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https://api.github.com/repos/huggingface/transformers/issues/8221 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8221/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8221/comments | https://api.github.com/repos/huggingface/transformers/issues/8221/events | https://github.com/huggingface/transformers/issues/8221 | 733,985,169 | MDU6SXNzdWU3MzM5ODUxNjk= | 8,221 | [GPT2] Loss NaN after some time with FP16 | {
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"We can't really help without seeing the code you are running. Some of the models do not support FP16 for instance, and we have no idea which model you are using.",
"Oh, sorry. It's the example script ```examples/language_modeling/run_language_modeling.py``` but with modified data loader.\r\n\r\nfull code below:\... | 1,604 | 1,610 | 1,610 | NONE | null | ## 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: 3.4.0
- Platform: Linux-4.4.0-176-generic-x86_64-with-glibc2.17
- Python version: 3.8.6
- PyTorch versi... | {
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https://api.github.com/repos/huggingface/transformers/issues/8220 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8220/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8220/comments | https://api.github.com/repos/huggingface/transformers/issues/8220/events | https://github.com/huggingface/transformers/issues/8220 | 733,953,625 | MDU6SXNzdWU3MzM5NTM2MjU= | 8,220 | Example for running T5 for translation | {
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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"
] | 1,604 | 1,610 | 1,610 | NONE | null | Hi,
I am having hard time finetuning T5-small on WMT-14 de/en and bleu score does go high. I followed the notebooks of question answering with T5, is there any specific point to consider for translation, so any specific parameter which needs to be given to model.generate ?
could you assist me with showing me some ex... | {
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https://api.github.com/repos/huggingface/transformers/issues/8219 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8219/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8219/comments | https://api.github.com/repos/huggingface/transformers/issues/8219/events | https://github.com/huggingface/transformers/issues/8219 | 733,940,916 | MDU6SXNzdWU3MzM5NDA5MTY= | 8,219 | Roberta weights are not initialized loading the bare Roberta | {
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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"
] | 1,604 | 1,610 | 1,610 | NONE | null | ## 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: '3.4.0'
- Platform: Colab
- Python version:
- PyTorch version (GPU?):
- Tensorflow version (GPU?): 2.... | {
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https://api.github.com/repos/huggingface/transformers/issues/8218 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8218/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8218/comments | https://api.github.com/repos/huggingface/transformers/issues/8218/events | https://github.com/huggingface/transformers/issues/8218 | 733,931,827 | MDU6SXNzdWU3MzM5MzE4Mjc= | 8,218 | ValueError: decoder_start_token_id or bos_token_id has to be defined for encoder-decoder generation | {
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"Hi,\r\ncould you assist in adding an example in tutorial for this, I followed the tutorial sample for summarization, Is the way I made my inputs (\"Question: Question sequence \") correct? thanks \r\nhere is the tutorial sample: \r\n```\r\n>>> input_ids = tokenizer(\"summarize: studies have shown that owning a do... | 1,604 | 1,604 | 1,604 | NONE | null | Hi
I followed the tutorial for generation with T5, and I made my input as "Question: Question sequence ", and target as "Target sequence", then I use tokenizer.batch_encode_plus to encode the sentence and then I call generate as:
model.generate(batch[input_ids], attention_mask=..., max_length=..., early_stopping=T... | {
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https://api.github.com/repos/huggingface/transformers/issues/8216 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8216/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8216/comments | https://api.github.com/repos/huggingface/transformers/issues/8216/events | https://github.com/huggingface/transformers/issues/8216 | 733,915,449 | MDU6SXNzdWU3MzM5MTU0NDk= | 8,216 | tokenizer's is_split_into_words seems not work | {
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"wrongly posted. I delete it."
] | 1,604 | 1,604 | 1,604 | NONE | null | I input tokenized list of tokens, but it return different result(not count pad token). It seems tokenize pretokenized tokens, ignoring `is_split_into_words`. Please refer to the code below:
```
sent = "the latest investigation was authorized after the supreme court in 2007 found dcc and its founder , jim flavin , g... | {
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https://api.github.com/repos/huggingface/transformers/issues/8215 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8215/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8215/comments | https://api.github.com/repos/huggingface/transformers/issues/8215/events | https://github.com/huggingface/transformers/issues/8215 | 733,913,568 | MDU6SXNzdWU3MzM5MTM1Njg= | 8,215 | Setting os.environ['CUDA_VISIBLE_DEVICES'] = ‘1’, but always training on GPU0, how to set it(GPT2)? | {
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"Hi @TheoRenLi, this question should go on https://discuss.huggingface.co\r\n\r\nWe keep the issues of the repo for bug and features request (with clear descriptions).",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Than... | 1,604 | 1,610 | 1,610 | NONE | null | # ❓ 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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https://api.github.com/repos/huggingface/transformers/issues/8217 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8217/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8217/comments | https://api.github.com/repos/huggingface/transformers/issues/8217/events | https://github.com/huggingface/transformers/issues/8217 | 733,919,619 | MDU6SXNzdWU3MzM5MTk2MTk= | 8,217 | tokenizer "is_split_into_words" seems not work | {
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"the same issue, is there any workaround?",
"same issue, I think there is a bug in PreTrainedTokenizer class\r\n```\r\n def get_input_ids(text):\r\n print(text)\r\n if isinstance(text, str):\r\n tokens = self.tokenize(text, **kwargs)\r\n return self.conv... | 1,604 | 1,649 | 1,606 | NONE | null | I input tokenized list of tokens, but it return different result(not count pad token). It seems tokenize pretokenized tokens, ignoring `is_split_into_words`. Please refer to the code below:
```
sent = "the latest investigation was authorized after the supreme court in 2007 found dcc and its founder , jim flavin , g... | {
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https://api.github.com/repos/huggingface/transformers/issues/8214 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8214/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8214/comments | https://api.github.com/repos/huggingface/transformers/issues/8214/events | https://github.com/huggingface/transformers/issues/8214 | 733,870,808 | MDU6SXNzdWU3MzM4NzA4MDg= | 8,214 | [Benchmark] | {
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## 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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https://api.github.com/repos/huggingface/transformers/issues/8213 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8213/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8213/comments | https://api.github.com/repos/huggingface/transformers/issues/8213/events | https://github.com/huggingface/transformers/pull/8213 | 733,835,108 | MDExOlB1bGxSZXF1ZXN0NTEzNTE4MDUy | 8,213 | Fix ignore files behavior in doctests | {
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I also fixed typing issues in the file and oth... | {
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https://api.github.com/repos/huggingface/transformers/issues/8212 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8212/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8212/comments | https://api.github.com/repos/huggingface/transformers/issues/8212/events | https://github.com/huggingface/transformers/issues/8212 | 733,804,394 | MDU6SXNzdWU3MzM4MDQzOTQ= | 8,212 | Pickle error | {
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"Can you give all the information you can about your environment and pip list and I’m pinging @lhoestq.\r\n\r\nIf you can manage to reproduce the error in a google colab or shareable environment that would be the top for debugging.",
"@VictorSanh got a similar issue once. Did you install transformers using `pip ... | 1,604 | 1,604 | 1,604 | NONE | null | While fine-tuning BERT with the new [script](https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm.py) I am facing the issue as follows:
```
Traceback (most recent call last):
File "run_mlm.py", line 310, in <module>
main()
File "run_mlm.py", line 259, in main
lo... | {
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https://api.github.com/repos/huggingface/transformers/issues/8211 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8211/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8211/comments | https://api.github.com/repos/huggingface/transformers/issues/8211/events | https://github.com/huggingface/transformers/issues/8211 | 733,789,766 | MDU6SXNzdWU3MzM3ODk3NjY= | 8,211 | Appropriate dataset format for language modeling example | {
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"General questions should be asked on the [forum](https://discuss.huggingface.co/) as we keep the issues for bugs.\r\n`run_clm` doesn't use the approach of taking the different lines of a dataset (that's in `run_mlm` as it's usually done for masked language modeling) so you will have to tweak the example script to ... | 1,604 | 1,604 | 1,604 | NONE | null | # What is the most memory efficient way/best way to format your dataset file for language modeling?
