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test_run_glue_with_pabee failing
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[ "@sshleifer Thanks for the issue. I noticed that this test fails sometimes. Do you have any idea how long has this problem been? Is it broken at the beginning or recently?", "Started breaking within the last few days. It is breaking fairly consistently at this point.", "It's I guess just flaky, for example it's...
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examples/bert-loses-patience/test_run_glue_with_pabee.py::PabeeTests::test_run_glue https://app.circleci.com/pipelines/github/huggingface/transformers/10373/workflows/0c9f2e61-2732-4857-84f0-71b59ddf10a9/jobs/71646 @JetRunner
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Experiment: ROUGE impact of using pegasus length-penalty implementation
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[ "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n", "I tried this a bit and did not get any improvements. Meanwhile, our beam search is getting similar scores to pegasus in #6844 , so I am...
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code is under `length_normalization` in the pegasus [tf repo](https://github.com/google-research/pegasus)
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Add pegasus model cards
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All learning rates are 0 warning
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[ "Duplicate of #5338 , ignore it.\r\nSorry for the confusion.", "It makes sense what you answered at #5338, thanks for the clarification. I'm closing this issue!" ]
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- `transformers` version: 3.0.2 - Platform: Linux - Python version: 3.6 - PyTorch version (GPU?): 1.4 (GPU) - Using GPU in script?: Yes - Using distributed or parallel set-up in script?: No ### Who can help @sshleifer ## Information Model I am using (Bert, XLNet ...): BART The problem arises when usi...
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how to fine tune t5 model for summarization task using tensorflow2?
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[ "please see: https://discuss.huggingface.co/t/how-to-train-t5-with-tensorflow/641." ]
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# ❓ Questions & Help <!-- The GitHub issue tracker is primarly intended for bugs, feature requests, new models and benchmarks, and migration questions. For all other questions, we direct you to the Hugging Face forum: https://discuss.huggingface.co/ . You can also try Stack Overflow (SO) where a wh...
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Docs: Separate documentation for mbart
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[ "@sshleifer I think adding new class should make thing more clear, should I go ahead with it ? Will also need to modify tests a little bit I guess", "yes, thanks!\r\n\r\nkey tests not to break\r\n```bash\r\nRUN_SLOW=1 pytest tests/test_modeling_mbart.py\r\n```", "You can also make `tokenization_mbart.py`" ]
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Currently all mbart documentation is stuffed into docs/ https://github.com/huggingface/transformers/blob/353b8f1e7a7361c0afd9e391381bc226b4a5ca8f/docs/source/model_doc/bart.rst#L42 mbart should have it's own `model_doc/mbart.rst` and entry in `pretrained_models.rst`. Optionally you can also create a new `src...
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[EncoderDecoder] Add Cross Attention for GPT2
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6415?src=pr&el=h1) Report\n> Merging [#6415](https://codecov.io/gh/huggingface/transformers/pull/6415?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/bc820476a5c72060f810f825298befd5ec85da4d&el=desc) will **decrease...
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MEMBER
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This PR implements **Bert2GPT2** by adding cross-attention layers to GPT2. Note that currently it is not possible to speed up decoder generation with the encoder-decoder framework (by using GPT2's past tensors) since it has to be implemented for all models that are compatible with the encoder/decoder framework (Ber...
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TypeError: forward() got an unexpected keyword argument 'labels'
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[ "Please copy-paste the entire stack trace, just the error message is not enough to know what's going on :-)", "Hi @sgugger thanks for the reply! \r\n\r\nPlease see below for the full stack-trace\r\n\r\n```python\r\n---------------------------------------------------------------------------\r\nTypeError ...
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## Environment info - `transformers` version: 3.0.2 - Platform: Linux-5.3.0-53-generic-x86_64-with-debian-buster-sid - Python version: 3.7.7 - PyTorch version (GPU?): 1.6.0 (True) - Tensorflow version (GPU?): 2.3.0 (False) - Using GPU in script?: True - Using distributed or parallel set-up in script?: Distribu...
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Create README.md
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Model card for https://huggingface.co/akhooli/gpt2-small-arabic
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Create model card T5-base fine-tuned on event2Mind for Intent Prediction
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More funny examples: https://twitter.com/mrm8488/status/1292952742395367424
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[EncoderDecoder] Add encoder-decoder for roberta/ vanilla longformer
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6411?src=pr&el=h1) Report\n> Merging [#6411](https://codecov.io/gh/huggingface/transformers/pull/6411?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/404782912ad1324592c2d5bb2e88d1ee99a040b6&el=desc) will **decrease...
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This PR adds Roberta to the Encoder Decoder framework. Thus, it automatically makes it possible to use both `Roberta2Roberta` models and `Longformer2Roberta` model: ```python from transformers import EncoderDecoderModel model = EncoderDecoderModel.from_pretrained("roberta-base", "roberta-base") input_ids = torch...
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Cannot unzip the XNLI-MT 1.0 zip file.
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[ "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n", "I am able to unzip the archive form this link: https://dl.fbaipublicfiles.com/XNLI/XNLI-MT-1.0.zip" ]
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# ❓ Questions & Help Is there anyone who succeeding the unzip of XNLI-MT 1.0 zip file? <!-- The GitHub issue tracker is primarly intended for bugs, feature requests, new models and benchmarks, and migration questions. For all other questions, we direct you to the Hugging Face forum: https://discuss.hu...
