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https://api.github.com/repos/huggingface/transformers/issues/3512 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3512/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3512/comments | https://api.github.com/repos/huggingface/transformers/issues/3512/events | https://github.com/huggingface/transformers/issues/3512 | 589,768,101 | MDU6SXNzdWU1ODk3NjgxMDE= | 3,512 | how to get activation weights of a pretrained 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"
] | 1,585 | 1,591 | 1,591 | CONTRIBUTOR | 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 Stack Overflow (SO) where a whole community of PyTorch and
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3511?src=pr&el=h1) Report\n> Merging [#3511](https://codecov.io/gh/huggingface/transformers/pull/3511?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/601ac5b1dc1438f00d09696588f2deb0f045ae3b&el=desc) will **increase... | 1,585 | 1,589 | 1,585 | CONTRIBUTOR | null | PR to remove the softmax and make the pad token label id to -1. | {
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https://api.github.com/repos/huggingface/transformers/issues/3510 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3510/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3510/comments | https://api.github.com/repos/huggingface/transformers/issues/3510/events | https://github.com/huggingface/transformers/issues/3510 | 589,757,840 | MDU6SXNzdWU1ODk3NTc4NDA= | 3,510 | reproducing the performance of XLM-ROBERTA on MLQA dataset on the zh language | {
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"Credit to people at Microsoft Asia: Ning Wu and Nan Dua\r\nTo achieve the best performance on the \"zh\" test sets, you just need to add \r\n\"final_text = tok_text\" after line 497 in squad_metrics.py (only for zh). Because there isn't space and subword in Chinese, so we don't need to execute the get_final_test()... | 1,585 | 1,661 | 1,586 | NONE | null | # ❓ Questions & Help
## Details
<!-- Description of your issue -->
I have trouble in reproducing the result of XLM-ROBERTA on MLQA dataset for Chinese languages. The result of the rest of the language seems fine, however on the zh section, I have very low {'exact_match': 4.263188631496982, 'f1': 17.45105917846194... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3509?src=pr&el=h1) Report\n> Merging [#3509](https://codecov.io/gh/huggingface/transformers/pull/3509?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/601ac5b1dc1438f00d09696588f2deb0f045ae3b&el=desc) will **not chan... | 1,585 | 1,585 | 1,585 | CONTRIBUTOR | null | If `args.should_continue` is true, then there is no way in the current example to reload a checkpoint since it is assumed it exists within the output_dir. Checking here fixes everything as expected. | {
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https://api.github.com/repos/huggingface/transformers/issues/3508 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3508/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3508/comments | https://api.github.com/repos/huggingface/transformers/issues/3508/events | https://github.com/huggingface/transformers/issues/3508 | 589,731,690 | MDU6SXNzdWU1ODk3MzE2OTA= | 3,508 | [Bart] when output_paste=False BartForConditionalGeneration raises confusing error | {
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"@sshleifer I'm seeing this as well. It doesn't happen if `num_beams=1`. Might have to do with the recent generation and bart changes. Only started happening in the last week or so. ",
"Thanks for contributing!\r\n\r\nA few thoughts:\r\n\r\n1. if you pass `output_past=True` to `BartForConditionalGeneration.from_p... | 1,585 | 1,613 | 1,586 | NONE | null | # 🐛 Bug
## Information
i am using BART
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [x ] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
The tasks I am working on is:
* [ ] an official GLUE/SQU... | {
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- Add detailed description on how to process input and target for T5 training | {
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https://api.github.com/repos/huggingface/transformers/issues/3506 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3506/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3506/comments | https://api.github.com/repos/huggingface/transformers/issues/3506/events | https://github.com/huggingface/transformers/issues/3506 | 589,696,985 | MDU6SXNzdWU1ODk2OTY5ODU= | 3,506 | No grad feature in model parameters | {
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"This is more of a general PyTorch question than a Transformers-question. Have you tried asking on StackOverflow or the PyTorch forums?"
] | 1,585 | 1,585 | 1,585 | 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 Stack Overflow (SO) where a whole community of PyTorch and
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3504?src=pr&el=h1) Report\n> Merging [#3504](https://codecov.io/gh/huggingface/transformers/pull/3504?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/601ac5b1dc1438f00d09696588f2deb0f045ae3b&el=desc) will **decrease... | 1,585 | 1,585 | 1,585 | MEMBER | null | Update `model.generate()` docs | {
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"Interesting idea! What do you think @thomwolf ?",
"Hi, any update on this, even partial code?",
"I'm gunna take a crack this weekend, hopefully, By starting from the [distilbert example](https://github.com/huggingface/transformers/tree/master/examples/distillation) and modifying. I'll post a branch if I make ... | 1,585 | 1,593 | 1,593 | NONE | null | {
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https://api.github.com/repos/huggingface/transformers/issues/3502 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3502/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3502/comments | https://api.github.com/repos/huggingface/transformers/issues/3502/events | https://github.com/huggingface/transformers/issues/3502 | 589,622,307 | MDU6SXNzdWU1ODk2MjIzMDc= | 3,502 | Bert Batch Encode Plus adding an extra [SEP] | {
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"Hi @creat89, \r\n\r\nThanks for posting this issue! \r\n\r\nYou are correct there is some inconsistent behavior here. \r\n\r\n1. We should probably in general not allow using `batch_encode_plus()` of a simple string. For this the `encode_plus()` function should be used. \r\n2. It seems like there is an inconsiste... | 1,585 | 1,586 | 1,586 | NONE | null | # 🐛 Bug
## Information
I'm using `bert-base-multilingual-cased` tokenizer and model for creating another model. However, the `batch_encode_plus` is adding an extra `[SEP]` token id in the middle.
The problem arises when using:
* Specific strings to encode, e.g. `16.`, `3.`, `10.`,
* The `bert-base-multiling... | {
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https://api.github.com/repos/huggingface/transformers/issues/3501 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3501/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3501/comments | https://api.github.com/repos/huggingface/transformers/issues/3501/events | https://github.com/huggingface/transformers/pull/3501 | 589,610,966 | MDExOlB1bGxSZXF1ZXN0Mzk1MTE5NDYx | 3,501 | [BART] Update encoder and decoder on set_input_embedding | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3501?src=pr&el=h1) Report\n> Merging [#3501](https://codecov.io/gh/huggingface/transformers/pull/3501?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/601ac5b1dc1438f00d09696588f2deb0f045ae3b&el=desc) will **increase... | 1,585 | 1,585 | 1,585 | CONTRIBUTOR | null | Since _resize_token_embeddings will create a new embedding layer,
resizing the input embeddings for BART will currently break, as the
model.shared will refer to the new embedding created but the
model.encoder.embed_tokens and the model.decoder.embed_tokens will
still refer to the old embedding created.