## Details
I am running run_clm.py and can only get my dataset to work with the smallest GPT2 model. I would like to experiment with gpt2-xl ideally but would settle for large and xlnet. I am using distributed training... | {
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https://api.github.com/repos/huggingface/transformers/issues/8210 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8210/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8210/comments | https://api.github.com/repos/huggingface/transformers/issues/8210/events | https://github.com/huggingface/transformers/issues/8210 | 733,782,398 | MDU6SXNzdWU3MzM3ODIzOTg= | 8,210 | Simple import issue for run_clm.py | {
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"Hi there, as mentioned in the README of the examples (in bold), you need to install transformers [from source](https://huggingface.co/transformers/installation.html#installing-from-source) to use that script.",
"I did thank, you for the rapid reply! Comfortable programmer, files not so much so again thank you fo... | 1,604 | 1,626 | 1,604 | NONE | null | ## Environment info
- `transformers` version: 3.4.0
- Platform: Linux-4.19.112+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.9
- PyTorch version (GPU?): 1.6.0+cu101 (True)
- Tensorflow version (GPU?): 2.3.0 (True)
- Using GPU in script?: yes
- Using distributed or parallel set-up in script?: no
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https://api.github.com/repos/huggingface/transformers/issues/8209 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8209/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8209/comments | https://api.github.com/repos/huggingface/transformers/issues/8209/events | https://github.com/huggingface/transformers/issues/8209 | 733,723,156 | MDU6SXNzdWU3MzM3MjMxNTY= | 8,209 | XLMRobertaTokenizer potential bug | {
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"Indeed this seems a bit strange.\r\n\r\nPining @n1t0 and @Narsil here (actually this should probably rather be an issue in the https://github.com/huggingface/tokenizers repo)",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occu... | 1,604 | 1,619 | 1,619 | NONE | null | ## Environment info
- `transformers` version: 3.4.0
- Platform: Linux-5.4.60-1-pve-x86_64-with-debian-buster-sid
- Python version: 3.6.3
- PyTorch version (GPU?): 1.7.0 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: no
- Using distributed or parallel set-up in script?: no
###... | {
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https://api.github.com/repos/huggingface/transformers/issues/8208 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8208/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8208/comments | https://api.github.com/repos/huggingface/transformers/issues/8208/events | https://github.com/huggingface/transformers/issues/8208 | 733,701,576 | MDU6SXNzdWU3MzM3MDE1NzY= | 8,208 | Poor f1 score when validating existing 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"
] | 1,604 | 1,610 | 1,610 | NONE | null | I have been attempting to validate the results on several models, but have been unable to match them with the results posted on the model cards.
For example, I took an Albert model: https://huggingface.co/ahotrod/albert_xxlargev1_squad2_512
and I run:
```
python run_squad.py
--model_type albert
--model_name_o... | {
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https://api.github.com/repos/huggingface/transformers/issues/8207 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8207/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8207/comments | https://api.github.com/repos/huggingface/transformers/issues/8207/events | https://github.com/huggingface/transformers/pull/8207 | 733,687,432 | MDExOlB1bGxSZXF1ZXN0NTEzNDA5MDgz | 8,207 | Updated ConversationalPipeline to work with encoder-decoder models | {
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"> Looks great! Can we maybe add one test with the small `BlenderbotModel` to `/home/patrick/hugging_face/transformers/tests/test_pipelines_conversational.py` ?\r\n\r\nThank you @patrickvonplaten , I added an integration test using BlenderBot 90M.",
"Merging, unrelated failure."
] | 1,604 | 1,604 | 1,604 | CONTRIBUTOR | null | # What does this PR do?
This PR extends the capabilities of the existing ConversationalPipeline to work with Encoder Decoder models (such as BlenderBot).
The pipeline has been modified as follows:
- history generated from concatenation of the inputs to the generated tokens for encoder-decoder (decoders use dire... | {
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https://api.github.com/repos/huggingface/transformers/issues/8206 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8206/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8206/comments | https://api.github.com/repos/huggingface/transformers/issues/8206/events | https://github.com/huggingface/transformers/issues/8206 | 733,686,719 | MDU6SXNzdWU3MzM2ODY3MTk= | 8,206 | Sentence transformer Segmentation Fault - Pytorch 1.4.0, 2.80 | {
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"This will also be fixed by #8073 ",
"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"
] | 1,604 | 1,610 | 1,610 | NONE | null | ## 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: Linux
- Python version: 3.7
- PyTorch version (GPU?): 1.4 (Both)
- Tensorflow version (G... | {
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https://api.github.com/repos/huggingface/transformers/issues/8205 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8205/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8205/comments | https://api.github.com/repos/huggingface/transformers/issues/8205/events | https://github.com/huggingface/transformers/pull/8205 | 733,677,350 | MDExOlB1bGxSZXF1ZXN0NTEzNDAxODk4 | 8,205 | [Bug fix] Fixed value for BlenderBot pad token | {
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The current `BlenderbotSmallTokenizer` has an incorrect (probably a typo) value for the `pad_token`. This causes the BlenderBot model to crash on padded sequences (currently pads with a value that exceeds the embedding matrix size).
This PR fixes the behaviour and the tokenizer now pads co... | {
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https://api.github.com/repos/huggingface/transformers/issues/8204 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8204/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8204/comments | https://api.github.com/repos/huggingface/transformers/issues/8204/events | https://github.com/huggingface/transformers/issues/8204 | 733,627,414 | MDU6SXNzdWU3MzM2Mjc0MTQ= | 8,204 | [Benchmark] | {
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## 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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https://api.github.com/repos/huggingface/transformers/issues/8203 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8203/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8203/comments | https://api.github.com/repos/huggingface/transformers/issues/8203/events | https://github.com/huggingface/transformers/pull/8203 | 733,618,936 | MDExOlB1bGxSZXF1ZXN0NTEzMzYyODE1 | 8,203 | Add TFDPR | {
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"Hi @LysandreJik , thanks for the great review! \r\nI will fix and test the code as suggested.\r\n\r\nHowever, I have a very newbie question about style and document fixing. I admit that I can access only Colab (I have only windows PC) so I am really not sure how to do `make fixup` and `make docs` (in my understan... | 1,604 | 1,608 | 1,605 | CONTRIBUTOR | null | # What does this PR do?
Add `TFDPRContextEncoder, TFDPRQuestionEncoder` and `TFDPRReader` in `modeling_tf_dpr.py`, as well as other relevant files in the [checklist](https://github.com/huggingface/transformers/tree/master/templates/adding_a_new_model) .
Now the TF model works properly and can load Pytorch's weig... | {
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https://api.github.com/repos/huggingface/transformers/issues/8202 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8202/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8202/comments | https://api.github.com/repos/huggingface/transformers/issues/8202/events | https://github.com/huggingface/transformers/issues/8202 | 733,596,217 | MDU6SXNzdWU3MzM1OTYyMTc= | 8,202 | 'SummaryWriter' object has no attribute 'add_hparams' | {
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<!-- 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: 3.4.0
- Platform: Linux-4.15.0-72-generic-x86_64-with-debian-buster-sid
- Python version: 3.6.12
- PyTo... | {
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https://api.github.com/repos/huggingface/transformers/issues/8201 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8201/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8201/comments | https://api.github.com/repos/huggingface/transformers/issues/8201/events | https://github.com/huggingface/transformers/issues/8201 | 733,591,224 | MDU6SXNzdWU3MzM1OTEyMjQ= | 8,201 | New model addition | {
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"##",
"P#86",
"user blocked"
] | 1,604 | 1,604 | 1,604 | NONE | null | # 🌟 New model addition
## Model description
<!-- Important information -->
## Open source status
* [x] the model implementation is available: (give details)
* [ ] the model weights are available: (give details)
* [x] who are the authors: (mention them, if possible by @gh-username)
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https://api.github.com/repos/huggingface/transformers/issues/8200 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8200/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8200/comments | https://api.github.com/repos/huggingface/transformers/issues/8200/events | https://github.com/huggingface/transformers/issues/8200 | 733,584,454 | MDU6SXNzdWU3MzM1ODQ0NTQ= | 8,200 | Mmmmianam | {
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"😁",
"#876 "
] | 1,604 | 1,604 | 1,604 | NONE | null | # 🚀 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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https://api.github.com/repos/huggingface/transformers/issues/8199 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8199/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8199/comments | https://api.github.com/repos/huggingface/transformers/issues/8199/events | https://github.com/huggingface/transformers/issues/8199 | 733,509,030 | MDU6SXNzdWU3MzM1MDkwMzA= | 8,199 | Sentencepiece dependency causing docker build to fail | {
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"This will be fixed when #8073 is merged.",
"Is there any help in terms of what version to pin to in order to avoid this? This is currently a huge blocker on my end.",
"On the sentencepiece side I don’t know (you can open an issue on their side to ask) but on the `transformers` side we are actively working on r... | 1,604 | 1,610 | 1,610 | NONE | null | ## 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:3.4.0
- Platform:Ubuntu 18.04
- Python version: 3.7
- PyTorch version (GPU?): 1.7.0 no gpu
- Tensorflow... | {
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https://api.github.com/repos/huggingface/transformers/issues/8198 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8198/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8198/comments | https://api.github.com/repos/huggingface/transformers/issues/8198/events | https://github.com/huggingface/transformers/pull/8198 | 733,485,723 | MDExOlB1bGxSZXF1ZXN0NTEzMjU5NDA2 | 8,198 | Added 12 model cards for Indian Language Models | {
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"Wow, so cool! Thanks for your contribution."