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TF2 TPU slow?
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[ "Hello!\r\n\r\nTraining on TPU is slow indeed because the training loop is not optimized for TPU. For two reasons:\r\n1) we don't want to have a version that is specifically optimized for each device which will create to much confusion for maintenance.\r\n2) having a training loop optimized for TPU will limit the p...
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## Environment info - `transformers` version: 3.0.2 - Platform: ubuntu 18.04 - Python version: 3.6 - Tensorflow version (GPU?): TF 2.3.0 ### Who can help @jplu ## Information Model I am using (Bert, XLNet ...): BERT The problem arises when using: * [x] my own modified scripts: (give details below) ...
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i have used t5_base for abstractive summarization but it is not giving good results,Could you please give me solution for this
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[ "Hi @gopal354 , this depends on lot of factors. What is the domain of your dataset ? There are many other summrization models available on the model hub trained on different datasets. You can try them as well. Or if you have a dataset, then you can further fine-tune these models on your domain. ", "Would be nice...
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# 🖥 Benchmarking `transformers` ## Benchmark Which part of `transformers` did you benchmark? ## Set-up What did you run your benchmarks on? Please include details, such as: CPU, GPU? If using multiple GPUs, which parallelization did you use? ## Results Put your results here!
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Slow Decoding Speed when using BertForLMModel
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[ "Yeah, exactly - we should / could add the layer cache for `BertLMHeadModel`. It's not trivial to do it, but feel free to give it a try. " ]
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I set the BertLMHeadModel as Decoder in my Seq2Seq model. It seems to work well in training. But when decoing, it decodes very slowly. I think there is no layer_past used in GPT2, XLNet in BertLMHeadModel and many attentions are computed repetitively?
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RuntimeError: Error while creating shape using tf-xlm-roberta-large
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[ "Facing the same issue on on GCP + TPU, same TF and TPU versions. ", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n" ]
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I get the following runtime error after the 2nd fold. this is my model: maxlen = 50 `with strategy.scope(): #bert_encoder = TFBertModel.from_pretrained(model_name) base_model = TFAutoModel.from_pretrained(model_name) input_word_ids = tf.keras.Input(shape = (maxlen, ), dtype = tf.int32, n...
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[s2s] wmt download script use less ram
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6405?src=pr&el=h1) Report\n> Merging [#6405](https://codecov.io/gh/huggingface/transformers/pull/6405?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/b9ecd92ee4fcd515f542c73593a4b6fa0b2c81fc&el=desc) will **decrease...
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a few enhancement to https://github.com/huggingface/transformers/pull/6403 the main change: - rewrite not to load 100GB into RAM - wmt19 is huge! and then a few small things: - replaced the default dataset to wmt16 as it's much much smaller than wmt19 to experiment with (also it seems that at least wmt19-ru-en ...
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[lightning_base] fix s2s logging, only make train_loader once
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6404?src=pr&el=h1) Report\n> Merging [#6404](https://codecov.io/gh/huggingface/transformers/pull/6404?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/72add6c98f2c0607f088fa0c78d40f11e2efa4c4&el=desc) will **decrease...
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setup is called many times (incl twice by trainer.test), creating a dataloader each time. Will only creating a train_loader on the first call cause bad side effects that I don't understand @nateraw @williamFalcon ? I read docs [https://pytorch-lightning.readthedocs.io/en/latest/introduction_guide.html], so I think I...
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[s2s] Script to save wmt data to disk
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6403?src=pr&el=h1) Report\n> Merging [#6403](https://codecov.io/gh/huggingface/transformers/pull/6403?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/00bb0b25ed66a4878f2e0ffdd1ca65b7684db57e&el=desc) will **decrease...
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remove lr_scheduler redundancy
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[ "@sshleifer has a better version in works, closing." ]
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This PR solves https://github.com/huggingface/transformers/issues/6374 by removing a hardcoded `lr_scheduler` and switching to using the new method.
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[TF Longformer] Add Multiple Choice, Seq Classification Model
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[ "Hi !\r\nI'd like to help and work on this if that's ok.", "Awesome, feel free to open an issue :-) ", "Hello !\r\n\r\nI'm a bit lost here. I've looked at `modeling_tf_roberta.py` and `modeling_longformer.py` to create the class `TFLongformerForSequenceClassification`. I'm not sure if I am going in the right di...
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MEMBER
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# 🚀 Feature request `modeling_longformer.py` has the classes `LongformerForSequenceClassification`, `LongformerForMultipleChoice` and `LongformerForTokenClassification` which are not present in `modeling_tf_longformer.py` at the moment. Those classes should be equally added to `modeling_tf_longformer.py`. ## ...
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ZeroDivisionError with Reformer
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[ "Hey @eliasjacob, the problem is probably that `self.args.gradient_accumaltion_steps` is set to a value > then `(len(train_dataloader)`", "You were right (although I am unsure why the same notebook yielded different results in collab). Thank you very much!" ]
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## Environment info <!-- You can run the command `transformers-cli env` and copy-and-paste its output below. Don't forget to fill out the missing fields in that output! --> - `transformers` version: 3.0.0 - Platform: Linux-5.4.0-42-generic-x86_64-with-Ubuntu-18.04-bionic - Python version: 3.6.9 - PyTo...