We need ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3500 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3500/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3500/comments | https://api.github.com/repos/huggingface/transformers/issues/3500/events | https://github.com/huggingface/transformers/pull/3500 | 589,603,851 | MDExOlB1bGxSZXF1ZXN0Mzk1MTE0OTAz | 3,500 | [Wait to merge] [Bart] Rename lm_labels argument to masked_lm_labels | {
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"Could you make sure the kwarg in `examples/summarization/bart/run_bart_sum.py` is correct? Thanks!",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3500?src=pr&el=h1) Report\n> Merging [#3500](https://codecov.io/gh/huggingface/transformers/pull/3500?src=pr&el=desc) into [master](https://codecov... | 1,585 | 1,593 | 1,593 | CONTRIBUTOR | null | While the docstring correctly lists masked_lm_labels, forward
was expecting lm_labels. Renaming to match BERT and the rest of
the MLM-based models
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https://api.github.com/repos/huggingface/transformers/issues/3499 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3499/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3499/comments | https://api.github.com/repos/huggingface/transformers/issues/3499/events | https://github.com/huggingface/transformers/issues/3499 | 589,597,058 | MDU6SXNzdWU1ODk1OTcwNTg= | 3,499 | masked_lm_loss in BertForMaskedLM model | {
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"Have a look at the `mask_tokens` method in `run_language_modeling.py`. This takes in the `input_ids`, performs masking on them and returns the masked `input_ids` and corresponding `masked_lm_labels`.",
"@Drpulti I am also getting the same error as you, and I believe it is because `-100` exists in the `masked_lm_... | 1,585 | 1,585 | 1,585 | NONE | null | Altought I've read the documentation related to BertForMaskedLM class, I still cannot understand how to properly calculate loss for my problem.
Let's suppose that my target sentence is:
"_I will be writing when you arrive._"
I want to calculate loss for all words except 'arrive'.
The documentation says:
> **ma... | {
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https://api.github.com/repos/huggingface/transformers/issues/3498 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3498/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3498/comments | https://api.github.com/repos/huggingface/transformers/issues/3498/events | https://github.com/huggingface/transformers/issues/3498 | 589,593,554 | MDU6SXNzdWU1ODk1OTM1NTQ= | 3,498 | XLM-ROBERTA | {
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"That's a good point @nooralahzadeh! We should probably add the `model_type` field to the XLM-ROBERTA config. \r\n\r\n@julien-c - If it's fine for you I can add the `model_type` `xlm-roberta` to all `xlm-roberta` configs of the following models: \r\nhttps://huggingface.co/models?search=xlm-rob \r\n\r\nAs @nooralahz... | 1,585 | 1,643 | 1,585 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): XLM-ROBERTA
In order to fine-tune XLM-ROBERTA from pre_trained file, since the config file does not have the model_type field, all the required files should be in a folder which contains "xlm-robert" in its name! otherwise the "XLM" config will be as... | {
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https://api.github.com/repos/huggingface/transformers/issues/3497 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3497/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3497/comments | https://api.github.com/repos/huggingface/transformers/issues/3497/events | https://github.com/huggingface/transformers/issues/3497 | 589,552,346 | MDU6SXNzdWU1ODk1NTIzNDY= | 3,497 | REALM | {
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"Code is released for the preceding paper: Latent Retrieval for Weakly Supervised Open Domain Question Answering\" https://www.aclweb.org/anthology/P19-1612/\r\nhttps://github.com/google-research/language/tree/master/language/orqa",
"This issue has been automatically marked as stale because it has not had recent ... | 1,585 | 1,642 | 1,642 | NONE | null | # 🌟 New model addition
REALM is from some of the authors of BERT (I like to think of it as the next BERT :) ) that have found a way to incorporate world knowledge (from Wikipedia) into the model.
They do this by having the concept of a retriever module that retrieves information from wikipedia articles.
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https://api.github.com/repos/huggingface/transformers/issues/3496 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3496/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3496/comments | https://api.github.com/repos/huggingface/transformers/issues/3496/events | https://github.com/huggingface/transformers/issues/3496 | 589,510,716 | MDU6SXNzdWU1ODk1MTA3MTY= | 3,496 | How to load BertforSequenceClassification models weights into BertforTokenClassification model? | {
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"Have you tried loading your checkpoint in the model using `from_pretrained`:\r\n\r\n```py\r\nmodel = BertForTokenClassification.from_pretrained(\"checkpoint)\r\n```\r\n\r\n? It should work out of the box. Please be aware that the NER head will be randomly initialized as it is not in the sequence classification che... | 1,585 | 1,591 | 1,591 | NONE | null | Initially, I have a fine-tuned BERT base cased model using a text classification dataset and I have used BertforSequenceClassification class for this. Now I want to use this fine-tuned BERT model weights for Named Entity Recognition and I have to use BertforTokenClassification class for this. I'm unable to figure out h... | {
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"I have encountered the same error running the LM finetuning script on Google Colab, also with the Bert model type but using the pretrained weights from 'allenai/scibert_scivocab_uncased'\r\n\r\n```\r\n!python run_language_modeling.py \\\r\n --output_dir=models \\\r\n --model_type=bert \\\r\n --model_name_... | 1,585 | 1,635 | 1,592 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Bert
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
The tasks I am working on is:
* ... | {
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## Information
Model I am using (Bert, XLNet ...): XLM-R
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
The tasks I am working on is:
*... | {
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"You can use `run_language_modeling.py` for this purpose. Just set `--model_type` to `gpt2`, set `--model_name_or_path` to the gpt2 model checkpoint you want (`gpt2`) and set `--train_data_file` to your dataset and you should be ready to go.",
"Thanks! The issue is that I want to use the pre-trained version of GP... | 1,585 | 1,592 | 1,592 | NONE | null | It looks like there used to be a script `run_lm_finetuning.py` that has been replaced by `run_language_modeling.py`. It's unclear to me how to use this script to run finetuning. I want to finetune GPT-2 on a variety of downstream tasks, and would love some help! | {
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https://api.github.com/repos/huggingface/transformers/issues/3492 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3492/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3492/comments | https://api.github.com/repos/huggingface/transformers/issues/3492/events | https://github.com/huggingface/transformers/pull/3492 | 589,411,064 | MDExOlB1bGxSZXF1ZXN0Mzk0OTY4MDEz | 3,492 | [model_cards]: use MIT license for all dbmdz models | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3492?src=pr&el=h1) Report\n> Merging [#3492](https://codecov.io/gh/huggingface/transformers/pull/3492?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/17dceae7a1de5577cd0c07a97dcd5821a08af07c&el=desc) will **decrease... | 1,585 | 1,601 | 1,585 | COLLABORATOR | null | Hi,
this PR adds MIT license tag for all dbmdz models 🤗 | {
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https://api.github.com/repos/huggingface/transformers/issues/3491 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3491/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3491/comments | https://api.github.com/repos/huggingface/transformers/issues/3491/events | https://github.com/huggingface/transformers/pull/3491 | 589,373,752 | MDExOlB1bGxSZXF1ZXN0Mzk0OTM3Mjg1 | 3,491 | cased -> uncased for example cmdline consistency | {
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"In the same file, there is also `--do_lower_case` wrongly apply to `roberta-base` and `xlnet-large-cased` model. It will be great if this PR also includes that fix.",
"> In the same file, there is also `--do_lower_case` wrongly apply to `roberta-base` and `xlnet-large-cased` model. It will be great if this PR al... | 1,585 | 1,586 | 1,586 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/3490 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3490/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3490/comments | https://api.github.com/repos/huggingface/transformers/issues/3490/events | https://github.com/huggingface/transformers/issues/3490 | 589,360,195 | MDU6SXNzdWU1ODkzNjAxOTU= | 3,490 | which iterator to use for different hugging face transformer models for solving multiple choice questions? | {
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"Do I need to build my own iterator for this?\r\nHow should the tokens be arranged for multiple choice question solving?\r\n\r\ne.g. (question) (token1) (token2) (MCoption)(answer1)\r\n. ----> is this the right format for all of the GPT-2, BERT and XLNet? \r\n\r\nThank you",
"This issue has been automatically mar... | 1,585 | 1,591 | 1,591 | NONE | null | Hello,
I have used Hugging Face GPT-2 models to do Natural Language Processing.
When I used the GPT-2 model, I used the ```BPTTIterator``` from TorchText to pre-process my text data, since GPT-2 essentially performs regular language modelling (next token prediction).
