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https://api.github.com/repos/huggingface/transformers/issues/2913 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2913/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2913/comments | https://api.github.com/repos/huggingface/transformers/issues/2913/events | https://github.com/huggingface/transformers/pull/2913 | 567,827,276 | MDExOlB1bGxSZXF1ZXN0Mzc3MzgwMjIx | 2,913 | make RobertaForMaskedLM implementation identical to fairseq | {
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"Awesome. Could you check if the existing @slow tests break for Roberta, and add a new one that hardcodes the fairseq logits from your example and makes sure we also return them. Trying to avoid accidental breakage. Thanks again! ",
"@sshleifer Not sure how I would hardcode a tensor of size 1, 12, 50265. Can I ju... | 1,582 | 1,582 | 1,582 | COLLABORATOR | null | closes https://github.com/huggingface/transformers/issues/1874
The implementation of RoBERTa in `transformers` differs from the original implementation in [fairseq](https://github.com/pytorch/fairseq/tree/master/fairseq/models/roberta), as results showed (cf. https://github.com/huggingface/transformers/issues/1874).... | {
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https://api.github.com/repos/huggingface/transformers/issues/2912 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2912/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2912/comments | https://api.github.com/repos/huggingface/transformers/issues/2912/events | https://github.com/huggingface/transformers/pull/2912 | 567,824,937 | MDExOlB1bGxSZXF1ZXN0Mzc3Mzc4MjQ5 | 2,912 | Override build_inputs_with_special_tokens for fast tokenizers | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2912?src=pr&el=h1) Report\n> Merging [#2912](https://codecov.io/gh/huggingface/transformers/pull/2912?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/59c23ad9c931ac4fe719abeb3c3851df046ef3a6?src=pr&el=desc) will **i... | 1,582 | 1,582 | 1,582 | MEMBER | null | Signed-off-by: Morgan Funtowicz <morgan@huggingface.co> | {
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https://api.github.com/repos/huggingface/transformers/issues/2911 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2911/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2911/comments | https://api.github.com/repos/huggingface/transformers/issues/2911/events | https://github.com/huggingface/transformers/issues/2911 | 567,769,840 | MDU6SXNzdWU1Njc3Njk4NDA= | 2,911 | missing "para" attribute in ARC dataset for multiple choice question answering model | {
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"Got it. \r\nThis parameter is for the context.",
"May I know how do you solve this problem? I just ran into this problem.",
"You will have to add a \"para\" field for every choice - This is for adding knowledge. To get a baseline you can simply use a dummy text in that field \r\n\r\n`{\r\n \"id\": \"MCAS_2000... | 1,582 | 1,586 | 1,582 | NONE | null | # 🐛 Bug
## Information
Model I am using Roberta.
Language I am using the model on (English)
The problem arises when using:
* [ ] the official example scripts: (give details below)
**https://github.com/huggingface/transformers/blob/master/examples/utils_multiple_choice.py**
The tasks I am working on is... | {
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https://api.github.com/repos/huggingface/transformers/issues/2910 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2910/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2910/comments | https://api.github.com/repos/huggingface/transformers/issues/2910/events | https://github.com/huggingface/transformers/issues/2910 | 567,751,259 | MDU6SXNzdWU1Njc3NTEyNTk= | 2,910 | `PreTrainedTokenizerFast.build_inputs_with_special_tokens` doesn't add the special tokens | {
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"Hi @bryant1410, \r\n\r\nThanks for reporting the issue, as a workaround for now, can you try the following:\r\n\r\n```python\r\ntokenizer.tokenize(\"abc\")\r\ntokenizer.tokenizer(\"def\")\r\n```\r\n\r\nIt should do the same, let me know.\r\nIn the meantime I'll have a closer look at the function `tokenizer.build_i... | 1,582 | 1,582 | 1,582 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): BertTokenizer (but seems to apply to most)
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below... | {
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"> Please incorporate my comments on this file in the other PR :)\r\n\r\nis on my radar :-) ",