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DPR retriever module
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[ "Pinging @lhoestq!", "Hi @mchari \r\n\r\nThe retriever is now part of the `nlp` library.\r\nYou can install it with\r\n\r\n```\r\npip install nlp\r\n```\r\n\r\nand load the retriever:\r\n```python\r\nfrom nlp import load_dataset\r\n\r\nwiki = load_dataset(\"wiki_dpr\", with_embeddings=False, with_index=True, spli...
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I see https://github.com/huggingface/transformers/pull/5279 that describes the DPR flow. Just checking to see when the retriever module will be available. Many thanks for making DPR available !
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Data collator with padding
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6398?src=pr&el=h1) Report\n> Merging [#6398](https://codecov.io/gh/huggingface/transformers/pull/6398?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/3425936643b157bda181af169b371dcf0a3ad3eb&el=desc) will **increase...
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Add a data collator to dynamically pad samples during batching. This is necessary for the training set since padding can't be applied beforehand if we use shuffling (unless with pad to a fixed `max_length`). This should make it more straightforward to plug nlp into the Trainer.
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Create README.md
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6397?src=pr&el=h1) Report\n> Merging [#6397](https://codecov.io/gh/huggingface/transformers/pull/6397?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/7ea9b2db3732904014b9121fb8a5c896ae00d4cf&el=desc) will **increase...
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For GPT-2 Arabic Poetry - https://huggingface.co/akhooli/gpt2-small-arabic-poetry
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switch Hindi-BERT to S3 README
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6396?src=pr&el=h1) Report\n> Merging [#6396](https://codecov.io/gh/huggingface/transformers/pull/6396?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/3e0fe3cf5c1059c04535de8f04f4efed7251adbe&el=desc) will **increase...
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The Markdown parser currently cuts off the CoLab URL (the last char is an underscore) on https://huggingface.co/monsoon-nlp/hindi-bert There are some other necessary updates, and I'd rather update this model card by pushing to S3 in the future
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Bug in the question answering pipeline
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[ "Hi! This bug was patched on `master`. Can you install from source and let me know if this fixes your issue? \r\n\r\n`pip install git+https://github.com/huggingface/transformers`", "This fixed it! Thank you!" ]
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## Environment info <!-- You can run the command `transformers-cli env` and copy-and-paste its output below. Don't forget to fill out the missing fields in that output! --> - `transformers` version: 3.0.2 - Platform: Linux-4.19.112+-x86_64-with-Ubuntu-18.04-bionic - Python version: 3.6.9 - PyTorch ver...
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Error while loading albert for token classification
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[ "Quick update:\r\nAbove code works just fine in Ubuntu environment with below specs:\r\n- `transformers` version: 3.0.2\r\n- Platform: Linux-5.3.0-1034-azure-x86_64-with-debian-buster-sid\r\n- Python version: 3.6.10\r\n- PyTorch version (GPU?): 1.5.1 (True)\r\n- Tensorflow version (GPU?): 2.0.0 (True)\r\n- Using GP...
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## Environment info - `transformers` version: 3.0.2 - Platform: Windows-10-10.0.18362-SP0 - Python version: 3.6.10 - PyTorch version (GPU?): not installed (NA) - Tensorflow version (GPU?): 2.2.0 (False) - Using GPU in script?: No - Using distributed or parallel set-up in script?: No ### Who can help @Lysandr...
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Add missing docker arg for TPU CI.
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6393?src=pr&el=h1) Report\n> Merging [#6393](https://codecov.io/gh/huggingface/transformers/pull/6393?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/3e0fe3cf5c1059c04535de8f04f4efed7251adbe&el=desc) will **decrease...
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Fixes `"docker build" requires exactly 1 argument.` for the path where `$CIRCLE_PR_NUMBER` is unset.
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seq2seq examples require pytest
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[ "yes, great catch. Will update!" ]
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## Environment info <!-- You can run the command `transformers-cli env` and copy-and-paste its output below. Don't forget to fill out the missing fields in that output! --> - `transformers` version: 3.0.2 - Platform: Linux-5.4.0-42-generic-x86_64-with-glibc2.29 - Python version: 3.8.2 - PyTorch versio...
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Fix links for open in colab
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This commit was supposed to be in #6389 but I didn't push hard enough.
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Warn if debug requested without TPU fixes (#6308)
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[ "The CircleCI failures look like a pre-existing line length violation in `trainer.py` and a checksum mismatch downloading transformers itself for `run_tests_torch`. I don't believe either are related to my change – I was able to run the examples test suite locally and everything passed. I'd be happy to fix the line...
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Check whether a PyTorch compatible TPU is available before attempting to print TPU metrics after training has completed. This way, users who apply `--debug` without reading the documentation aren't suprised by a stacktrace.
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Colab button
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This PR adds a "open in colab" button on the tutorials of our documentation. For each of those tutorials, three notebooks are available: mixed version (with cells PyTorch and TensorFlow), PyTorch-only and TensorFlow only, so hovering on the button makes a dropdown appear with the three different links. Those noteboo...
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[T5 3B Covid 19] Adapt T5 TF conversion script to handle covid-19 3b t5
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This PR shows which changes were necessary to convert the 3B (and 11B) T5 model from this issue: https://github.com/huggingface/transformers/tree/adapt_t5_for_covid_19_3b to PyTorch. It might be possible that the official T5 library has changed in which case this code might be useful again. For now, this PR stays...