I am wondering, when I use GPT-2, BERT and XL... | {
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https://api.github.com/repos/huggingface/transformers/issues/3489 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3489/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3489/comments | https://api.github.com/repos/huggingface/transformers/issues/3489/events | https://github.com/huggingface/transformers/issues/3489 | 589,335,968 | MDU6SXNzdWU1ODkzMzU5Njg= | 3,489 | missing import in BartForConditionalGeneration example | {
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"Please complete the issue template, I don't understand what the issue is.",
"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"
] | 1,585 | 1,591 | 1,591 | NONE | null | Add
`from transformers import AutoTokenizer, AutoModelWithLMHead`
to Bart for Conditional Generation example in
# 🐛 Bug
## Information
Model I am using (Bert, XLNet ...):
Language I am using the model on (English, Chinese ...):
The problem arises when using:
* [ ] the official example scripts: ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3488 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3488/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3488/comments | https://api.github.com/repos/huggingface/transformers/issues/3488/events | https://github.com/huggingface/transformers/pull/3488 | 589,285,805 | MDExOlB1bGxSZXF1ZXN0Mzk0ODc4ODMx | 3,488 | [bart-tiny-random] Put a 5MB model on S3 to allow faster examples test | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3488?src=pr&el=h1) Report\n> Merging [#3488](https://codecov.io/gh/huggingface/transformers/pull/3488?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/17dceae7a1de5577cd0c07a97dcd5821a08af07c&el=desc) will **decrease... | 1,585 | 1,585 | 1,585 | CONTRIBUTOR | null | - Vocab size is the same to avoid requiring a new tokenizer.
- this allows examples that parametrize `model_name`, like `evaluate_cnn.py`, to run much quicker: `summarization/bart/test_bart_examples.py` runs in 6 seconds vs 22 + download time previously.
- Would be happy to do this for more models.
- Will update `ru... | {
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https://api.github.com/repos/huggingface/transformers/issues/3487 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3487/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3487/comments | https://api.github.com/repos/huggingface/transformers/issues/3487/events | https://github.com/huggingface/transformers/pull/3487 | 589,255,391 | MDExOlB1bGxSZXF1ZXN0Mzk0ODU0Mzk1 | 3,487 | Create model card | {
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"@julien-c Do you know why does it fail?"
] | 1,585 | 1,585 | 1,585 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/3486 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3486/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3486/comments | https://api.github.com/repos/huggingface/transformers/issues/3486/events | https://github.com/huggingface/transformers/issues/3486 | 589,255,313 | MDU6SXNzdWU1ODkyNTUzMTM= | 3,486 | setup.py succeeds, then can't import transformers | {
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"Do you use the `zsh` shell? cause in this case I think you have to do `pip install -e \".\"`\r\n\r\nI think this has something to do with the shells. Can you compare `zsh` to pure `bash` shell?",
"Fails in bash identically.\r\nOne clue, this is also happening for `pip install tokenizers` followed by import `toke... | 1,585 | 1,585 | 1,585 | CONTRIBUTOR | null | ```bash
pip install -e .
```
works succesfully and makes `transformers.egg-info/`
Then,
```python
import transformers
```
fails with
```
ModuleNotFoundError: No module named 'transformers'
```
env
```
- `transformers` version: 2.6.0
- Platform: Darwin-19.0.0-x86_64-i386-64bit
- Python version: 3... | {
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https://api.github.com/repos/huggingface/transformers/issues/3485 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3485/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3485/comments | https://api.github.com/repos/huggingface/transformers/issues/3485/events | https://github.com/huggingface/transformers/pull/3485 | 589,211,407 | MDExOlB1bGxSZXF1ZXN0Mzk0ODE4Mjk2 | 3,485 | Fix circle ci flaky fail of wmt example | {
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"This is from this right? https://circleci.com/gh/huggingface/transformers/26455?utm_campaign=workflow-failed&utm_medium=email&utm_source=notification",
"Yeah exactly - it should be fixed now. \r\nI will push a slightly cleaner version in a second :-) ",
"In general, every example test that creates folder or fi... | 1,585 | 1,585 | 1,585 | MEMBER | null | Weird bug which might be fixed by forcing bleu scorer.
Test pass locally, but seem to fail on circle ci. | {
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"This seems to be similar to [Issue #3466](https://github.com/huggingface/transformers/issues/3466)",
"Hi, this issue was solved with https://github.com/huggingface/transformers/commit/e2c05f06ef58ea77103d2c64492dd8d9a0b21c3f\r\n\r\nCould you try to pull the repository once again and try then?",
"Yes, that seem... | 1,585 | 1,585 | 1,585 | NONE | null | ## Information
I am trying to build the documentation in `docs/` using `sphinx-build` so that I can add it to [Dash](https://kapeli.com/dash) as one of the docsets. However, I get an assertion error with sphinx-build when I run `make html` in the `docs/` folder *only when tensorflow is installed*. The build works wi... | {
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"I agree. Tried for an hour last night to add coverage for `run_bart_sum.py` and got stuck on two things.\r\n\r\n1) A `circleci` job that installs `pytorch_lightning` (and potentially other dependencies)\r\n2) the ability to import `examples/transformer_base.py`\r\n\r\n### Suggested Approach:\r\n- add the aforement... | 1,585 | 1,591 | 1,591 | CONTRIBUTOR | null |
# Add tests for more of the examples/
We need to have more testing code for examples. This is particularly true with NER which recently had a tokenizer issue.
(Self-assigning) | {
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"I believe that the `collate` function should take care of it. However, you will need to create the `attention_mask` variable when you have inputs of variable length, so that the model does not attend to the padded indices.",
"@Genius1237 I'm a real noob (I come from a programming background and no ML), but I'm u... | 1,585 | 1,593 | 1,591 | NONE | null | I use a custom TextDataset in [examples/run_language_modeling.py](https://github.com/huggingface/transformers/blob/master/examples/run_language_modeling.py). I can't figure if I need to pad the examples to `bucket_size` myself, or is it already been taken care of in [L221-L223](https://github.com/huggingface/transforme... | {
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https://api.github.com/repos/huggingface/transformers/issues/3480 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3480/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3480/comments | https://api.github.com/repos/huggingface/transformers/issues/3480/events | https://github.com/huggingface/transformers/pull/3480 | 589,175,966 | MDExOlB1bGxSZXF1ZXN0Mzk0Nzg4ODAx | 3,480 | Add option to choose T5 model size. | {
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This PR gives the option to choose the T5 model size, and changes the tests to only use the small 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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"You're probably on an old transformers version."