"UPDATE: Changed slow tests for language generation design according to discussion in PR #2885 .\r\nIf this looks alright, I'll add test cases for the other LMModels @LysandreJik & @sshleifer ",
"# [Codecov](https://c... | 1,582 | 1,582 | 1,582 | MEMBER | null | Move implementation of slow hardcoded generate models to this PR from. Checkout previous discussion in PR #2885 | {
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https://api.github.com/repos/huggingface/transformers/issues/2908 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2908/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2908/comments | https://api.github.com/repos/huggingface/transformers/issues/2908/events | https://github.com/huggingface/transformers/issues/2908 | 567,634,883 | MDU6SXNzdWU1Njc2MzQ4ODM= | 2,908 | Model I am using Roberta | {
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## 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: (give details below)
* [ ] my own modified scripts: (give details below)
The tasks I am working on is:
* [ ] an offici... | {
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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",
"h56cho: I'm not sure if you ask about the code or the algorithm.\r\nAs far as I understand from the code, the class MLP is a basic 2-la... | 1,582 | 1,593 | 1,593 | NONE | null | Hello,
I am having some trouble understanding the MLP function used in the Hugging Face GPT-2, which is found [here](https://github.com/huggingface/transformers/blob/73028c5df0c28ca179fbe565482a9c2143787f61/src/transformers/modeling_gpt2.py#L204).
Q1. For MLP, why are we setting the n_state to be equal to 3072, w... | {
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https://api.github.com/repos/huggingface/transformers/issues/2906 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2906/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2906/comments | https://api.github.com/repos/huggingface/transformers/issues/2906/events | https://github.com/huggingface/transformers/issues/2906 | 567,579,770 | MDU6SXNzdWU1Njc1Nzk3NzA= | 2,906 | documentation for TF models mentions non-existent methods | {
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> The model is set in evaluation mode by default using ``model.eval()`` (Dropout modules are deactivated)
> To train the model, you should first set it back in traini... | {
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https://api.github.com/repos/huggingface/transformers/issues/2904 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2904/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2904/comments | https://api.github.com/repos/huggingface/transformers/issues/2904/events | https://github.com/huggingface/transformers/issues/2904 | 567,555,116 | MDU6SXNzdWU1Njc1NTUxMTY= | 2,904 | squad_convert_example_to_features does not work with CamembertTokenizer | {
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"Solved by #2746 "
] | 1,582 | 1,582 | 1,582 | NONE | null | # 🐛 Bug
## Information
Model I am using : CamemBERT
Language I am using the model on : French
The problem arises when using:
* [*] my own modified scripts: (give details below)
The tasks I am working on is:
* [*] an official GLUE/SQUaD task: SQUaD
## To reproduce
Steps to reproduce the behavior:
... | {
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"The differences between the BERT and RoBERTa model are the following:\r\n\r\n- Different pre-training (larger batch size for RoBERTa, no NSP, no token type ids ...)\r\n- Different tokenizer\r\n\r\nThe model architecture is exactly the same. The only real difference after the pre-training is the difference in token... | 1,582 | 1,582 | 1,582 | 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
Given that RoBERTa outperformed BERT on several tasks, yet having a slight architecture modification, I want to know if it is possible to co... | {
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https://api.github.com/repos/huggingface/transformers/issues/2901 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2901/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2901/comments | https://api.github.com/repos/huggingface/transformers/issues/2901/events | https://github.com/huggingface/transformers/issues/2901 | 567,446,250 | MDU6SXNzdWU1Njc0NDYyNTA= | 2,901 | Pre-trained BERT-LM missing LM Head - returns random token predictions | {