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Fix docs and bad word tokens generation_utils.py
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6387?src=pr&el=h1) Report\n> Merging [#6387](https://codecov.io/gh/huggingface/transformers/pull/6387?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/155288f04ba9a5d0a0e4d5be4f6d4e808ad8cfff&el=desc) will **increase...
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This PR fixes two issues: 1. The codes https://github.com/huggingface/transformers/blob/6028ed92bd9e5471e6f8a1d23cfd95a3a63018fb/src/transformers/generation_utils.py#L224-L228 throw an exception `AssertionError: Greedy decoding will always produce the same output for num_beams == 1 and num_return_sequences > 1. ...
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Create README.md
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[POC] Notebooks cron
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Setting up a cron job to create the notebooks on the documentation
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AttributeError: type object "BartTokenizer" has no attribute 'name'
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[ "I think the notebook you are linking is trying to access the `name` attribute of `BartTokenizer` which does not exist indeed. It looks like the failure should be reported to the author of that notebook, it's not a bug in transformers.", "Pinging @ohmeow ", "Yah, I'm here :)\n\nOn Mon, Aug 10, 2020, 7:36 AM Sur...
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## Environment info <!-- You can run the command `transformers-cli env` and copy-and-paste its output below. Don't forget to fill out the missing fields in that output! --> - `transformers` version: 3.0.2 - Platform: Google Colab - Python version: 3.7 - PyTorch version (GPU?): - Tensorflow version (...
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hi
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## Environment info <!-- You can run the command `transformers-cli env` and copy-and-paste its output below. Don't forget to fill out the missing fields in that output! --> - `transformers` version: - Platform: - Python version: - PyTorch version (GPU?): - Tensorflow version (GPU?): - Using GPU in s...
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Ci GitHub caching
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Same as https://github.com/huggingface/transformers/pull/6287 but for Github Actions
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Create README.md
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6381?src=pr&el=h1) Report\n> Merging [#6381](https://codecov.io/gh/huggingface/transformers/pull/6381?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/6028ed92bd9e5471e6f8a1d23cfd95a3a63018fb&el=desc) will **decrease...
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Add metadata to be indexed properly
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Change metadata to be indexed correctly
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6379?src=pr&el=h1) Report\n> Merging [#6379](https://codecov.io/gh/huggingface/transformers/pull/6379?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/6028ed92bd9e5471e6f8a1d23cfd95a3a63018fb&el=desc) will **increase...
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6,378
Create README.md
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6378?src=pr&el=h1) Report\n> Merging [#6378](https://codecov.io/gh/huggingface/transformers/pull/6378?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/6028ed92bd9e5471e6f8a1d23cfd95a3a63018fb&el=desc) will **decrease...
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[EncoderDecoderModel] add a `add_cross_attention` boolean to config
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6377?src=pr&el=h1) Report\n> Merging [#6377](https://codecov.io/gh/huggingface/transformers/pull/6377?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/1429b920d44d610eaa0a6f48de43853da52e9c03&el=desc) will **decrease...
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The `EncoderDecoderModel` uses models from `AUTO_MODEL_FOR_CAUSAL_LM` as their decoder models. The problem is that these models can be used in two ways: 1) As a stand-alone decoder model (GPT2) like **without** cross-attention layers 2) As part of a `EncoderDecoderModel` **with** cross-attention layers. Currentl...
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Introduce dataset and data collator for Bert pretrain NSP
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[ "Superseded by #6644, thanks a lot for your contribution!" ]
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Follow up from discussion in https://github.com/huggingface/transformers/issues/6330 This PR introduces changes to allow both the LMML and NSP objectives to be run using ```BertForPretraining```.
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CUDA Out of Memory
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[ "Yes it seems like the GPU that was allocated to you does not provide enough GPU memory for the model" ]
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# ❓ Questions & Help <!-- The GitHub issue tracker is primarly intended for bugs, feature requests, new models and benchmarks, and migration questions. For all other questions, we direct you to the Hugging Face forum: https://discuss.huggingface.co/ . You can also try Stack Overflow (SO) where a wh...
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[s2s] remove lr_scheduler redundancy
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[ "Proposed solution here: https://github.com/huggingface/transformers/pull/6402\r\n" ]
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in `get_train_dataloader`
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Pegasus finetuning diary
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[ "freeze_embeds didn't matter (before mask fix)\r\nmask fix explanation: \r\nwe need `decoder_start_token_id=pad_token_id` to avoid the first word issue, but `decoder_padding_mask` should NOT tell the model to ignore that decoder_start_token_id, else you get nan.\r\n\r\nThis fix makes 1 example per batch not have eo...
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Best score so far .2065 Rouge, much worse than paper. Generations appear to start lower case/be missing words at the beginning. Clues: - adding `<pad>` as prefix (like for generation) makes loss nan for at least 1000 steps (I killed it). - Without prefix, loss is nan for 5 steps, them improves. - distillatio...
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Update modeling_tf_utils.py
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6372?src=pr&el=h1) Report\n> Merging [#6372](https://codecov.io/gh/huggingface/transformers/pull/6372?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/6e8a38568eb874f31eb49c42285c3a634fca12e7&el=desc) will **decrease...
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fix typo: ckeckpoint->checkpoint
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the test now works again
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6371?src=pr&el=h1) Report\n> Merging [#6371](https://codecov.io/gh/huggingface/transformers/pull/6371?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/6e8a38568eb874f31eb49c42285c3a634fca12e7&el=desc) will **increase...