] | 1,585 | 1,585 | 1,585 | NONE | null | I am trying to use the script run_glue present in the transformers library to fintenue Flaubert for french data using huggingface's transformers and I am gettinh this error :
`
03/27/2020 11:54:48 - WARNING - __main__ - Process rank: -1, device: cuda, n_gpu: 2, distributed training: False, 16-bits training: Tru... | {
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- [x] Add Bart, T5 and MMBT to main docs page
- [x] Add MMBT docs
- [ ] Add MMBT pretrained info
- [ ] Polish MMBT docstring | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3474?src=pr&el=h1) Report\n> Merging [#3474](https://codecov.io/gh/huggingface/transformers/pull/3474?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e392ba6938f50655a195ea7ec8a260b1e9fc6058&el=desc) will **increase... | 1,585 | 1,594 | 1,594 | NONE | null | No new features added and no modifications to the existing code has been done. Just addition of scripts for the fine-tuning. | {
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"Do you mind giving a reproducible example so that we may debug easily?",
"I was following this issue because I ran into the same problem. I won't use the code I ran into the problem with here but here is the gist:\r\n\r\n```python\r\nfrom transformers import XLNetForSequenceClassification\r\n\r\nmodel = XLNetFor... | 1,585 | 1,591 | 1,591 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): XLNet
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
The tasks I am working on is:
*... | {
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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"
] | 1,585 | 1,594 | 1,594 | NONE | null | This optimization in tokenization reduces the tokenization time by ~ 85-92 %
Stats:
Before fix:
8%|████████▉ | 119574/1486030 [01:03<12:09, 1874.22it/s]
After fix:
98%|████████████████████████████████████... | {
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"When you encode with `tokenizer = AlbertTokenizer.from_pretrained('albert-base-v2')` a [CLS] token is added in the beginning and a [SEP] token is added at the end. You can verify this by: \r\n\r\n```python \r\nfrom transformers import AlbertTokenizer, TFAlbertForMaskedLM\r\n\r\ntokenizer = AlbertTokenizer.from_pre... | 1,585 | 1,585 | 1,585 | NONE | null | # 🐛 Bug
## Information
### Model
TFAlbertForMaskedLM <https://huggingface.co/transformers/model_doc/albert.html#tfalbertformaskedlm>
### Language
English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
```pytho... | {
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"\r\n\r\nHappy to help on this @LysandreJik @patrickvonplaten",
"The test runs fine locally on my computer. A couple of wild thoughts:\r\n\r\n- It happened after merging #3411 and #3428 which adds quite so... | 1,585 | 1,585 | 1,585 | CONTRIBUTOR | null | Started happening at https://github.com/huggingface/transformers/pull/3428
and has been happening consistently.
scroll all the way down for [traceback](https://circleci.com/gh/huggingface/transformers/26044?utm_campaign=vcs-integration-link&utm_medium=referral&utm_source=github-build-link) | {
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"The file `run_language_modeling.py` does indeed not have a variable called `MODEL_CLASSES`. Can you explain what you are trying to do exactly?"
] | 1,585 | 1,585 | 1,585 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...):GPT2
```python
def generate_samples(args, model, prompt_text):
"""Generating sampling for the provided prompt using the provided model."""
set_seed(args.seed)
_, _, tokenizer_class = run_language_modeling.MODEL_CLASSES[args.model_type]
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3467?src=pr&el=h1) Report\n> Merging [#3467](https://codecov.io/gh/huggingface/transformers/pull/3467?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/63f4d8cad010f1972254007ad56b22fe5ed203fe&el=desc) will **increase... | 1,585 | 1,585 | 1,585 | CONTRIBUTOR | null | {
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"Was fixed with https://github.com/huggingface/transformers/commit/e2c05f06ef58ea77103d2c64492dd8d9a0b21c3f"
] | 1,585 | 1,585 | 1,585 | MEMBER | null | # 🐛 Bug
## Information
Docstring
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
## To reproduce
Steps to reproduce the behavior:
1. `pip install -e ".[docs]"` at `transformers` root folder
2. `cd docs`
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"Had the same Issue, I think it was already fixed in an older commit, but the pip package doesnt seem to be updated. Try installing transformers from this repo:\r\n`git clone https://github.com/huggingface/transformers`\r\n`cd transformers`\r\n`pip install .`",
"I also had the same issue as @paras55, and the solu... | 1,585 | 1,594 | 1,594 | NONE | null | This is error while running the question answering pipeline !
convert squad examples to features: 0%| | 0/1 [00:00<?, ?it/s]
---------------------------------------------------------------------------
RemoteTraceback Traceback (most recent call last)
RemoteTraceback:
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"`transformers` 2.6.0 has dropped support for Python 3.5: https://github.com/huggingface/transformers/releases/tag/v2.6.0",
"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"
] | 1,585 | 1,591 | 1,591 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): ALBERT
Language I am using the model on (English, Chinese ...):
The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
## To reproduce
Steps to reproduc... | {
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https://api.github.com/repos/huggingface/transformers/issues/3461 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3461/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3461/comments | https://api.github.com/repos/huggingface/transformers/issues/3461/events | https://github.com/huggingface/transformers/pull/3461 | 588,605,997 | MDExOlB1bGxSZXF1ZXN0Mzk0MzIxMzU0 | 3,461 | Add T5 to docs | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3461?src=pr&el=h1) Report\n> Merging [#3461](https://codecov.io/gh/huggingface/transformers/pull/3461?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/3ee431dd4c720e67e35a449b453d3dc2b15ccfff&el=desc) will **increase... | 1,585 | 1,585 | 1,585 | MEMBER | null | - [x] Copy past from bart docs
- [x] polish main docs page
- [x] improve docstring in `modeling_t5.py` and `modeling_tf_t5.py` | {
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https://api.github.com/repos/huggingface/transformers/issues/3460 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3460/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3460/comments | https://api.github.com/repos/huggingface/transformers/issues/3460/events | https://github.com/huggingface/transformers/issues/3460 | 588,601,234 | MDU6SXNzdWU1ODg2MDEyMzQ= | 3,460 | Error : forward() got an unexpected keyword argument 'inputs_embeds' | {
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"I can run the following code succesfully: \r\n\r\n```\r\nfrom transformers import GPT2Model, GPT2Tokenizer\r\nimport torch\r\n\r\nmodel = GPT2Model.from_pretrained('gpt2')\r\ntokenizer = GPT2Tokenizer.from_pretrained('gpt2', pad_token='<PAD>')\r\n\r\ninput_ids = tokenizer.encode(\"Hello, how are you?\", return_ten... | 1,585 | 1,597 | 1,585 | NONE | null | Hello,
I am trying to train a GPT2 from scratch using ```modeling_gpt2.py``` as a base.
I declared the model as follow :
```Python
config = GPT2Config(vocab_size = VELSIZE, n_positions = SEQLEN, n_embd = EMBEDSIZE, n_layer = NUMLAYER,n_ctx = SEQLEN, n_head = NUMHEAD)
model = GPT2Model(config)
```
I don'... | {
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https://api.github.com/repos/huggingface/transformers/issues/3458 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3458/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3458/comments | https://api.github.com/repos/huggingface/transformers/issues/3458/events | https://github.com/huggingface/transformers/issues/3458 | 588,570,744 | MDU6SXNzdWU1ODg1NzA3NDQ= | 3,458 | WARNING - __main__ - Process rank: -1, device: cuda, n_gpu: 2, distributed training: False, 16-bits training: True | {
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"？how to solve it"
] | 1,585 | 1,687 | 1,585 | NONE | null | I am trying to use the script run_glue to fintenue Flaubert for french data using huggingface's transformers and I am gettinh this error :
`
03/27/2020 11:54:48 - WARNING - __main__ - Process rank: -1, device: cuda, n_gpu: 2, distributed training: False, 16-bits training: True
Traceback (most recent call last)... | {
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"Importing `TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING` from `transformers` works for me. Can you update your transformers library and see whether you still get the import error.",
"Hi,\r\n\r\nI have the same issue here. I have installed transformers from source with the latest update.\r\n But still this **ImportE... | 1,585 | 1,586 | 1,585 | NONE | null | Wanted to use the ner demo, but after running:
`!python3 ./ner/run_tf_ner.py --data_dir /data --model_type bert --labels .data/labels.txt --model_name_or_path bert-base-multilingual-cased --output_dir germeval-model --max_seq_length 128 --num_train_epochs 3 --per_device_train_batch_size 32 --save_steps 750 --seed 1... | {
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https://api.github.com/repos/huggingface/transformers/issues/3456 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3456/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3456/comments | https://api.github.com/repos/huggingface/transformers/issues/3456/events | https://github.com/huggingface/transformers/issues/3456 | 588,465,885 | MDU6SXNzdWU1ODg0NjU4ODU= | 3,456 | Fine-tuning with BertForSequenceClassification on custom dataset yields a model that outputs only the label with highest support in training set | {
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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",
"@royeis did you find solution for this? I am facing the same issue. ",
"@SarikGhazarian \r\nEnded up solving this with a workaround. ... | 1,585 | 1,595 | 1,591 | NONE | null | Hello!