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"My guess would be that you'd need to load (and then save) with `BertForPreTraining` rather than `BertModel`.\r\n\r\nhttps://github.com/huggingface/transformers/blob/20fc18fbda3669c2f4a3510e0705b2acd54bff07/src/transformers/modeling_bert.py#L806",
"@BramVanroy you're my hero for today! Appreciated man! \r\n\r\nTe... | 1,582 | 1,582 | 1,582 | NONE | null | # 🐛 Bug
## Information
I released Greek BERT, almost a week ago and so far I'm exploring its use by running some benchmarks in Greek datasets. Although Greek BERT works just fine for sequence tagging (`AutoModelForTokenClassification`) and text classification (`AutoModelForSequenceClassification`), there are iss... | {
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https://api.github.com/repos/huggingface/transformers/issues/2899 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2899/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2899/comments | https://api.github.com/repos/huggingface/transformers/issues/2899/events | https://github.com/huggingface/transformers/issues/2899 | 567,295,418 | MDU6SXNzdWU1NjcyOTU0MTg= | 2,899 | RobertaTokenizer different than fairseq for 'world' | {
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"Reading more, pretty sure we only expect to have the same results as fairseq when the argument to fairseq starts with a space. Closing but would love verification/knowledge !",
"Yes, this comes from #2778, which changes the default behavior to automatically prepending a space when `add_special_tokens=True` for R... | 1,582 | 1,582 | 1,582 | CONTRIBUTOR | null | `pip install fairseq`
```
roberta = torch.hub.load('pytorch/fairseq', 'roberta.base')
rt = RobertaTokenizer.from_pretrained('roberta-base')
for ex in ['Hello world', ' Hello world', ' world', 'world', 'Hello', ' Hello']:
print(f'{ex} fairseq: {roberta.encode(ex).tolist()}, Transformers: {rt.encode(ex, add_pre... | {
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"It is both b) and c) :).",
"Hello @LysandreJik and @BramVanroy \r\n\r\nDid you have any results in training run_language_modeling.py for some language from scratch (i mean with and without NSP (next sentence prediction) as is in that script) ?\r\n\r\nDid you get better or relatively the same losses (and p... | 1,582 | 1,590 | 1,582 | NONE | null | The example script in `run_language_modeling.py` does not include the next sentence prediction for pre-training BERT. I was wondering if that is a) an oversight, b) for simplicity, or c) because you have found its impact to be non-significant? | {
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https://api.github.com/repos/huggingface/transformers/issues/2897 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2897/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2897/comments | https://api.github.com/repos/huggingface/transformers/issues/2897/events | https://github.com/huggingface/transformers/issues/2897 | 567,222,545 | MDU6SXNzdWU1NjcyMjI1NDU= | 2,897 | save_pretrained doesn't work with GPT2FastTokenizer | {
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"After upgrading to 2.5.0, the code now throws\r\n\r\n```\r\nTraceback (most recent call last):\r\n File \"<stdin>\", line 1, in <module>\r\n File \"/Users/bilal/Documents/transformers/src/transformers/tokenization_utils.py\", line 587, in save_pretrained\r\n return vocab_files + (special_tokens_map_file, adde... | 1,582 | 1,582 | 1,582 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): GPT2TokenizerFast
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [X ] my own modified scripts: (give details below)
The tasks I am work... | {
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https://api.github.com/repos/huggingface/transformers/issues/2896 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2896/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2896/comments | https://api.github.com/repos/huggingface/transformers/issues/2896/events | https://github.com/huggingface/transformers/issues/2896 | 567,173,047 | MDU6SXNzdWU1NjcxNzMwNDc= | 2,896 | BertModel' object missing 'save_pretrained' attribute | {
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"Hi, `from_pretrained` appeared in an older version of the library. `pytorch-pretrained-BERT` is a year old, is less robust and lacks certain functionalities (such as the one you mentioned) which are present in `transformers`."
] | 1,582 | 1,582 | 1,582 | NONE | null | I was attempting to download a pre-trained BERT model & save it to my cloud directory using Google Colab.
model.save_pretrained() seems to be missing completely for some reason.