] | 1,604 | 1,604 | 1,604 | CONTRIBUTOR | null | # What does this PR do?
This PR adds model cards for 12 language models which have been uploaded to the model hub recently over [here](https://huggingface.co/neuralspace-reverie). These cover 3 Indian languages and for each language there are 4 model variants namely: BERT, DistilBERT, RoBERTa and XLM-R.
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https://api.github.com/repos/huggingface/transformers/issues/8197 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8197/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8197/comments | https://api.github.com/repos/huggingface/transformers/issues/8197/events | https://github.com/huggingface/transformers/pull/8197 | 733,454,689 | MDExOlB1bGxSZXF1ZXN0NTEzMjMzMjc3 | 8,197 | Remove deprecated arguments from new run_clm | {
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Fix a deprecated warning by replacing `tokenizer.max_len` with `tokenizer.model_max_length`.
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https://api.github.com/repos/huggingface/transformers/issues/8196 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8196/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8196/comments | https://api.github.com/repos/huggingface/transformers/issues/8196/events | https://github.com/huggingface/transformers/issues/8196 | 733,417,733 | MDU6SXNzdWU3MzM0MTc3MzM= | 8,196 | pytest Errors | {
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"I got the same error while loading BERT tokeniser and model from torch hub",
"Hello! Do you mind pasting the result of `pip list` done in your environment? Thank you!",
"It’s an Anaconda virtual environment.\nPython 3.6.11\n\n$ pip list\nPackage Version Location\n---------... | 1,604 | 1,604 | 1,604 | NONE | null | ## 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! -->
```
ai) ubuntu@ip-10-0-1-82:~/transformers$ transformers-cli env
/home/ubuntu/anaconda2/envs/ai/lib/python3.6/site-packages/tensorfl... | {
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https://api.github.com/repos/huggingface/transformers/issues/8195 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8195/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8195/comments | https://api.github.com/repos/huggingface/transformers/issues/8195/events | https://github.com/huggingface/transformers/pull/8195 | 733,411,226 | MDExOlB1bGxSZXF1ZXN0NTEzMTk3MTU3 | 8,195 | Attempt at a temporary fix on `model_max_length` for roberta and Camembert variants | {
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"No, `model_max_length` is not defined in the `tokenizer.json` for these models so truncation is off, or fails at inference in the model.",
"Well we also load the `transformers` specific configuration with `from_pretrained`, not only the `tokenizers` file (because We have additional attributes in `transformers`).... | 1,604 | 1,651 | 1,631 | CONTRIBUTOR | null | - The issue is that this information is not contained in the
`tokenizer` config file.
- It used to be harcoded already (with 512 value too).
- It is unclear right now how to "properly" fix it.
# What does this PR do?
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"I'm okay with this, but users will still need to copy paste or rewrite `Seq2SeqTrainingArguments` and pass those as `args` instead of default `TrainingArguments`, since we assume `args` is `Seq2SeqTrainingArguments` in multiple methods \r\n\r\n"
] | 1,604 | 1,604 | 1,604 | MEMBER | null | # What does this PR do?
Seq2SeqTrainer can be used as an independent file if no `label_smoothing` is done. This PR move the import to the init to make it possible to simple download this file and use it as it is without any dependencies for standard seq2seq training.
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https://api.github.com/repos/huggingface/transformers/issues/8193 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8193/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8193/comments | https://api.github.com/repos/huggingface/transformers/issues/8193/events | https://github.com/huggingface/transformers/pull/8193 | 733,381,683 | MDExOlB1bGxSZXF1ZXN0NTEzMTcxNTE5 | 8,193 | Fix two bugs with --logging_first_step | {
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"Thanks for your PR! For the first point, I think we should fix the docs, not add an evaluation. It doesn't make any sense to evaluate at step 1 (one could call `trainer.evaluate()` before training if they really wanted to).\r\nFor the second point, good catch, this is certainly useful!",
"OK, both the descriptio... | 1,604 | 1,604 | 1,604 | CONTRIBUTOR | null | # What does this PR do?
This PR fixes two bugs relating to the `--logging_first_step` flag:
1. Though the description for `--logging_first_step` says `"Log and eval the first global_step"`, the flag doesn't actually eval (it only logs). This PR makes sure that eval happens on the first step.
2. When `--logging_first... | {
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"There is no plan for that as both those APIs will be deprecated soon. Users should directly use the [Datasets](https://github.com/huggingface/datasets) library which works for both PyTorch and TF. There are examples of how to replicate `TextDataset` and `LineByLineTextDataset` using that library in the new [`run_c... | 1,604 | 1,609 | 1,609 | CONTRIBUTOR | null | Hey, guys. I find [`TextDataset`](https://github.com/huggingface/transformers/blob/9a21b50614991889f11dbe0743af25923765f9e9/src/transformers/data/datasets/language_modeling.py#L20) and `LineByLineTextDataset` is a great design, it help people build input data more faster. But it's a pity that it only support **pytorch*... | {
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https://api.github.com/repos/huggingface/transformers/issues/8189 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8189/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8189/comments | https://api.github.com/repos/huggingface/transformers/issues/8189/events | https://github.com/huggingface/transformers/pull/8189 | 733,290,389 | MDExOlB1bGxSZXF1ZXN0NTEzMDk1Nzcy | 8,189 | Doc fixes and filter warning in wandb | {
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There is no `XxxForPreTrainingModel`, just `XxxForPretraining`, so fixing the docs strings in multiple files.
Also, as discussed on the comet side, there should be no warning when the ENV says wandb should not be used.
| {
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https://api.github.com/repos/huggingface/transformers/issues/8188 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8188/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8188/comments | https://api.github.com/repos/huggingface/transformers/issues/8188/events | https://github.com/huggingface/transformers/pull/8188 | 733,275,906 | MDExOlB1bGxSZXF1ZXN0NTEzMDg0NDMx | 8,188 | Finalize lm examples | {
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This PR adds a `run_mlm_wwm` script for an example of MLM with whole word masking, which was the last kind of examples supporter by `run_language_modeling`.
As a result, it moves this script to `contrib/legacy/` and udpates the README to document how to use all the new example scripts.