I have a custom dataset that I wish to fine tune BERT on for classification. The examples consist of 3 sequences each and the label set is {0, 1, ..., 9}. The training data has 570 examples, and validation has 150 examples.
The encoding of the input examples is as follows:
`tmp_enc = sequence_a + ' [SEP] ' +... | {
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"Merging this as discussed (preliminarily) with @LysandreJik last week",
"This is great."
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https://api.github.com/repos/huggingface/transformers/issues/3454 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3454/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3454/comments | https://api.github.com/repos/huggingface/transformers/issues/3454/events | https://github.com/huggingface/transformers/issues/3454 | 588,440,095 | MDU6SXNzdWU1ODg0NDAwOTU= | 3,454 | NER pipeline usage examples | {
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"The German and English CoNLL datasets use the IOB1 tagging scheme. `B-` is only used to separate two adjacent entities of the same type."
] | 1,585 | 1,585 | 1,585 | NONE | null | In the NER usage examples:
https://huggingface.co/transformers/usage.html#named-entity-recognition
Can you explain why the examples give only I- entities? For example:
('New', 'I-LOC'), ('York', 'I-LOC'), ('City', 'I-LOC')
('Hu', 'I-ORG'), ('##gging', 'I-ORG'), ('Face', 'I-ORG'), ('Inc', 'I-ORG')
Why are there... | {
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"We had to turn that model off because it was really expensive/hard to operationalize.\r\n\r\nWe'll add a warning to that particular webpage. (cc @LysandreJik)"
] | 1,585 | 1,585 | 1,585 | NONE | null | When setting the model size to **gpt2/xl**, WwT gets stuck on loading the autocomplete.
Checking Chrome's console tells me
"Failed to load resource: the server responded with a status of 502 (Bad Gateway)"
Having a quick look through the older tickets, I saw that this has happened before. #2121 | {
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"@acarrera94 does this look OK?",
"This looks great! Something else we might want to figure out is the best configuration of max_seq_length and max_target_length. For example, the tesla V100 in google colab can for sure handle about max_seq_length=768 and max_target_length=56 with a batch size of 4. It can't hand... | 1,585 | 1,586 | 1,586 | CONTRIBUTOR | null | - factor out redundant tokenization logic
- For both articles and summaries, batches are "trimmed" such that no columns are full of `pad_token_id`.
- The max sizes are 1024 for source and 56 for target. This ensures that truncation never happens for summaries, and rarely happens for articles. These values are uncha... | {
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https://api.github.com/repos/huggingface/transformers/issues/3449 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3449/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3449/comments | https://api.github.com/repos/huggingface/transformers/issues/3449/events | https://github.com/huggingface/transformers/pull/3449 | 588,363,258 | MDExOlB1bGxSZXF1ZXN0Mzk0MTIzMTQ3 | 3,449 | revert unpin isort commit | {
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"This syntax is not support by PyPi unfortunately, so we had to revert this.",
"> This syntax is not support by PyPi unfortunately, so we had to revert this.\r\n\r\nI see...is there another way of getting the pinned version? \r\nIn general, do we need isort? Doesn't black also sort the import statements? ",
"O... | 1,585 | 1,585 | 1,585 | MEMBER | null | This PR reverts the change of
https://github.com/huggingface/transformers/commit/fbc5bf10cfe4d4ca81f8daacc148b0abd51dda5a
Using the unpinned version of `isort` makes black and `isort` disagree in some cases.
In this PR the unpinned version of `isort` leads to a falied code quality test:
https://github.com/huggi... | {
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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"
] | 1,585 | 1,591 | 1,591 | NONE | null | # 🐛 Bug
## Information
Model I am using: Bert
Language I am using the model on: English, German, Swedish
The problem arises when using:
* [x] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
The tasks I am working on is:
* [ ] an official GLUE/SQU... | {
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https://api.github.com/repos/huggingface/transformers/issues/3447 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3447/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3447/comments | https://api.github.com/repos/huggingface/transformers/issues/3447/events | https://github.com/huggingface/transformers/issues/3447 | 588,329,149 | MDU6SXNzdWU1ODgzMjkxNDk= | 3,447 | Save models after each epoch | {
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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 also need this. Did you figure out a better way of doing it other than counting the number of checkpoints required for an epoch manua... | 1,585 | 1,601 | 1,601 | NONE | null | # 🚀 Feature request
In the various training scripts in `examples`, would it be better to checkpoint the model at the end of each epoch, as well as every `save_steps` iterations as specified by the user?
## Motivation
I suppose for language modelling, saving the model after each epoch is not as important, but for ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3446 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3446/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3446/comments | https://api.github.com/repos/huggingface/transformers/issues/3446/events | https://github.com/huggingface/transformers/issues/3446 | 588,328,329 | MDU6SXNzdWU1ODgzMjgzMjk= | 3,446 | Special tokens to pre-trained BART model | {
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"Hi!\r\nTwo points that might be helpful.\r\n- The `add_special_tokens` functionality should work the same as `RobertaTokenizer`. \r\n- `<s>` is already the `bos` token, so I don't expect it to be broken up.\r\n\r\nLet me know if that resolves your issue, thanks!",
"\r\nNot sure how to go about doing this ?\r\n@s... | 1,585 | 1,621 | 1,585 | CONTRIBUTOR | 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 Stack Overflow (SO) where a whole community of PyTorch and
Tensorflow enthusiast can help you out. Make s... | {
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"Hi, this is not currently supported, you would need to implement this yourself. Feel free to open a PR if you do"
] | 1,585 | 1,585 | 1,585 | 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 Stack Overflow (SO) where a whole community of PyTorch and
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https://api.github.com/repos/huggingface/transformers/issues/3444 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3444/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3444/comments | https://api.github.com/repos/huggingface/transformers/issues/3444/events | https://github.com/huggingface/transformers/issues/3444 | 588,181,401 | MDU6SXNzdWU1ODgxODE0MDE= | 3,444 | Import error in example script `run_language_modeling.py` | {
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"You need to upgrade your version of transformers (to 2.6), or better, to [install from source](https://github.com/huggingface/transformers#run-the-examples).",
"I just pulled the `huggingface/transformers-tensorflow-gpu:2.10.0` docker image, went to the `examples/language-modeling/` folder and ran the following,... | 1,585 | 1,590 | 1,585 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): RobertaForMaskedLM
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
The tasks I am work... | {
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"Seems like scibert is also broken. When I run\r\n\r\n```\r\npython run_language_modeling.py \\\r\n --output_dir=output \\\r\n --model_type=scibert \\\r\n --model_name_or_path=allenai/scibert_scivocab_cased \\\r\n --output_dir=/kaggle/working/model \\\r\n --do_train \\\r\n --line_by_line \\\r\n ... | 1,585 | 1,591 | 1,591 | CONTRIBUTOR | null | # 🐛 Bug
The `run_language_modeling.py` fails when using community models.