Link to Colab notebook: https://colab.research.google.com/drive/1ix_nNhsd89nLfTy6Nyh-Ak8PHn1SYm-0
Here's my code:
```
!pip insta... | {
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https://api.github.com/repos/huggingface/transformers/issues/2895 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2895/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2895/comments | https://api.github.com/repos/huggingface/transformers/issues/2895/events | https://github.com/huggingface/transformers/pull/2895 | 567,091,007 | MDExOlB1bGxSZXF1ZXN0Mzc2Nzc5ODY3 | 2,895 | Enable 'from transformers import AlbertMLMHead' | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2895?src=pr&el=h1) Report\n> Merging [#2895](https://codecov.io/gh/huggingface/transformers/pull/2895?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/2ae98336d17fceea7506af9880b862b6252a38f6?src=pr&el=desc) will **d... | 1,582 | 1,582 | 1,582 | CONTRIBUTOR | null | Discussed at https://github.com/huggingface/transformers/issues/2894
I'm writing a custom pretraining script that incorporates both the masked language modeling (MLM) and sentence order prediction (SOP) objectives. I'm able to use the TFAlbertForMaskedLM model for the MLM objective, but need access to the last_hidde... | {
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https://api.github.com/repos/huggingface/transformers/issues/2894 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2894/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2894/comments | https://api.github.com/repos/huggingface/transformers/issues/2894/events | https://github.com/huggingface/transformers/issues/2894 | 567,084,724 | MDU6SXNzdWU1NjcwODQ3MjQ= | 2,894 | Allow import of model components, e.g. `from transformers import TFAlbertMLMHead` | {
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"Why don't you import it directly via\r\n`from transformers.modeling_tf_albert import TFAlbertMLMHead`\r\n?\r\nIn my opinion it is not good practise to expose everything via `__init__.py` because the autocomplete feature of an IDE will become messy.",
"That's true, don't know why that slipped my mind. Thanks for... | 1,582 | 1,582 | 1,582 | CONTRIBUTOR | null | # 🚀 Feature request
Expose model components such as custom layers like `TFAlbertMLMHead`, that are created in `modeling_tf_albert.py` and others.
## Motivation
I'm writing a custom pretraining script that incorporates both the masked language modeling (MLM) and sentence order prediction (SOP) objectives. I'm ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2893 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2893/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2893/comments | https://api.github.com/repos/huggingface/transformers/issues/2893/events | https://github.com/huggingface/transformers/issues/2893 | 567,084,440 | MDU6SXNzdWU1NjcwODQ0NDA= | 2,893 | Pipeline Loading Models and Tokenizers | {
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"Also cc'ing @fmikaelian on this for information :)",
"Apologize for the careless mistake @fmikaelian ",
"Hi, other than the careless mistake, I'm trying to understand why I cannot load any model from transformers S3 repo. I have tried :\r\n\r\n1) from transformers import FlaubertModel, FlaubertTokenizer\r\n\r\... | 1,582 | 1,583 | 1,583 | 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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https://api.github.com/repos/huggingface/transformers/issues/2892 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2892/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2892/comments | https://api.github.com/repos/huggingface/transformers/issues/2892/events | https://github.com/huggingface/transformers/pull/2892 | 567,079,208 | MDExOlB1bGxSZXF1ZXN0Mzc2NzcwMjY1 | 2,892 | Create README.md | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2892?src=pr&el=h1) Report\n> Merging [#2892](https://codecov.io/gh/huggingface/transformers/pull/2892?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/2ae98336d17fceea7506af9880b862b6252a38f6?src=pr&el=desc) will **d... | 1,582 | 1,582 | 1,582 | CONTRIBUTOR | null | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2891?src=pr&el=h1) Report\n> Merging [#2891](https://codecov.io/gh/huggingface/transformers/pull/2891?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/2ae98336d17fceea7506af9880b862b6252a38f6?src=pr&el=desc) will **n... | 1,582 | 1,582 | 1,582 | CONTRIBUTOR | null | 
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https://api.github.com/repos/huggingface/transformers/issues/2890 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2890/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2890/comments | https://api.github.com/repos/huggingface/transformers/issues/2890/events | https://github.com/huggingface/transformers/pull/2890 | 567,043,439 | MDExOlB1bGxSZXF1ZXN0Mzc2NzQxMzc2 | 2,890 | Support for torch-lightning in NER examples | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2890?src=pr&el=h1) Report\n> Merging [#2890](https://codecov.io/gh/huggingface/transformers/pull/2890?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/0dbddba6d2c5b2c6fc08866358c1994a00d6a1ff?src=pr&el=desc) will **n... | 1,582 | 1,588 | 1,582 | CONTRIBUTOR | null | Update of https://github.com/huggingface/transformers/pull/2816
This PR creates a new example coding style for the pytorch code.