... | {
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https://api.github.com/repos/huggingface/transformers/issues/8187 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8187/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8187/comments | https://api.github.com/repos/huggingface/transformers/issues/8187/events | https://github.com/huggingface/transformers/issues/8187 | 733,267,983 | MDU6SXNzdWU3MzMyNjc5ODM= | 8,187 | Configuration initialized from checkpoint does not keep the checkpoint identifier in its attributes | {
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"Good point.\r\n\r\nMaybe what we could do is:\r\n- initializing the configuration with `from_pretrained` initializes the `name_or_path` attribute of the config as you mention, and\r\n- using the configuration in a *model* `from_pretrained` method override the `name_or_path` attribute with the one of the model so t... | 1,604 | 1,610 | 1,610 | MEMBER | null | Since version v3.4.0, initializing a model using the `from_pretrained` method adds a `name_or_path` attribute to the configuration, referencing the checkpoint used for initialization:
```py
from transformers import BertModel
model = BertModel.from_pretrained(model_name)
print(model.config.name_or_path)
# model... | {
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https://api.github.com/repos/huggingface/transformers/issues/8186 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8186/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8186/comments | https://api.github.com/repos/huggingface/transformers/issues/8186/events | https://github.com/huggingface/transformers/issues/8186 | 733,264,586 | MDU6SXNzdWU3MzMyNjQ1ODY= | 8,186 | T5 (probably BART) issues with the `tf.saved_model.save` API and the `output_xxx` configuration attributes. | {
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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"
] | 1,604 | 1,610 | 1,610 | MEMBER | null | The TensorFlow implementation of the T5 (and very probably the BART) model has an issue with using the tf.saved_model.save API alongside the `output_attentions=True` and the `output_hidden_states=True` configuration attributes.
The tests are skipped currently due to this issue. | {
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https://api.github.com/repos/huggingface/transformers/issues/8185 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8185/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8185/comments | https://api.github.com/repos/huggingface/transformers/issues/8185/events | https://github.com/huggingface/transformers/issues/8185 | 733,262,213 | MDU6SXNzdWU3MzMyNjIyMTM= | 8,185 | TensorFlow Longformer model as a saved model with attention outputs | {
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"Don't manage to get this test passing even with the new design of #7562 -> the problem to me is that the shape of `attentions` in Longformer depends on the input tensor => so not sure we'll find a good solution here",
"If it can't pass the test defined in the common tests, then the best would be to override the ... | 1,604 | 1,610 | 1,610 | MEMBER | null | The TensorFlow implementation of the Longformer model has an issue with using the `tf.saved_model.save` API alongside the `output_attentions=True` configuration attribute.
The test is skipped currently due to this issue. | {
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https://api.github.com/repos/huggingface/transformers/issues/8184 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8184/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8184/comments | https://api.github.com/repos/huggingface/transformers/issues/8184/events | https://github.com/huggingface/transformers/issues/8184 | 733,208,390 | MDU6SXNzdWU3MzMyMDgzOTA= | 8,184 | trainer.evaluate returns 'epoch' from training | {
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"You can easily ignore that value though.\r\n\r\nThe problem is that you won't have it at each eval during the training loop if we don't include it. There could be something smarter there, but it would take time for something that is just purely cosmetic.",
"I added a small PR for improved documentation about th... | 1,604 | 1,605 | 1,605 | CONTRIBUTOR | null | I am training a BERT model: `trainer.train()`
Then I call `evaluate_result = trainer.evaluate(labeled_dataset_test)`
The value of `evaluate_result` looks like this:
```python
{'eval_loss': 0.5908029079437256,
'eval_acc': 0.8282828282828283,
'eval_bac': 0.8243021346469622,
'eval_mcc': 0.7422526698197041,... | {
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https://api.github.com/repos/huggingface/transformers/issues/8183 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8183/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8183/comments | https://api.github.com/repos/huggingface/transformers/issues/8183/events | https://github.com/huggingface/transformers/issues/8183 | 733,147,415 | MDU6SXNzdWU3MzMxNDc0MTU= | 8,183 | Summarization outputs on T5-small gets truncated | {
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"Hey @harung1993, \r\n\r\nsorry I'm having trouble understanding your question here. Also this seems like a question that should rather be posted in https://discuss.huggingface.co/ . We are trying to use github issues only for bug reports. Thanks!",
"This issue has been automatically marked as stale because it ha... | 1,604 | 1,610 | 1,610 | NONE | null | # ❓ 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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https://api.github.com/repos/huggingface/transformers/issues/8182 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8182/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8182/comments | https://api.github.com/repos/huggingface/transformers/issues/8182/events | https://github.com/huggingface/transformers/issues/8182 | 733,136,812 | MDU6SXNzdWU3MzMxMzY4MTI= | 8,182 | cannot load pytorch_model.bin / pytorch version ? | {
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"Hi! Could you provide the code you're using, as well as all the environment information?",
"@LysandreJik should we update the issue template for this last option `Questions & Help`?\r\n\r\nI feel like our first question to everybody is always `Could you provide the code you're using, as well as all the environme... | 1,604 | 1,610 | 1,610 | NONE | null | # ❓ 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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https://api.github.com/repos/huggingface/transformers/issues/8181 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8181/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8181/comments | https://api.github.com/repos/huggingface/transformers/issues/8181/events | https://github.com/huggingface/transformers/issues/8181 | 733,119,624 | MDU6SXNzdWU3MzMxMTk2MjQ= | 8,181 | Documentation on how to get results out of trainer is missing. | {
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"Hello! Indeed, do you want to open a PR to fix this? Thanks!",
"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"
] | 1,604 | 1,610 | 1,610 | CONTRIBUTOR | null | Hi,
some time ago it was possible to get the results out of the trainer by `trainer.log_history`.
This now changed to `trainer.state.log_history`. But everything is not documented. I suggest to add documentation on how to get results out of the trainer. | {
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https://api.github.com/repos/huggingface/transformers/issues/8180 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8180/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8180/comments | https://api.github.com/repos/huggingface/transformers/issues/8180/events | https://github.com/huggingface/transformers/pull/8180 | 733,095,406 | MDExOlB1bGxSZXF1ZXN0NTEyOTMwNDg2 | 8,180 | Fix the behaviour of DefaultArgumentHandler (removing it). | {
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"Sure before the change\r\n\r\n```python\r\nfrom transformers import pipeline\r\n\r\npipe = pipeline(task='fill-mask', model='bert-base-uncased')\r\npipe(\"I am a real [MASK]\", targets=[\"superhero\", \"legend\"])\r\n# [{'sequence': '[CLS] i am a real superhero [SEP]',\r\n# 'score': 1.21390044682812e-07,\r\n# 't... | 1,604 | 1,604 | 1,604 | CONTRIBUTOR | null | # What does this PR do?
This PR will attempt to fix some clearly wrong error message in what I think should be
valid calls.
The decision to remove `DefaultArgumentHandler` comes from the fact that the real usage actually lied for only QuestionAnswering and ZeroShot which already have their own handler.
Having... | {
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https://api.github.com/repos/huggingface/transformers/issues/8179 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8179/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8179/comments | https://api.github.com/repos/huggingface/transformers/issues/8179/events | https://github.com/huggingface/transformers/issues/8179 | 733,092,078 | MDU6SXNzdWU3MzMwOTIwNzg= | 8,179 | `do_predict` option of `TrainingArguments` - but no way to pass test set. | {
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"The `do_predict` argument (like `do-train` and `do-eval` is not used by `Trainer`), just by the training scripts provided as examples.\r\n\r\nGetting predictions on a test set is done with `trainer.predict(test_dataset)`.",
"Should corresponding documentation be added?",
"Sure, do you want to take a stab at it... | 1,604 | 1,605 | 1,605 | CONTRIBUTOR | null | The `TrainingArguments` class has the option to pass `do_predict=True`. The doc sais: "Whether to run predictions on the test set or not."
But there is no way to pass a test set to the trainer. At least I can not find it in the documentation...
Can you please clarify / fix this?
Many thanks
Philip | {
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"cc @LysandreJik @mfuntowicz ",
"Offline approval from @mfuntowicz!"
] | 1,604 | 1,604 | 1,604 | CONTRIBUTOR | null | 1. Use `@nn.compact` rather than `@compact` (as to not make it seem
like compact is a standard Python decorator.
2. Move attribute docstrings from two `__call__` methods to comments
on the attributes themselves. (This was probably a remnant from
the pre-Linen version where the attributes were arguments to
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https://api.github.com/repos/huggingface/transformers/issues/8177 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8177/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8177/comments | https://api.github.com/repos/huggingface/transformers/issues/8177/events | https://github.com/huggingface/transformers/issues/8177 | 733,026,147 | MDU6SXNzdWU3MzMwMjYxNDc= | 8,177 | AutoTokenizer.from_pretrained function cannot be customized | {
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"Hi! Could you provide an example of the usage that you would like to see with the `transformers` library, so that we may see what can be done?",
"Is this the same as #8125 ?",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occ... | 1,604 | 1,610 | 1,610 | NONE | null | A customized tokenizer has been provided in the tokenizer library, so that I can directly use the word segmentation data and vocab in the previous fairseq, but there is AutoTokenizer.from_pretrained function in the transformer, which cannot be customized like the tokenizer library, so I have no choice to directly use f... | {
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https://api.github.com/repos/huggingface/transformers/issues/8176 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8176/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8176/comments | https://api.github.com/repos/huggingface/transformers/issues/8176/events | https://github.com/huggingface/transformers/pull/8176 | 733,015,137 | MDExOlB1bGxSZXF1ZXN0NTEyODY0MzM2 | 8,176 | Fixing some warnings in DeBerta | {
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Just fixes some simple warning coming from python from incorrect escapes in docstrings + `collections.abc` import.