## Information
Model I am using (Bert, XLNet ...): BioClinical_BERT
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [ ] m... | {
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"I try it in Mac, it had same error\r\nmy enviroment is transformers 2.4 mac python 3.7",
"That's because you don't have TensorFlow 2 installed.",
"Conda users:\r\n\r\nFor whom the problem is not solved with re/installing TensorFlow, update the modules in conda.\r\n`conda install tensorflow`",
"You might want... | 1,585 | 1,629 | 1,585 | NONE | null | this is the log when I imported the TFBertModel from transformers
```
from transformers import TFBertModel
ImportError: cannot import name 'TFBertModel' from 'transformers' (/home/cally/.local/lib/python3.7/site-packages/transformers/__init__.py)
```
my enviroment is transformers 2.4 linux python 3.7 | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3441?src=pr&el=h1) Report\n> Merging [#3441](https://codecov.io/gh/huggingface/transformers/pull/3441?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/010e0460b22ddd7f74e31163f69ab3da2e9741ba&el=desc) will **decrease... | 1,585 | 1,587 | 1,587 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/3440 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3440/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3440/comments | https://api.github.com/repos/huggingface/transformers/issues/3440/events | https://github.com/huggingface/transformers/pull/3440 | 588,074,571 | MDExOlB1bGxSZXF1ZXN0MzkzODk1MDA3 | 3,440 | feat: config what's trainable in Bert layers | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3440?src=pr&el=h1) Report\n> Merging [#3440](https://codecov.io/gh/huggingface/transformers/pull/3440?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/010e0460b22ddd7f74e31163f69ab3da2e9741ba&el=desc) will **increase... | 1,585 | 1,594 | 1,594 | CONTRIBUTOR | null | Make it possible to configure trainability for specific subparts of a `TFBertMainLayer`.
This is minimal and Bert-only. Really should be added in more model types, not just Bert, but it probably necessarily differs quite a bit between model types, so probably can't be done in a very “DRY” way.
See https://github.... | {
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close #3227
These two issues happen because the `token_type_ids` are not generated by the `encode_plus` method when the SQuAD and multiple choice scripts expect it. The GLUE script was patched by #3240 | {
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https://api.github.com/repos/huggingface/transformers/issues/3438 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3438/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3438/comments | https://api.github.com/repos/huggingface/transformers/issues/3438/events | https://github.com/huggingface/transformers/issues/3438 | 587,998,589 | MDU6SXNzdWU1ODc5OTg1ODk= | 3,438 | Same probability from fine-tuning custom pre-trained LM | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,585 | 1,619 | 1,619 | 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 Stack Overflow (SO) where a whole community of PyTorch and
Tensorflow enthusiast can help you out. Make s... | {
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"Tagging @srush @nateraw from the original [Lightning GLUE PR](https://github.com/huggingface/transformers/pull/3290) to check I'm not missing something?",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3437?src=pr&el=h1) Report\n> Merging [#3437](https://codecov.io/gh/huggingface/transformers/p... | 1,585 | 1,592 | 1,585 | CONTRIBUTOR | null | Without this fix, I'm getting near-random validation performance for a trained model, and the validation performance differs per validation run. I think this happens since the `model` variable isn't set with the loaded checkpoint, so I'm using a randomly initialized model. Looking at the model activations, they differ ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3436 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3436/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3436/comments | https://api.github.com/repos/huggingface/transformers/issues/3436/events | https://github.com/huggingface/transformers/issues/3436 | 587,957,792 | MDU6SXNzdWU1ODc5NTc3OTI= | 3,436 | TFXLMRoberta impossible to load base and large model with pretrained weight ? | {
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"maybe u can use from_pt=True\r\nTFXLMRobertaForSequenceClassification.from_pretrained(pretrained_model_name_or_path=\"xlm-roberta-large\", **_from_pt=True_**)",
"Hi, thanks for your answer.\r\nI got exactly the same message with \"from_pt=True\"",
"I am suspecting that the file does not exist.\r\nI succeed to ... | 1,585 | 1,592 | 1,592 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...):
XLMRoberta
Language I am using the model on (English, Chinese ...):
The problem arises when using:
* [ x] the official example scripts: (give details below)
The tasks I am working on is:
my own task or dataset: (give details below)
## To r... | {
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https://api.github.com/repos/huggingface/transformers/issues/3435 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3435/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3435/comments | https://api.github.com/repos/huggingface/transformers/issues/3435/events | https://github.com/huggingface/transformers/pull/3435 | 587,930,786 | MDExOlB1bGxSZXF1ZXN0MzkzNzc4NTA5 | 3,435 | Updated/added model cards | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3435?src=pr&el=h1) Report\n> Merging [#3435](https://codecov.io/gh/huggingface/transformers/pull/3435?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ccbe839ee0b78a17e74dab218bfae7efe904ac3b&el=desc) will **increase... | 1,585 | 1,585 | 1,585 | CONTRIBUTOR | null | Trained four models, adding/updating model cards to make consistent! | {
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https://api.github.com/repos/huggingface/transformers/issues/3434 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3434/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3434/comments | https://api.github.com/repos/huggingface/transformers/issues/3434/events | https://github.com/huggingface/transformers/issues/3434 | 587,757,698 | MDU6SXNzdWU1ODc3NTc2OTg= | 3,434 | How to detokenize a BertTokenizer output? | {
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"I came across the same problem some days ago. I like your code, however it can be faster:\r\n\r\n```python\r\n\r\ndef is_subtoken(word):\r\n if word[:2] == \"##\":\r\n return True\r\n else:\r\n return False\r\n\r\ntokens = ['why', 'isn', \"##'\", '##t', 'Alex', \"##'\", 'text', 'token', '##izin... | 1,585 | 1,591 | 1,591 | NONE | null | For example, let's tokenize a sentece "why isn't Alex' text tokenizing":
tokenizer = BertTokenizer.from_pretrained('bert-base-uncased', do_lower_case=True)
tokens = tokenizer.tokenize("why isn't Alex' text tokenizing")
We are getting the next output:
['why', 'isn', "'", 't', 'Alex', "'", 'text', '... | {
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https://api.github.com/repos/huggingface/transformers/issues/3433 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3433/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3433/comments | https://api.github.com/repos/huggingface/transformers/issues/3433/events | https://github.com/huggingface/transformers/pull/3433 | 587,747,120 | MDExOlB1bGxSZXF1ZXN0MzkzNjI4NzMx | 3,433 | Extend config with task specific configs. | {
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"> I think this makes sense, giving where we've been going up to now.\r\n> \r\n> I would like to understand what is our philosophy with the growing size of the configuration files; for example the `bert-base-cased` configuration on S3 looks like this:\r\n> \r\n> ```\r\n> {\r\n> \"architectures\": [\r\n> \"Ber... | 1,585 | 1,585 | 1,585 | MEMBER | null | As discussed and proposed by @thomwolf in PR #3413, another step towards a combined tokenizer/model config is this PR. It extends the normal config with the following parameters:
```
{
....
prefix = "", # generic generation HP
max_length: 100,
length_penalty: 1.0,
task_specific_params: {
"summarizatio... | {
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https://api.github.com/repos/huggingface/transformers/issues/3432 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3432/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3432/comments | https://api.github.com/repos/huggingface/transformers/issues/3432/events | https://github.com/huggingface/transformers/issues/3432 | 587,708,041 | MDU6SXNzdWU1ODc3MDgwNDE= | 3,432 | how to use transformers to get all pretraining model names in transformers hub | {
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"```python\r\nfrom transformers.hf_api import HfApi\r\n\r\napi = HfApi()\r\nmodels = api.list_models()\r\n```\r\n\r\nThis is not very well documented yet so feel free to add to the doc."
