far, on the WMT19 benchmark. We also participated in the [WMT20 Metrics shared task ](http://www.statmt.org/wmt20/pdf/2020.wmt-1.101.pdf) where once again COMET was validated as a top-performing metric. I hope that this metric will help researcher's and industry workers to better validate their MT systems in the future 🤗 ! Cheers, Ricardo
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sourcerer is down
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Hind_Encorp all done
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Diplomacy detection 3
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