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https://api.github.com/repos/huggingface/transformers/issues/8175 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8175/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8175/comments | https://api.github.com/repos/huggingface/transformers/issues/8175/events | https://github.com/huggingface/transformers/issues/8175 | 733,001,646 | MDU6SXNzdWU3MzMwMDE2NDY= | 8,175 | Onnx converted model output shape not matching with the finetuned model (BUG) | {
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"It was working for me when using --pipeline sentiment-analysis",
"Hi @user06039 did you find a solution for this? Cause I am also facing the same issue."
] | 1,604 | 1,647 | 1,604 | NONE | null | I have trained a transformer 3 class classification model, the model used is distilbert-base-uncased.
Now, after training I tried to convert the model to onnx for faster inference using below script.
`
!python convert_graph_to_onnx.py --framework pt --model pt_line-distilbert --tokenizer distilbert-base-uncased ... | {
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https://api.github.com/repos/huggingface/transformers/issues/8174 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8174/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8174/comments | https://api.github.com/repos/huggingface/transformers/issues/8174/events | https://github.com/huggingface/transformers/issues/8174 | 732,972,745 | MDU6SXNzdWU3MzI5NzI3NDU= | 8,174 | Possible bug in "trainer" when training "BertForPretraining.from_pretrained()" | {
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"Hi Dana! I don't think this is a bug. You are not providing `BertForPreTraining` the `nsp_labels` it also requires for training, so it does not compute the loss (and then the rest fails). You should use `DataCollatorForNextSentencePrediction` to have the batches get those labels too (and it might requires using `T... | 1,604 | 1,604 | 1,604 | NONE | null | ## 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! -->
Environment is colab with GPU enabled. modules are provided in the Jupyter notebook on Google Drive here:
[https://colab.researc... | {
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https://api.github.com/repos/huggingface/transformers/issues/8173 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8173/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8173/comments | https://api.github.com/repos/huggingface/transformers/issues/8173/events | https://github.com/huggingface/transformers/issues/8173 | 732,948,955 | MDU6SXNzdWU3MzI5NDg5NTU= | 8,173 | raining loss is not decreasing when using the Roberta pre-trained model from the transformers library | {
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"Hello! Could you open a post on the [forum](https://discuss.huggingface.co) instead? We try to keep issues for bugs only.",
"Hi, sure."
] | 1,604 | 1,604 | 1,604 | NONE | null | I load the Roberta pre-trained model from the transformers library and use it for the sentence-pair classification task. The loss function used to decrease during the training per epoch until the last week, but now even though all of the parameters, including the batch size and the learning rate have the same value, wh... | {
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https://api.github.com/repos/huggingface/transformers/issues/8172 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8172/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8172/comments | https://api.github.com/repos/huggingface/transformers/issues/8172/events | https://github.com/huggingface/transformers/pull/8172 | 732,870,098 | MDExOlB1bGxSZXF1ZXN0NTEyNzQ3MzIx | 8,172 | Create Speedtest.py | {
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"Hello, could you provide more information on what this is? The template is empty, and I'm not sure what this brings to the library.",
"Don't spend time on this @LysandreJik this is just HacktoberFest spam"
] | 1,604 | 1,604 | 1,604 | NONE | null | # What does this PR do?
<!--
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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"Hello! Thanks for offering to contribute the TF implementation of the DPR model! Something that may help you is to open a PR very early on, even if you have a lot of questions. This way we can help provide pointers, and we can guide you in the right direction. \r\n\r\nAnother aspect that may be of tremendous help,... | 1,604 | 1,605 | 1,605 | CONTRIBUTOR | null | # 🌟 New model addition
## Model description
Hi, I would love to try contributing TFDPR . This is the first time to me, so I need some suggestions.
I have followed @sshleifer 's [great PR on TFBart model](https://github.com/huggingface/transformers/commit/829842159efeb1f920cbbb1daf5ad67e0114d0b9) on 4 files :` __i... | {
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https://api.github.com/repos/huggingface/transformers/issues/8167 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8167/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8167/comments | https://api.github.com/repos/huggingface/transformers/issues/8167/events | https://github.com/huggingface/transformers/pull/8167 | 732,828,961 | MDExOlB1bGxSZXF1ZXN0NTEyNzEzOTk1 | 8,167 | Create README.md | {
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"Thanks for sharing! You should add more metadata to your model card if possible: https://huggingface.co/docs#what-metadata-can-i-add-to-my-model-card"
] | 1,604 | 1,604 | 1,604 | CONTRIBUTOR | null | Telugu BERTU Readme file
# What does this PR do?
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"Thanks @TFUsers for this important PR.\r\n\r\nAs far as I know the activation names are also directly inside the the `config.json` files in the model hub. @sgugger @LysandreJik Do we plan to update all of them?",
"Very good point @jplu. We can't change those names in the config hosted online because it wouldn't... | 1,604 | 1,604 | 1,604 | CONTRIBUTOR | null | This pull request replaces the swish with the silu. Note "silu" still maps to tf.keras.activations.swish not tf.keras.activations.silu for tensorflow since the silu is in the tensorflow nightlies, but not in the stable version of tensorflow.
This fixes https://github.com/huggingface/transformers/issues/8100
@Lysa... | {
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"This issue has been automatically marked as stale and been closed because it has not had recent activity. Thank you for your contributions.\n\nIf you think this still needs to be addressed please comment on this thread."
] | 1,604 | 1,614 | 1,614 | CONTRIBUTOR | null | Optionally take randomness/sampling out of calculate_rouge_score.
Not breaking, the default is unchanged. | {
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"Thanks!",
"OK, everything seems to be working well. Let me know if you have any comments/suggestions/recommendations before replicating this to the rest of the jobs.\r\n\r\nSee: https://github.com/huggingface/transformers/runs/1329578690?check_suite_focus=true \r\n\r\nI will wait for https://github.com/huggingfa... | 1,604 | 1,604 | 1,604 | CONTRIBUTOR | null | As discussed at https://github.com/huggingface/transformers/pull/8110 this PR:
* [x] - generates 3 types of failure reports - long, short and one-per-line
* [x] - fixes multiple test suite tasks in a single job to allow them all to run regardless of the outcome of the previous test suites (using `if: always()`
* [... | {
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https://api.github.com/repos/huggingface/transformers/issues/8162 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8162/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8162/comments | https://api.github.com/repos/huggingface/transformers/issues/8162/events | https://github.com/huggingface/transformers/pull/8162 | 732,680,841 | MDExOlB1bGxSZXF1ZXN0NTEyNTg0NjMw | 8,162 | Fix typo: s/Chinees/Chinese/ | {
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"Oh, it was already fixed in #8159"
] | 1,604 | 1,604 | 1,604 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/8161 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8161/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8161/comments | https://api.github.com/repos/huggingface/transformers/issues/8161/events | https://github.com/huggingface/transformers/issues/8161 | 732,680,098 | MDU6SXNzdWU3MzI2ODAwOTg= | 8,161 | generate() always starts with bos_token_id | {
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"Hey @j-min, I don't think we will change this behavior because a) huge backward breaking change b) I think it's important to understand that generate **has** to start with a BOS/decoder_start_token_id (see Encoder-Decoder blog post: https://huggingface.co/blog/encoder-decoder)\r\n\r\nAlso you could add `skip_speci... | 1,604 | 1,604 | 1,604 | NONE | null | ## 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: 3.4.0
- Platform: Ubuntu 16.04
- Python version: 3.7
- PyTorch version (GPU?): 1.6 GPU
- Tensorflow ve... | {
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https://api.github.com/repos/huggingface/transformers/issues/8160 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8160/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8160/comments | https://api.github.com/repos/huggingface/transformers/issues/8160/events | https://github.com/huggingface/transformers/issues/8160 | 732,670,103 | MDU6SXNzdWU3MzI2NzAxMDM= | 8,160 | ConnectionError: ('Connection aborted.', OSError("(32, 'EPIPE')")) | {
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"cc @julien-c ",
"We've seen similar issues in the past @danyaljj. \r\n\r\nWe are going to release a new upload system for models in the coming week, can this wait till then? If it can't, and if you can upload your model to another bucket, we can copy it over manually. Let us know.",
"Hey, @julien-c 👋 Sounds ... | 1,604 | 1,605 | 1,605 | CONTRIBUTOR | null | Getting this error uploading a T5-3b model (~5 GB) to the model-hub.