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"You're not running the latest version of transformers.",
"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"
] | 1,585 | 1,590 | 1,590 | NONE | null | # 🐛 Bug
## Information
I am doing the tutorial ["Quick tour of the fine-tuning/usage scripts"](https://github.com/huggingface/transformers#quick-tour-of-the-fine-tuningusage-scripts)
I downloaded the Glue dataset.
When I try to run this command from pytorch
```
python ./examples/run_glue.py \
--model_... | {
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https://api.github.com/repos/huggingface/transformers/issues/3430 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3430/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3430/comments | https://api.github.com/repos/huggingface/transformers/issues/3430/events | https://github.com/huggingface/transformers/issues/3430 | 587,624,157 | MDU6SXNzdWU1ODc2MjQxNTc= | 3,430 | Problem saving and/or loading fine-tuned model | {
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"Hi @antoilouis,\r\n\r\nThanks for posting this. \r\nA quick wild guess might be that after training you save the model in `args.output_dir` but then load it from a different `args.model_name_or_path` (also since you said that if you evaluate the model right after training you get good results. \r\n\r\nMy advice to... | 1,585 | 1,666 | 1,591 | CONTRIBUTOR | null | # ❓ Questions & Help
I have finetuned bert-base-cased for multi-class classification with BertForSequenceClassification and got great results (about 88% accuracy on my dev data). However, when I save the finetuned model, load it and run the evaluation on the exact same dev data, I got awful results (about 0.17 accurac... | {
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https://api.github.com/repos/huggingface/transformers/issues/3429 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3429/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3429/comments | https://api.github.com/repos/huggingface/transformers/issues/3429/events | https://github.com/huggingface/transformers/issues/3429 | 587,612,101 | MDU6SXNzdWU1ODc2MTIxMDE= | 3,429 | Confusion in understanding the output of BERTforTokenClassification class from Transformers library | {
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"AFAIK, `12` does",
"For detailed explanation for this, refer\r\nhttps://stackoverflow.com/questions/60847291/confusion-in-understanding-the-output-of-bertfortokenclassification-class-from-t"
] | 1,585 | 1,585 | 1,585 | NONE | null | It is the example given in the documentation of transformers pytorch library
```
from transformers import BertTokenizer, BertForTokenClassification
import torch
tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
model = BertForTokenClassification.from_pretrained('bert-base-uncased')
input_ids = to... | {
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https://api.github.com/repos/huggingface/transformers/issues/3428 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3428/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3428/comments | https://api.github.com/repos/huggingface/transformers/issues/3428/events | https://github.com/huggingface/transformers/pull/3428 | 587,605,933 | MDExOlB1bGxSZXF1ZXN0MzkzNTE0NzU4 | 3,428 | Add wmt translation example | {
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"> long\r\n\r\nYeah we should definitely try to run it on a GPU - will take a look at that :-) ",
"Not sure whether we need fp16 and multi-gpu training. I think single GPU training is enough and t5 + wmt does not take much memory. But happy to take a look into it if you guys think it's worth it :-) @thomwolf @Lys... | 1,585 | 1,585 | 1,585 | MEMBER | null | PR adds translation example for T5.
It uses the `sacrebleu` BLEU scorer.
I adapted the README.md a bit so that users are aware that models in official paper were attained with finetuned T5 @craffel | {
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https://api.github.com/repos/huggingface/transformers/issues/3427 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3427/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3427/comments | https://api.github.com/repos/huggingface/transformers/issues/3427/events | https://github.com/huggingface/transformers/issues/3427 | 587,596,866 | MDU6SXNzdWU1ODc1OTY4NjY= | 3,427 | I want to create a tokenizer which the vocab file in my computer | {
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"Your config.json file should be named `config.json`, and then you should be able to do:\r\n```\r\nself.model_config = AutoConfig.from_pretrained(r'/home/cally/Awake/Code/bert/pre_model/')\r\nself.tokenizer = AutoTokenizer.from_pretrained(r'/home/cally/Awake/Code/bert/pre_model/')\r\n```\r\n\r\n(just the folder nam... | 1,585 | 1,620 | 1,585 | NONE | null | I want to create a tokenizer in my computer, which the vocab file is below, my code as below
```
self.model_config = AutoConfig.from_pretrained(r'/home/cally/Awake/Code/bert/pre_model/bert_config.json')
self.tokenizer = AutoTokenizer.from_pretrained(r'/home/cally/Awake/Code/bert/pre_model/vocab.txt')
```
it appear... | {
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https://api.github.com/repos/huggingface/transformers/issues/3426 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3426/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3426/comments | https://api.github.com/repos/huggingface/transformers/issues/3426/events | https://github.com/huggingface/transformers/issues/3426 | 587,449,620 | MDU6SXNzdWU1ODc0NDk2MjA= | 3,426 | Expected object of device type cuda but got device type cpu for argument #1 'self' in call to _th_index_selec | {
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"Are the inputs also being cast to GPU?",
"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"
] | 1,585 | 1,591 | 1,591 | NONE | null | I wrapped the code base into a flask container and tried to run it on a GPU and I am running into a GPU device copy issue. Looking for pointers.
I have verified that the model actually gets moved to the GPU:
` self.model.to(torch.device("cuda" if torch.cuda.is_available() and not "store_true" else "cpu"))
... | {
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https://api.github.com/repos/huggingface/transformers/issues/3425 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3425/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3425/comments | https://api.github.com/repos/huggingface/transformers/issues/3425/events | https://github.com/huggingface/transformers/pull/3425 | 587,431,688 | MDExOlB1bGxSZXF1ZXN0MzkzMzc1Njc1 | 3,425 | Update model card huseinzol05/bert-base-bahasa-cased | {
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"Hi @huseinzol05! can you rebase on master so that it's easy to merge?",
"@julien-c , done! thank u very much!",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3425?src=pr&el=h1) Report\n> Merging [#3425](https://codecov.io/gh/huggingface/transformers/pull/3425?src=pr&el=desc) into [master](ht... | 1,585 | 1,585 | 1,585 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/3424 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3424/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3424/comments | https://api.github.com/repos/huggingface/transformers/issues/3424/events | https://github.com/huggingface/transformers/issues/3424 | 587,387,008 | MDU6SXNzdWU1ODczODcwMDg= | 3,424 | Where is the code of Bart fine-tuning?Thanks | {
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"Hi,\r\nthe code is in `transformers/examples/summarization/bart/`. Read the `README.md` file.\r\n\r\n> To use your own data, copy that files format. Each article to be summarized is on its own line.\r\n\r\nOr look at issue #3672"
] | 1,585 | 1,587 | 1,587 | NONE | null | {
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https://api.github.com/repos/huggingface/transformers/issues/3422 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3422/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3422/comments | https://api.github.com/repos/huggingface/transformers/issues/3422/events | https://github.com/huggingface/transformers/pull/3422 | 587,319,727 | MDExOlB1bGxSZXF1ZXN0MzkzMjg4Njc1 | 3,422 | [BART] add bart-large-xsum weights | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3422?src=pr&el=h1) Report\n> Merging [#3422](https://codecov.io/gh/huggingface/transformers/pull/3422?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/17dceae7a1de5577cd0c07a97dcd5821a08af07c&el=desc) will **decrease... | 1,585 | 1,585 | 1,585 | CONTRIBUTOR | null | - conversion script can now take a path, which is required since this model is not on `torch.hub`. Finetuning with fairseq and then converting to huggingface should work. I also cleaned it up a bit
- Config in S3 is already updated with author-recommended generation parameters:
`(num_beams=6, length_penalty=1., min_l... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3421?src=pr&el=h1) Report\n> Merging [#3421](https://codecov.io/gh/huggingface/transformers/pull/3421?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/d0c36a7b7270f114322c191866d29abea383e5da&el=desc) will **increase... | 1,585 | 1,585 | 1,585 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/3420 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3420/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3420/comments | https://api.github.com/repos/huggingface/transformers/issues/3420/events | https://github.com/huggingface/transformers/issues/3420 | 587,277,985 | MDU6SXNzdWU1ODcyNzc5ODU= | 3,420 | Reading files takes for ever in language modeling | {
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"the same issue happens with me when running on 30 GB English Text, with the same parameters given to the script",
"@julien-c any recommendations on this issue?",
"Maybe launch on a single node and in a debugger, to see what's happening?",
"I have run the debugging both with pre-trained tokenizer using --mode... | 1,585 | 1,595 | 1,595 | NONE | null | # 🐛 Bug
## Information
Model I am using (GPT2):
Language I am using the model on (Music Midifiles tokens):
The problem arises when using:
* [ ] the official example scripts: (give details below)
The tasks I am working on is:
* language modeling, running the script run_langauge_modling.py
## To re... | {
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https://api.github.com/repos/huggingface/transformers/issues/3419 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3419/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3419/comments | https://api.github.com/repos/huggingface/transformers/issues/3419/events | https://github.com/huggingface/transformers/pull/3419 | 587,267,666 | MDExOlB1bGxSZXF1ZXN0MzkzMjQ2MzY3 | 3,419 | Adds translation pipeline | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3419?src=pr&el=h1) Report\n> Merging [#3419](https://codecov.io/gh/huggingface/transformers/pull/3419?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/9c683ef01e19c4dc1216dcd1ae3c8e7c44d7b2b9&el=desc) will **increase... | 1,585 | 1,585 | 1,585 | MEMBER | null | The API for translation is as follows:
```
en_fr_translation = pipeline("translation_en_to_fr")
en_fr_translation("How old are you?")