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`test_finetune_lr_shedulers` can now run after https://github.com/huggingface/transformers/pull/6358 was merged
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FastTokenizer not returning batch_size for offset_mapping for short texts
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[ "After inspecting the code, it looks that the cause can be found inside `tokenization_utils_base.py`.\r\n\r\nThen, in the method `convert_to_tensors` form `BatchEncoding` there are the following lines:\r\n```python3\r\n# Do the tensor conversion in batch\r\nfor key, value in self.items():\r\n try:\r\n if ...
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## Environment info - `transformers` version: 3.0.2 - Platform: Linux-5.4.0-42-generic-x86_64-with-glibc2.10 - Python version: 3.8.2 - PyTorch version (GPU?): 1.6.0 (True) - Tensorflow version (GPU?): not installed (NA) - Using GPU in script?: No - Using distributed or parallel set-up in script?: No # Who can...
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trainer/lightning_base: Arbitrary config updates through command line
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[ "see `argparse.remainder` https://stackoverflow.com/questions/22850332/getting-the-remaining-arguments-in-argparse/46250042#46250042\r\n\r\nh/t @stas00 \r\n\r\n", "You could probably extract all the known args via `argparse`'s:\r\n```\r\nargs, unknown = parser.parse_known_args()\r\n```\r\nand then use another too...
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this issue [https://github.com/huggingface/transformers/issues/6367], and a recent one to add dropout to the command line, as well as the usage of task_specific_params during finetuning, are all one off solutions to address a larger problem. During finetuning/training, it is very difficult to arbitrarily set config att...
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Can't load a saved tokenizer with AutoTokenizer.from_pretrained without saving Config as well
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[ "@eladsegal I think that the `AutoTokenizer` requires the config file to determine what model to use. In https://huggingface.co/transformers/model_doc/auto.html it states that: \r\n\r\n> The from_pretrained() method takes care of returning the correct tokenizer class instance based on the model_type property of the...
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### Environment info - `transformers` version: master (https://github.com/huggingface/transformers/commit/6e8a38568eb874f31eb49c42285c3a634fca12e7) ### Who can help tokenizers: @mfuntowicz ### Information When saving a tokenizer with .save_pretrained, it can be loaded with the class it was saved with but not ...
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[s2s] pass max_length to config through command line
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Problem: In summarization, ideal beam search params vary between finetuning datasets. If you are finetuning pegasus-large on xsum, you want config.max_length=56, if you are finetuning pegasus-large on cnn-dailymail you want config.max_length=128. ### Solutions - the command line arg should be called `max_generate...
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[WIP] Lm loss feed forward chunking
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6366?src=pr&el=h1) Report\n> Merging [#6366](https://codecov.io/gh/huggingface/transformers/pull/6366?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/6e8a38568eb874f31eb49c42285c3a634fca12e7&el=desc) will **decrease...
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Final word embedding layer in LM loss calculation presents a bottleneck as the entire time dim - can be chunked similar to feed forward layers.
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Feed forward chunking others
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6365?src=pr&el=h1) Report\n> Merging [#6365](https://codecov.io/gh/huggingface/transformers/pull/6365?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/fb7330b30ebfbb3f07b87203f0405ee09905eeda&el=desc) will **increase...
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Adding feed forward chunking to other models. Based on #6024
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correct pl link in readme
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6364?src=pr&el=h1) Report\n> Merging [#6364](https://codecov.io/gh/huggingface/transformers/pull/6364?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/6e8a38568eb874f31eb49c42285c3a634fca12e7&el=desc) will **decrease...
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[s2s] add BartTranslationDistiller for distilling mBART
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6363?src=pr&el=h1) Report\n> Merging [#6363](https://codecov.io/gh/huggingface/transformers/pull/6363?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/be1520d3a3c09d729649c49fa3163bd938b6a238&el=desc) will **decrease...
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New class `BartTranslationDistiller` does the same distillation method as `SummarizationDistiller`, but computes BLEU scores instead of ROUGE scores. It also accepts `--src_lang` and `--tgt_lang` arguments from the command line. There is one strong checkpoint already posted at `sshleifer/distillmbart-12-6/`. I will ...
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[TFTrainer] Error "iterating over `tf.Tensor` is not allowed"
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[ "The following bug on Tensorflow could be related: https://github.com/tensorflow/tensorflow/issues/42119", "Was just a Dataset setup issue. The correct setup for the Dataset can be seen here https://github.com/huggingface/transformers/issues/6551" ]
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## Environment info <!-- You can run the command `transformers-cli env` and copy-and-paste its output below. Don't forget to fill out the missing fields in that output! --> - `transformers` version: 3.0.2 (from pip) - Platform: Linux-4.15.0-91-generic-x86_64-with-Ubuntu-18.04-bionic - Python version: 3...
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lr_schedulers: add get_polynomial_decay_schedule_with_warmup
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6361?src=pr&el=h1) Report\n> Merging [#6361](https://codecov.io/gh/huggingface/transformers/pull/6361?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/bd0eab351a338175053998ddfc059f1cb6424ab4&el=desc) will **increase...
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this PR adds a new scheduler plus test, code is based on amalgamation of a few different implementations I'm not sure it's 100% correct - needs more experimenting - but feedback is welcome. For reference here are 3 different implementations of this scheduler: 1. https://github.com/pyprob/pyprob/blob/master/pypro...