I don't think it's my connection; I didn't have any issues with other smaller models, except this one.
Any thoughts on what could be the issue?
```
$ transformers-cli upload unifiedqa-t5-3b --organization allenai
About to upload file /Users... | {
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https://api.github.com/repos/huggingface/transformers/issues/8159 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8159/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8159/comments | https://api.github.com/repos/huggingface/transformers/issues/8159/events | https://github.com/huggingface/transformers/pull/8159 | 732,631,894 | MDExOlB1bGxSZXF1ZXN0NTEyNTQzMjY2 | 8,159 | Fix typo: indinces -> indices | {
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"> Looks good, thanks! Just make sure to run `make style` to have our scripts automatically fix the files you changed.\r\n\r\nOh. So should I send a new patch with the changes after running `make style`?",
"I'm not following. Your last commit had the styling changes so all is good.",
"> I'm not following. Your ... | 1,604 | 1,604 | 1,604 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/8158 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8158/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8158/comments | https://api.github.com/repos/huggingface/transformers/issues/8158/events | https://github.com/huggingface/transformers/issues/8158 | 732,563,139 | MDU6SXNzdWU3MzI1NjMxMzk= | 8,158 | EncoderDecoderModel: tie weights between different classes of models | {
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"Yeah I think you have a good point here! Was discussing this with @ibeltagy and I think we should add a `_tie_encoder_decoder_word_embeddings(...)` that does exactly what you suggested. We should probably run this method when initializing an Encoder-Decoder model and if word embeddings are of the same size. We ca... | 1,603 | 1,610 | 1,610 | NONE | null | # 🚀 Feature request
Tie weights between different classes of models, tie embedding matrices, update tutorial.
## Motivation
I have been following the Longformer2Roberta tutorial https://github.com/huggingface/transformers/blob/master/model_cards/patrickvonplaten/longformer2roberta-cnn_dailymail-fp16/README.md... | {
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https://api.github.com/repos/huggingface/transformers/issues/8157 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8157/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8157/comments | https://api.github.com/repos/huggingface/transformers/issues/8157/events | https://github.com/huggingface/transformers/pull/8157 | 732,535,199 | MDExOlB1bGxSZXF1ZXN0NTEyNDYwMzkz | 8,157 | [testing] distributed: correct subprocess output checking | {
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* the external subprocess runner will now be more flexible and check `stdout|stderr` to validate that the subprocess sent at least some output. Currently the code checks only `stdout` which isn't right since the subpr... | {
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https://api.github.com/repos/huggingface/transformers/issues/8156 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8156/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8156/comments | https://api.github.com/repos/huggingface/transformers/issues/8156/events | https://github.com/huggingface/transformers/issues/8156 | 732,526,024 | MDU6SXNzdWU3MzI1MjYwMjQ= | 8,156 | BertTokenizer loses unicode character | {
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"I'm having a similar problem since upgrading to 4.0 where certain unicode characters are being \"eaten\" even though I set 'use_fast' = False.\r\n\r\n## Environment info\r\n\r\n- `transformers` version: 4.0.0\r\n- Platform: macOS-10.16-x86_64-i386-64bit\r\n- Python version: 3.8.6\r\n- PyTorch version (GPU?): 1.7.0... | 1,603 | 1,614 | 1,614 | NONE | null | ## Environment info
- `transformers` version: 3.0.2
- Platform: Linux-4.15.0-109-generic-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.9
- PyTorch version (GPU?): 1.4.0 (True)
- Tensorflow version (GPU?): 2.3.0 (False)
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No
... | {
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https://api.github.com/repos/huggingface/transformers/issues/8155 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8155/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8155/comments | https://api.github.com/repos/huggingface/transformers/issues/8155/events | https://github.com/huggingface/transformers/issues/8155 | 732,491,539 | MDU6SXNzdWU3MzI0OTE1Mzk= | 8,155 | ONNX T5 with Beam Search | {
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"Hi @amanpreet692 ,\r\nI'm not sure what this error means, but I've `T5` `onnx` version ready which is compatible with `generate` method.\r\nTo be able to use cache I exported the `encoder` and `lm_head` to `onnx` and kept the `decoder` in `torch`. This is bit hacky but still gives 1.4-1.6x speed-up for beam search... | 1,603 | 1,610 | 1,610 | CONTRIBUTOR | null | Hey guys,
I didn't know where this belonged so opening up a generic issue.
I was working on integrating the ONNX T5 code by @abelriboulot with the HuggingFace Beam Search decoding code since I already had a decently performing T5 model for summarization and wanted to improve performance on CPU while maintaining the i... | {
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"I might be misreading progress bars. Running another test, will reopen if I can replicate. ",
"PTL (device 1) using less GPU ram it seems:\r\n\r\n\r\n\r\n\r\nProgress bars (note that PTL/Bottom is per epo... | 1,603 | 1,610 | 1,610 | CONTRIBUTOR | null | For the following two commands,
+ PTL finishes: 2.01 it/s, ~3H, 21.32 Rouge
+ Trainer: 1.0 it/s, roughly 5.5H, 21.36 Rouge
I wanted to report this so I don't lose track of it. Looked at the code, and don't see any obvious issue, besides that the slowdown is suspiciously close to 2x.
Any idea @patil-suraj ... | {
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https://api.github.com/repos/huggingface/transformers/issues/8153 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8153/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8153/comments | https://api.github.com/repos/huggingface/transformers/issues/8153/events | https://github.com/huggingface/transformers/pull/8153 | 732,407,932 | MDExOlB1bGxSZXF1ZXN0NTEyMzUyNzc5 | 8,153 | Add a template for examples and apply it for mlm and plm examples | {
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This PR adds a cookiecutter template to add a new example and experiments with it to add the run_mlm new script and a run_plm specific to XLNet. It runs with the same results as the old version.
Side note: the part for random masking applied in a data collator can become platform agnostic ... | {
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"❤️ "
] | 1,603 | 1,603 | 1,603 | COLLABORATOR | null | # What does this PR do?
Some random guy made a PR adding a `tokenizer_class` argument to `PretrainedConfig` but did not document it. This PR fixes that. | {
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This PR does two things:
- the first one is to replace `no-` to `no_` in the `HFArgumentParser` so that arguments get a more consistent name: for instance `use_tokenizer_fast` in the new examples script give an argument `no-use_tokenizer_fast` and the inconsistency between - and _ makes it h... | {
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https://api.github.com/repos/huggingface/transformers/issues/8149 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8149/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8149/comments | https://api.github.com/repos/huggingface/transformers/issues/8149/events | https://github.com/huggingface/transformers/pull/8149 | 732,284,137 | MDExOlB1bGxSZXF1ZXN0NTEyMjUwMDEx | 8,149 | Model card: Update widget examples. | {
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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"
] | 1,603 | 1,610 | 1,610 | NONE | null | In Keras when the embedding layers using masking it is propagate to layer afterwards like Pooling or RNN-Layers. I wonder if this holds for using transformers Bert Models? I.e. in the following are the attention masks used in the following Pooling as masking too? So, the averages do not include padding tokens?
... | {
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https://api.github.com/repos/huggingface/transformers/issues/8147 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8147/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8147/comments | https://api.github.com/repos/huggingface/transformers/issues/8147/events | https://github.com/huggingface/transformers/pull/8147 | 732,243,610 | MDExOlB1bGxSZXF1ZXN0NTEyMjE1ODQz | 8,147 | [Model cards] Seq2Seq tags | {
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"👍 "
] | 1,603 | 1,603 | 1,603 | MEMBER | null | # What does this PR do?