```
for English to French translation.
PR adds tests and gives an example in the docstring.
PR builds on #3413 and should be merged after this one.
Example:
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https://api.github.com/repos/huggingface/transformers/issues/3418 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3418/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3418/comments | https://api.github.com/repos/huggingface/transformers/issues/3418/events | https://github.com/huggingface/transformers/issues/3418 | 587,242,349 | MDU6SXNzdWU1ODcyNDIzNDk= | 3,418 | Unused function in squad metrics | {
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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"
] | 1,585 | 1,590 | 1,590 | CONTRIBUTOR | null | In the squad metrics file, I noticed an unused function `find_all_best_thresh_v2`
https://github.com/huggingface/transformers/blob/master/src/transformers/data/metrics/squad_metrics.py#L167
It looks to be pertaining to the squad v2.0 dataset type, which has 'impossible' questions for contexts.
It looks like i... | {
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https://api.github.com/repos/huggingface/transformers/issues/3417 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3417/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3417/comments | https://api.github.com/repos/huggingface/transformers/issues/3417/events | https://github.com/huggingface/transformers/pull/3417 | 587,234,634 | MDExOlB1bGxSZXF1ZXN0MzkzMjE5NTAz | 3,417 | Fix XLNet batch generation bug | {
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"Hi @neonbjb,\r\n\r\nsorry to answer waaaay to late.\r\nBatch generation currently does not work. See #3021\r\n\r\nWe are not sure yet when and how to add this feature.",
"Uhhhh.. but it could with this PR? I have it working on my cloned repo and used it in this writeup. Your call though.\r\nhttps://nonint.com/20... | 1,585 | 1,591 | 1,591 | CONTRIBUTOR | null | When doing batch generation with XLNet, only the first element in the batch contains any predictions. This seems to be caused by the target_mapping being improperly initialized in prepare_inputs_for_generation. | {
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https://api.github.com/repos/huggingface/transformers/issues/3416 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3416/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3416/comments | https://api.github.com/repos/huggingface/transformers/issues/3416/events | https://github.com/huggingface/transformers/issues/3416 | 587,227,546 | MDU6SXNzdWU1ODcyMjc1NDY= | 3,416 | XLNet model on S3 not set up correctly? | {
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"After looking into this some more. It looks like my issue was arising from the fact that the XLNet authors published both a 'base' and 'large' version of their model: \r\n\r\n\r\n\r\nIt seems like the conf... | 1,585 | 1,585 | 1,585 | NONE | null | Hi all,
**I'm trying to initialize an XLNetForSequenceClassification model as follows:**
```
from transformers import XLNetForSequenceClassification, XLNetConfig
configuration = XLNetConfig()
model = XLNetForSequenceClassification.from_pretrained("xlnet-base-cased", config=configuration)
```
**However I'... | {
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https://api.github.com/repos/huggingface/transformers/issues/3415 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3415/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3415/comments | https://api.github.com/repos/huggingface/transformers/issues/3415/events | https://github.com/huggingface/transformers/issues/3415 | 587,127,797 | MDU6SXNzdWU1ODcxMjc3OTc= | 3,415 | Problem with running Transformer Notebook: How to train a language model | {
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"Importing CONFIG_MAPPING from https://github.com/huggingface/transformers/blob/master/src/transformers/configuration_auto.py to https://github.com/huggingface/transformers/blob/master/src/transformers/__init__.py fixes the problem (for the last version of the package)",
"This should be fixed on master by f8823ba... | 1,585 | 1,585 | 1,585 | NONE | null | Hello,
in the page:
https://github.com/huggingface/transformers/blob/master/notebooks/README.md
I clicked "open in colab" on the notebook "How to train a language model".
When the last run cell was run:
%%time
!{cmd}
The following error was presented:
Traceback (most recent call last):
File "ru... | {
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https://api.github.com/repos/huggingface/transformers/issues/3414 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3414/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3414/comments | https://api.github.com/repos/huggingface/transformers/issues/3414/events | https://github.com/huggingface/transformers/issues/3414 | 587,056,829 | MDU6SXNzdWU1ODcwNTY4Mjk= | 3,414 | Add custom rules for sampling from GPT-2 Generator | {
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"Hey @simonefrancia happy that you liked the blog post :-) \r\n\r\nThis sounds like quite a special sampling function, so the best you can do would be to fork/clone the repo and add this functionality yourself. If the sampling function is too special we probably will not include it into the master branch. \r\n\r\nB... | 1,585 | 1,585 | 1,585 | CONTRIBUTOR | null | Hi @patrickvonplaten,
I've read your [blogpost](https://huggingface.co/blog/how-to-generate) and it's really interesting. Thanks! I have a question for that.
We have recently trained a GPT-2 generator with HF on general text and it works well.
But to have better results on my custom task, I would like to add a c... | {
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https://api.github.com/repos/huggingface/transformers/issues/3413 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3413/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3413/comments | https://api.github.com/repos/huggingface/transformers/issues/3413/events | https://github.com/huggingface/transformers/pull/3413 | 586,999,880 | MDExOlB1bGxSZXF1ZXN0MzkzMDIzNjQ0 | 3,413 | Add t5 to pipeline(task='summarization') | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3413?src=pr&el=h1) Report\n> Merging [#3413](https://codecov.io/gh/huggingface/transformers/pull/3413?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e392ba6938f50655a195ea7ec8a260b1e9fc6058&el=desc) will **increase... | 1,585 | 1,585 | 1,585 | MEMBER | null | This PR:
- adds T5 to summarization piplines.
- adds warnings and better defaults to Bart/T5 summarization
- removes unnecessary assert in generate() function
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