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Bug in squad example with XLNet
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[ "see also #3535", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n" ]
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## Environment info <!-- You can run the command `transformers-cli env` and copy-and-paste its output below. Don't forget to fill out the missing fields in that output! --> - `transformers` version: 3.0.2 - Platform: Linux-3.10.0-957.21.2.el7.x86_64-x86_64-with-centos-7.6.1810-Core - Python version: 3....
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Mult rouge by 100: standard units
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[ "I have no knowledge of ROUGE and why this would be necessary, so probably not the best person to review :-)" ]
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[s2s] fix --gpus clarg collision
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6358?src=pr&el=h1) Report\n> Merging [#6358](https://codecov.io/gh/huggingface/transformers/pull/6358?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/1aec991643a6fec0e7d504626fc68347fe93b658&el=desc) will **increase...
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### Problem finetune.py adds all the default pl args with this line ``` parser = pl.Trainer.add_argparse_args(parser) ``` and all the generic args from `add_generic_args`. ### Solution This moves the overlapping arg from lightning_base.py to the 2 pl examples that need it. CC @stas00 @patil-suraj
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6357?src=pr&el=h1) Report\n> Merging [#6357](https://codecov.io/gh/huggingface/transformers/pull/6357?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/1aec991643a6fec0e7d504626fc68347fe93b658&el=desc) will **increase...
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GPU memory consumption increases while training
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[ "Hey @sangnguyen7, \r\n\r\nIs there a reason to rerun these steps:\r\n\r\n```python\r\nmodel.train()\r\nmodel(**encode)\r\n!nvidia-smi\r\n```\r\nover and over again. I think what might happen here is that pytorch is saving more and more activations of the forward pass in each node of the model and thus will run out...
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## Environment info <!-- You can run the command `transformers-cli env` and copy-and-paste its output below. Don't forget to fill out the missing fields in that output! --> - `transformers` version: 3.0.2 - Platform: Google Colab - Python version: 3.6 - PyTorch version (GPU?): 1.6 - Tensorflow vers...
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BartModel decodes sequence of incorrect length when decoder_input_ids is specified / Output shape mismatch due to when `use_cache` True/False
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[ "@patrickvonplaten Actually, going over [the source code ](https://huggingface.co/transformers/_modules/transformers/modeling_bart.html#BartModel), I found that the exact line in the definition of `class BartModel(PretrainedBartModel)` that was causing this problem is:\r\n```python\r\nuse_cache = use_cache if use_c...
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From the [Bart docs](https://huggingface.co/transformers/model_doc/bart.html#bartmodel), the `decoder_input_ids` attribute should be a tensor of shape `(batch_size, target_sequence_length)`. If we call a `BartModel` without specifying `decoder_input_ids`, the decoded sequence length correctly matches that of `input_ids...
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[GPT2] Correct typo in docs
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6352?src=pr&el=h1) Report\n> Merging [#6352](https://codecov.io/gh/huggingface/transformers/pull/6352?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/9f57e39f7165fa8bd6ac911852221a76d4b79ebe&el=desc) will **decrease...
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Why is distillbart-cnn done with no teacher and distilbart-xsum has a teacher?
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[ "It's purely empirical. `distilbart-xsum` variants perform about 1-2 ROUGE pts worse without a teacher, the gap is basically 0 for the `distilbart-cnn` variants. For translation, it seems like teacher also helps a bit.\r\n", "In the future, you can tag me on discussion questions on discuss.huggingface.co !", "...
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@sshleifer Can you expand on why distillbart-xsum is done with a teacher and distillbart-cnn is not?
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Add model card for electra-base-turkish-cased-ner
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[ "Why is the test for `build_doc` failing?", "The CI failure is unrelated. Thanks for sharing!" ]
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[testing] USE_CUDA default and intuitive skip decorators
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[ "Perhaps, while we are at it, it'd be good to discuss the related skip decorators. **Please let me know whether this is different enough and should be in its own issue.**\r\n\r\nThese are the torch-related skip decorators we [currently have](https://github.com/huggingface/transformers/blob/master/src/transformers/t...
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This library's primarily use is for gpu work, and currently many tests won't run even if gpu is available, since the current setup wants env var `USE_CUDA` to be true for anything to happen. It's easy to forget to manually add this env var to pytest command line. To maximize the testing potential I propose that onl...
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[Bart] Cannot use Bart decoder cache with torchscript
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[ "After having fixed the bug it would be great if this line: https://github.com/huggingface/transformers/blob/ac001c48b8df1f5aadcc8cf2c71d7c1116c05250/tests/test_modeling_common.py#L252 can be removed so that a test for Bart + `past_key_value` is enabled.", "thanks for writing such a good issue, I'll take a look t...
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## Environment info <!-- You can run the command `transformers-cli env` and copy-and-paste its output below. Don't forget to fill out the missing fields in that output! --> - `transformers` version: 3.0.2 - Platform: Linux-4.15.0-111-generic-x86_64-with-Ubuntu-18.04-bionic - Python version: 3.7.5 - Py...
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ModuleNotFoundError: No module named 'transformers' on Google Colab
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[ "@Mohd-Misran seems to be working for me \r\n![image](https://user-images.githubusercontent.com/14134797/89741111-4e53cc00-da43-11ea-9a09-94431217301e.png). \r\n\r\nMaybe try to open a new colab notebook?\r\n", "You need to restart your Colab runtime after installing new dependencies" ]
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I installed **transformers** using the command `!pip install transformers` on **Google Colab Notebook** But then I try to `import transformers` it throws an error. This is the output of the pip install command: Requirement already satisfied: transformers in /usr/local/lib/python3.6/dist-packages/transformers-3.0...