<!--
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/8146 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8146/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8146/comments | https://api.github.com/repos/huggingface/transformers/issues/8146/events | https://github.com/huggingface/transformers/issues/8146 | 732,204,689 | MDU6SXNzdWU3MzIyMDQ2ODk= | 8,146 | Make tokenizer.pad() also pad `labels` | {
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Make tokenizer.pad() also pad `labels`
## Motivation
I tried to use this:
https://github.com/huggingface/transformers/blob/8065fea87007fbf7542fc060ff8ddd0b5df567da/src/transformers/data/data_collator.py#L69
But since labels is not padded, the result cannot turn into a tensor. `ValueEr... | {
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https://api.github.com/repos/huggingface/transformers/issues/8145 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8145/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8145/comments | https://api.github.com/repos/huggingface/transformers/issues/8145/events | https://github.com/huggingface/transformers/issues/8145 | 732,151,447 | MDU6SXNzdWU3MzIxNTE0NDc= | 8,145 | TransformerXL: StopIteration: Caught StopIteration in replica 0 on device 0 | {
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"The same code I tested on GPT-2, works fine for me. Guess something wrong with transformer-xl\r\n\r\nGPT-2 code below:\r\n```Python\r\nimport torch\r\nfrom torch.nn import DataParallel\r\nfrom transformers import GPT2Tokenizer, GPT2LMHeadModel\r\n\r\ndevice = \"cuda:0\"\r\n\r\n# Get model\r\ntokenizer = GPT2Tokeni... | 1,603 | 1,605 | 1,605 | NONE | null | ## Environment info
- `transformers` version: 3.4.0
- Platform: Linux-3.10.0-957.el7.x86_64-x86_64-with-debian-stretch-sid
- Python version: 3.6.9
- PyTorch version (GPU?): 1.6.0 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: ... | {
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https://api.github.com/repos/huggingface/transformers/issues/8144 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8144/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8144/comments | https://api.github.com/repos/huggingface/transformers/issues/8144/events | https://github.com/huggingface/transformers/issues/8144 | 732,107,799 | MDU6SXNzdWU3MzIxMDc3OTk= | 8,144 | ETA on TFEncoderDecoderModel and is BERTShare from https://arxiv.org/pdf/1907.12461.pdf planned? | {
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"I think we can keep this open, this looks like a fun project. Pinging @patrickvonplaten to let him know!",
"The models of https://arxiv.org/pdf/1907.12461.pdf are already added. You can check them out here (they are not called shared, but are shared indeed): https://huggingface.co/models?search=google%2Froberta... | 1,603 | 1,610 | 1,610 | NONE | null | # 🚀 Feature request
Is there a plan for BERTShare from https://arxiv.org/pdf/1907.12461.pdf to be an option for the EncoderDecoderModel?
Also, I can see that an TFEncoderDecoderModel is on the 'ToDo' list for the [EncoderDecoder Framework](https://github.com/huggingface/transformers/projects/23). Any chance of a... | {
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https://api.github.com/repos/huggingface/transformers/issues/8143 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8143/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8143/comments | https://api.github.com/repos/huggingface/transformers/issues/8143/events | https://github.com/huggingface/transformers/issues/8143 | 732,083,397 | MDU6SXNzdWU3MzIwODMzOTc= | 8,143 | Trainer makes RAM go out of memory after a while | {
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"Additional info:\r\nas a workaround, I am now using a smaller validation set, but it is not ideal. If the memory issue can't be solved, a better solution could be to introduce an option to use a random subset of the validation set to use to evaluate during training.",
"If the problem is just that the RAM is not ... | 1,603 | 1,603 | 1,603 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 3.4.0
- Platform: Linux-4.14.193-113.317.amzn1.x86_64-x86_64-with-glibc2.9
- Python version: 3.6.10
- PyTorch version (GPU?): 1.6.0 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: True
- Using distributed or parallel set-up in script?: ... | {
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https://api.github.com/repos/huggingface/transformers/issues/8142 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8142/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8142/comments | https://api.github.com/repos/huggingface/transformers/issues/8142/events | https://github.com/huggingface/transformers/issues/8142 | 732,060,842 | MDU6SXNzdWU3MzIwNjA4NDI= | 8,142 | Is there any Jupyter notebook or detailed example using BertGeneration or EncoderDecoderModel classes? | {
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"Releasing in ~1 week - it's almost ready :-) ",
"Thanks for letting me know! :)",
"I've released two condensed notebooks as mentioned here: https://discuss.huggingface.co/t/leveraging-pre-trained-checkpoints-for-summarization/835/13?u=patrickvonplaten\r\n\r\nWill also release a longer educational blog post in ... | 1,603 | 1,604 | 1,604 | NONE | null | I have been looking to do some seq2seq tasks in the huggingface-transformers using BertGeneration or EncoderDecoderModel classes.
But I only have ended up finding some simple examples described in the API documentation like below.
```
>>> import torch
>>> tokenizer = BertTokenizer.from_pretrained('bert-base-u... | {
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https://api.github.com/repos/huggingface/transformers/issues/8141 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8141/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8141/comments | https://api.github.com/repos/huggingface/transformers/issues/8141/events | https://github.com/huggingface/transformers/issues/8141 | 732,034,100 | MDU6SXNzdWU3MzIwMzQxMDA= | 8,141 | Vocab files missing in community pre-trained t5 model | {
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"I'm guessing you can use the tokenizer from t5-base (https://huggingface.co/t5-base#list-files) but @sshleifer can confirm or infirm",
"> I'm guessing you can use the tokenizer from t5-base (https://huggingface.co/t5-base#list-files) but @sshleifer can confirm or infirm\r\n\r\nThis is what I used in the interim.... | 1,603 | 1,603 | 1,603 | NONE | null | ## 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: 3.4.0
- Platform: Linux-5.4.0-1028-gcp-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.9
- PyTorc... | {
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https://api.github.com/repos/huggingface/transformers/issues/8140 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8140/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8140/comments | https://api.github.com/repos/huggingface/transformers/issues/8140/events | https://github.com/huggingface/transformers/issues/8140 | 731,955,035 | MDU6SXNzdWU3MzE5NTUwMzU= | 8,140 | Customize tokenizer in model card's widget | {
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"I tried to use `BertModel` instead of `RobertaModel` (copy weights from Roberta to Bert). But the position embedding is different. And the outputs are different... So I have to use this combination of `RobertaModel` and `BertTokenizer`. Is that mean I can't use the inference widget?",
"Yes, this is possible. See... | 1,603 | 1,603 | 1,603 | CONTRIBUTOR | null | I trained a Chinese Roberta model. In the model card, the widget uses a tokenizer defined in config.json(`RobertaTokenizer`). But my model uses `BertTokenizer`. Can I customize the tokenizer in the widget of the model card just like I can choose any combination of model and tokenizer in a pipeline? | {
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https://api.github.com/repos/huggingface/transformers/issues/8139 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8139/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8139/comments | https://api.github.com/repos/huggingface/transformers/issues/8139/events | https://github.com/huggingface/transformers/pull/8139 | 731,936,337 | MDExOlB1bGxSZXF1ZXN0NTExOTYxNDg5 | 8,139 | Fix doc errors and typos across the board | {
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https://api.github.com/repos/huggingface/transformers/issues/8138 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8138/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8138/comments | https://api.github.com/repos/huggingface/transformers/issues/8138/events | https://github.com/huggingface/transformers/issues/8138 | 731,927,505 | MDU6SXNzdWU3MzE5Mjc1MDU= | 8,138 | How to get translation of one batch of sentences after batch_encode_plus? | {
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"Hello, have you read the docs concerning the translation task? It is [available here](https://huggingface.co/transformers/task_summary.html#translation).\r\n\r\nSince you're specifically asking about a Helsinki model, you can find the documentation, with examples, [here](https://huggingface.co/transformers/model_d... | 1,603 | 1,604 | 1,604 | NONE | null | ```
model = AutoModelWithLMHead.from_pretrained("Helsinki-NLP/opus-mt-es-en")
tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-es-en")
batch_input_str = (("Mary spends $20 on pizza"), ("She likes eating it"), ("The pizza was great"))
encoded = (tokenizer.batch_encode_plus(batch_input_str, pad_to_max_... | {