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Create README.md
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6346?src=pr&el=h1) Report\n> Merging [#6346](https://codecov.io/gh/huggingface/transformers/pull/6346?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/9f57e39f7165fa8bd6ac911852221a76d4b79ebe&el=desc) will **decrease...
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Is it necessary to provide attention_mask, or model will calculate itself?
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[ "If you do not pass an `attention_mask` then the `attention_mask` will automatically set to all ones (`[1, 1, 1, ...,]`). Meanning that every token is attended to (no token is masked). Also check out the docs here: https://huggingface.co/transformers/glossary.html#attention-mask.\r\n\r\nIf your `input_ids` contain ...
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Is it necessary to provide attention_mask, or model will calculate itself?
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[s2s] fix label_smoothed_nll_loss
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[ "I think `sum` is good. Ideally, we should divide by the number of non pad tokens, but I'm gunna merge this and then we can experiment with more complicated transformations. Thanks for the fix!", "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6344?src=pr&el=h1) Report\n> Merging [#6344](https://...
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Regarding issue #4576 Regarding reduction, fairseq does reduce using 'sum' for both [cross_entropy](https://fairseq.readthedocs.io/en/latest/_modules/fairseq/criterions/cross_entropy.html#CrossEntropyCriterion) and [label_smoothed_cross_entropy](https://fairseq.readthedocs.io/en/latest/_modules/fairseq/criterions/l...
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The default cache directory is lack of disk capacity, I need change the configure of the default cache directory.
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[ "Please try to write better posts in the future. This is just lazy.\r\n\r\nYou can set the directory for a cache with the `TRANSFORMERS_CACHE` environment variable.", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank y...
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# 🚀 Feature request <!-- A clear and concise description of the feature proposal. Please provide a link to the paper and code in case they exist. --> ## Motivation <!-- Please outline the motivation for the proposal. Is your feature request related to a problem? e.g., I'm always frustrated when [....
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[marian] converter supports models from new Tatoeba project
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6342?src=pr&el=h1) Report\n> Merging [#6342](https://codecov.io/gh/huggingface/transformers/pull/6342?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/fb7330b30ebfbb3f07b87203f0405ee09905eeda&el=desc) will **increase...
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- no state dict change, just need to read model metadata from a new path - we only accept models with 7 letter names... like `ara-eng`. This is the new format. - added integration test for `ara-eng` Done: - [x] upload 300 models: all new ones that were not "dominated" by a model we already have, where dominated m...
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[s2s] tiny QOL improvement: run_eval prints scores
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6341?src=pr&el=h1) Report\n> Merging [#6341](https://codecov.io/gh/huggingface/transformers/pull/6341?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/322dffc6c9a44fd504b24b0efcbcaa419b577a93&el=desc) will **increase...
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its annoying to have to cat a file to see the scores after calling run_eval.py
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PegasusForConditionalGeneration (torch version)
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6340?src=pr&el=h1) Report\n> Merging [#6340](https://codecov.io/gh/huggingface/transformers/pull/6340?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f6cb0f806efecb64df40c946dacaad0adad33d53&el=desc) will **increase...
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This PR adds, [pegasus](https://arxiv.org/abs/1912.08777), a SOTA summarization model ported from [tf1] (https://github.com/google-research/pegasus) in collaboration with @JingqingZ . More info on the model can be found in `pegasus.rst` under Files changed. Config: [here](https://s3.amazonaws.com/models.huggingface...
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refactor almost identical tests
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6339?src=pr&el=h1) Report\n> Merging [#6339](https://codecov.io/gh/huggingface/transformers/pull/6339?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/322dffc6c9a44fd504b24b0efcbcaa419b577a93&el=desc) will **decrease...
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in preparation for adding more schedulers this PR refactors these almost identical tests. Unfortunately [can't use `pytest.mark.parametrize`](https://docs.pytest.org/en/latest/unittest.html#pytest-features-in-unittest-testcase-subclasses), so the only drawback that it makes them all into a single test. It'd have bee...
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remove a TODO item to use a tiny model
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6338?src=pr&el=h1) Report\n> Merging [#6338](https://codecov.io/gh/huggingface/transformers/pull/6338?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/1f8e8265188de8b76f5c28539056d6eb772e4e0f&el=desc) will **increase...
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as discussed with @sshleifer, removing this TODO to switch to a tiny model, since it won't be able to test the qualitative results of the evaluation (i.e. the results are meaningless).
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6,337
[CI] add manual workflow dispatch option to github actions runners
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https://github.blog/changelog/2020-07-06-github-actions-manual-triggers-with-workflow_dispatch/
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broken ONNX slow test
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[ "This seems to be a bit of a flaky test, doesn't it?", "There is strange try/except syntax in `_test_export ` that I think can be trivially improved." ]
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``` def test_quantize_pytorch(self): for model in OnnxExportTestCase.MODEL_TO_TEST: path = self._test_export(model, "pt", 12) > quantized_path = quantize(Path(path)) ``` tests/test_onnx.py:75: `path` is None https://github.com/huggingface/transformers/runs/960368281?check_sui...
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6,335
delete unused tiny models
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[ "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n" ]
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``` [ok] bart-tiny-random/ [ok] tiny-marian-en-de/ [ok] tiny-mbart/ [deleted] distilbert_tiny_random/ [ok] tiny-ctrl/ PRE tiny-dbmdz-bert-large-cased-fi...
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[WIP] Avoid call to torch.triu
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add tests/test_tokenization_reformer.py
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[ "I can help with this.", "Awesome!", "@sshleifer I put together the test code and find that the following test is failing:\r\n\r\n```\r\nself = < tests.test_tokenization_reformer.ReformerTokenizationTest\r\ntestMethod = test_torch_encode_plus_sent_to_model \r\n@slow\r\n@require_torch\r\ndef test_torch_encode_pl...
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I don't think there is any common test coverage for ReformerTokenizer. besides through integration tests. Good source for copy/modification is `XLMRobertaTokenizationTest`
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6,332
[CI] Self-scheduled runner also pins torch
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[ "merging to fix CI", "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6332?src=pr&el=h1) Report\n> Merging [#6332](https://codecov.io/gh/huggingface/transformers/pull/6332?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/6695450a23545bc9d5416f39ab39609c7811c653&e...
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CONTRIBUTOR
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```bash pip install torch!=1.6.0 --no-cache-dir ```
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6,331
Delete this line in label_smoothed_nll_loss
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CONTRIBUTOR
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```python bs = pad_mask.long().sum() ```
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6,330
BertForPreTraining with NSP
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[ "Hi! Supporting the NSP objective is not on our roadmap, due to the reason you've linked and because of insufficient bandwidth. \r\n\r\nHowever, similar to the work in #6168 for SOP, we're very open to contributions and would accept a PR adding the BERT NSP objective to the datacollators/datasets.", "Awesome, I'v...
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# ❓ Questions & Help ## Details I am trying to train BERT from scratch following a modification of https://huggingface.co/blog/how-to-train, where I use a BertTokenizer and BertForPreTraining. The [documentation for BertForPreTraining](https://huggingface.co/transformers/model_doc/bert.html#transformers.BertForPreT...
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OSError: Model name 'lonePatient/albert_chinese_small' was not found in tokenizers model
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[ "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n" ]
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NONE
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my code: from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("lonePatient/albert_chinese_small") model = AutoModel.from_pretrained("lonePatient/albert_chinese_small") model.save_pretrained("lonePatient+albert_chinese_small") +++++++++++ Downloading: 100%|███████████...
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Small docfile fixes
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6328?src=pr&el=h1) Report\n> Merging [#6328](https://codecov.io/gh/huggingface/transformers/pull/6328?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/2f2aa0c89cab9a77560e6845578f917a61081c67&el=desc) will **increase...
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COLLABORATOR
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Nothing major, just a few fixes to make the files work with the coming notebook conversion.
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6,327
Batched pipeline
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[ "Yes, building off of the model and example [here](https://huggingface.co/twmkn9/albert-base-v2-squad2): \r\n\r\n```\r\nfrom transformers.pipelines import pipeline\r\n\r\nmodel_name = \"twmkn9/albert-base-v2-squad2\"\r\nnlp = pipeline('question-answering', model=model_name, tokenizer=model_name)\r\nQA_input = {\r\n...
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Hi, Is there a way to run batches with QuestionAnsweringPipeline rather than just one example? Thanks.
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Patch models
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[ "Side note, if you rebase, you can remove those models from the special ignore list in the `check_repo` script." ]
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Text-to-SQL Query
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[ "pinging @mrm8488 .", "You can try this model: https://huggingface.co/mrm8488/t5-base-finetuned-wikiSQL\r\nThanks for ping me @patil-suraj ", "If you go to the model hub and type 'SQL', you get [this](https://huggingface.co/models?search=Sql). There are currently 3 variants of the T5 model fine-tuned on WikiSQL...
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# ❓ Questions & Help Hello everyone, I got a task that I want to use NLP for convert text into a SQL query. Anyone knows how to do this or got any suggestion? Thanks.
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Create README.md
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[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6324?src=pr&el=h1) Report\n> Merging [#6324](https://codecov.io/gh/huggingface/transformers/pull/6324?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/7e9861f7f4ab137cf102dae9cf6957c1c402c022&el=desc) will **decrease...
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Hi , I am having trouble locating the transformers/examples/summarization/bart/ file. I was wondering if it has been renamed or changed?
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[ "Think it was moved to the seq2seq directory: https://github.com/huggingface/transformers/tree/master/examples/seq2seq", "Thanks!" ]
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# ❓ Questions & Help <!-- The GitHub issue tracker is primarly intended for bugs, feature requests, new models and benchmarks, and migration questions. For all other questions, we direct you to the Hugging Face forum: https://discuss.huggingface.co/ . You can also try Stack Overflow (SO) where a wh...
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Transformer-XL: Improved tokenization with sacremoses
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[ "`ci/circleci: check_code_quality` fails for me due to Python 3.6 is not compatible with PyTorch 1.6. Any ideas how to fix this?", "Pinging @n1t0 and @TevenLeScao (in holidays right now, will be back next week!)", "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6322?src=pr&el=h1) Report\n> Merg...
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Fixes #5136 As explained in the above issue, this PR fixes the tokenization of the TransfoXLTokenizer by using the sacremoses library with an extended feature of tokenizing comma-separated and floating point numbers. That way the input text is tokenized the same way as in the WikiText-103 dateset used for pretrainin...
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