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https://api.github.com/repos/huggingface/transformers/issues/8137 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8137/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8137/comments | https://api.github.com/repos/huggingface/transformers/issues/8137/events | https://github.com/huggingface/transformers/issues/8137 | 731,914,635 | MDU6SXNzdWU3MzE5MTQ2MzU= | 8,137 | In built code not able to download for "bert-base-uncased" when running on cluster. | {
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"It seems that you have no internet access",
"Thank You. We also came to know that the cluster doesn't have internet access. I can manually download it and put that in a cache folder, if that is possible, can you please suggest where we can put this in a cache folder so that it could access from that place.",
"... | 1,603 | 1,610 | 1,610 | NONE | null | Traceback (most recent call last):
File "/users/sroychou/BERT_text_summarisation/scripts/train_bert_summarizer.py", line 12, in <module>
from metrics import optimizer, loss_function, label_smoothing, get_loss_and_accuracy, tf_write_summary, monitor_run
File "/users/sroychou/BERT_text_summarisation/scripts/me... | {
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"Hi, this [Kaggle notebook](https://www.kaggle.com/xhlulu/jigsaw-tpu-xlm-roberta) shows a very concise way to efficiently train/predict Huggingface's `XLMRoberta` (which is the same format as `Roberta`) . Hope it help!",
"This issue has been automatically marked as stale because it has not had recent activity. It... | 1,603 | 1,610 | 1,610 | NONE | null | I'd like to perform inference loop for the following roberta model:
```
model = TFRobertaForSequenceClassification.from_pretrained('roberta-base',return_dict=True,num_labels=2)
```
on a large set of pairs of sentences (couple of hundred thousands). I wanted to use `model.predict` and specify batch size, but the... | {
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https://api.github.com/repos/huggingface/transformers/issues/8135 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8135/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8135/comments | https://api.github.com/repos/huggingface/transformers/issues/8135/events | https://github.com/huggingface/transformers/issues/8135 | 731,799,559 | MDU6SXNzdWU3MzE3OTk1NTk= | 8,135 | Bort (Amazon's reduced BERT) | {
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"Any update on this one?",
"This was added in #9112"
] | 1,603 | 1,631 | 1,631 | NONE | null | # 🌟 New model addition
## Model description
Amazon Alexa researchers extract an optimal subset of architectural parameters for the BERT architecture by applying recent breakthroughs in algorithms for neural architecture search. The proposed optimal subset, “Bort,” is just 5.5 percent the effective size of the or... | {
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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",
"@nrjvarshney Hello did you managed this error? I am too having same error. Is there anybody to help?",
"Hello did you managed this er... | 1,603 | 1,655 | 1,610 | NONE | null | I'm trying to build a QuestionAnswering model using transformers
It works with single gpu training but fails with multiple gpus.
Is there any bug in the below code?
```
class QAModel(pl.LightningModule):
def __init__(self):
super(QAModel, self).__init__()
self.model_type = para... | {
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https://api.github.com/repos/huggingface/transformers/issues/8133 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8133/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8133/comments | https://api.github.com/repos/huggingface/transformers/issues/8133/events | https://github.com/huggingface/transformers/pull/8133 | 731,759,594 | MDExOlB1bGxSZXF1ZXN0NTExODExODM4 | 8,133 | [examples] minimal version requirement run-time check in PL | {
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In the nature of development we don't constantly re-run `pip install -r requirements.txt` so often when a breaking change is introduced we have to... | {
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This PR adds a cookiecutter template to add a new example and experiments with it to add the `run_mlm` new script. It runs with the same results as the old version. I'll also add a `run_plm` specific to XLNet then update the README and remove the old script.
Side note: the part for random ... | {
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@sshleifer | {
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Currently a configuration initialized with
```
config = BertConfig.from_pretrained(model_name)
```
does not have the `_model_name_or_path` attribute, whereas a configuration intialized from a model with
```py
model = BertModel.from_pretrained(mode... | {
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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"
] | 1,603 | 1,610 | 1,610 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
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https://api.github.com/repos/huggingface/transformers/issues/8125 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8125/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8125/comments | https://api.github.com/repos/huggingface/transformers/issues/8125/events | https://github.com/huggingface/transformers/issues/8125 | 731,669,109 | MDU6SXNzdWU3MzE2NjkxMDk= | 8,125 | Cannot load saved tokenizer using AutoTokenizer | {
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"Hello! Indeed, I wouldn't say this is a bug but more of a limitation of the `AutoTokenizer` class that has to rely on the model configuration in order to guess which tokenizer is affiliated with the model. Since you're not interacting with the configuration in the configuration anywhere here, and, therefore, are n... | 1,603 | 1,610 | 1,610 | NONE | null | ## 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: 3.4.0
- Platform: Win10 x64 (1607 Build 14393.3866)
- Python version: 3.6.10
- PyTorch version (GPU?): ... | {
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https://api.github.com/repos/huggingface/transformers/issues/8124 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8124/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8124/comments | https://api.github.com/repos/huggingface/transformers/issues/8124/events | https://github.com/huggingface/transformers/issues/8124 | 731,608,316 | MDU6SXNzdWU3MzE2MDgzMTY= | 8,124 | [s2s] distributed eval gets stuck on error w/ multigpu | {
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"same happens with `finetune.py` - happened in another run when it hit OOM. So basically any error.",
"@williamFalcon @SeanNaren (lightning friends)\r\n\r\nDo you guys have a clever way to collect failures in your multigpu tests?\r\nWhen something breaks, our multigpu test hangs.\r\n",
"yes... good questions ha... | 1,603 | 1,610 | 1,610 | CONTRIBUTOR | null | `examples/seq2seq/distillation.py` and probably others remain hanging on internal error when run w/ multiple gpus (2 here):
```
rm -r /tmp/tmpqajqhzwo; PYTHONPATH="src" python examples/seq2seq/distillation.py --supervise_forward --normalize_hidden --label_smoothing=0.0 --eval_beams=1 --val_metric=loss --save_top_k=... | {
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https://api.github.com/repos/huggingface/transformers/issues/8123 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8123/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8123/comments | https://api.github.com/repos/huggingface/transformers/issues/8123/events | https://github.com/huggingface/transformers/pull/8123 | 731,602,423 | MDExOlB1bGxSZXF1ZXN0NTExNjgwMjc0 | 8,123 | [DOC] Improve pipeline() docstrings for config and tokenizer | {
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"@sgugger I made the change as you requested. Not sure why CI is failing on build_doc. Seems to have to do with some env installation.",
"The failure is spurious (basically the new version of pytorch is not cached on the CI and it fails to download it sometimes). Thanks for th fix!"
] | 1,603 | 1,603 | 1,603 | COLLABORATOR | null | As currently written, it was not clear to me which arguments were needed when using a non-default model in `pipeline()`. It seemed that when you provided a non-default `model`, that you still needed to manually change the `config` and `tokenizer` because otherwise the "task's default will be used". In practice, though,... | {
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https://api.github.com/repos/huggingface/transformers/issues/8122 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/8122/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/8122/comments | https://api.github.com/repos/huggingface/transformers/issues/8122/events | https://github.com/huggingface/transformers/issues/8122 | 731,597,805 | MDU6SXNzdWU3MzE1OTc4MDU= | 8,122 | behaviour of ZeroShotClassification using facebook/bart-large-mnli is different on online demo vs local machine | {
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"Replace `AutoModel` with `AutoModelForSequenceClassification`. The former won't add the sequence classification head, i.e. it will use `BartModel` instead of `BartForSequenceClassification`, so the pipeline is trying to use just the outputs of the encoder instead of the NLI predictions in your snippet.",
"@joedd... | 1,603 | 1,603 | 1,603 | NONE | null | ## Environment info
- `transformers` version: 3.4.0
- Platform: Ubuntu 20.04
- Python version: 3.7.7
- PyTorch version (GPU?): 1.6.0 (GPU:Yes)
- Tensorflow version (GPU?): No
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: No
### Who can help
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