* Uses pytorch-lightning for the underlying training.
* Separates out the base transformer loading from the individual training.
* Moves each individual example to its own directory.
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https://api.github.com/repos/huggingface/transformers/issues/2889 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2889/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2889/comments | https://api.github.com/repos/huggingface/transformers/issues/2889/events | https://github.com/huggingface/transformers/issues/2889 | 567,013,661 | MDU6SXNzdWU1NjcwMTM2NjE= | 2,889 | Getting: AttributeError: 'BertTokenizer' object has no attribute 'encode' | {
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"Please fix the formatting of your post and use code tags.",
"I made the changes still all the text is shown struck off form.\r\nI am new to this bug log not sure how to change to code tag \r\n\r\n",
"I have used <code> tag ",
"Read how to use tags here: https://help.github.com/en/github/writing-on-github/cr... | 1,582 | 1,593 | 1,593 | NONE | null | # 🐛 Bug
## AttributeError: 'BertTokenizer' object has no attribute 'encode'
Model, I am using Bert
The language I am using the model on English
The problem arises when using:
```
input_ids = torch.tensor([tokenizer.encode("raw_text", add_special_tokens=True)])
```
The tasks I am working on is:
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https://api.github.com/repos/huggingface/transformers/issues/2888 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2888/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2888/comments | https://api.github.com/repos/huggingface/transformers/issues/2888/events | https://github.com/huggingface/transformers/pull/2888 | 566,948,323 | MDExOlB1bGxSZXF1ZXN0Mzc2NjYzNDM1 | 2,888 | [WIP] Adapt lm generate fn for seq 2 seq models | {
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"Excited for this!\r\n\r\nA little early for me to have an opinion, but I'd start by adding a bunch of failing tests (e.g. for t5.generate), and some slow tests that verify that T5.generate/another non seq2seq model generate reasonable results. (You have to run those locally). \r\n\r\nStylistically, I'd say `is_seq... | 1,582 | 1,583 | 1,583 | MEMBER | null | From looking at the soon-to-be-added Bart model, I though the language generation could be conceptually adapted as shown below to be able to produce language from seq-to-seq models (Bart & T5).
So far this is not tested at all and only adapted for the `_generate_no_beam_search()` function. Also it still has to be c... | {
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"Hi,\r\nwhich model do you use? Can't you simply remove the output of the other heads?",
"I am using TFDistilbertmodelforsequenceclassification.\r\nYou are right,i can remove other head attention,but while using tfserving,it's taking a lot time ,since the output attentions has huge dimension.\r\nSo,that's why ,i ... | 1,582 | 1,582 | 1,582 | NONE | null | hi, while doing output_attentions - True in the huggingface model.it return attention of size:(no. of heads,seq length,seq length)
can we configure it to return only the attention of the last 2 heads of the model.
please let me know.
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https://api.github.com/repos/huggingface/transformers/issues/2886 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2886/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2886/comments | https://api.github.com/repos/huggingface/transformers/issues/2886/events | https://github.com/huggingface/transformers/issues/2886 | 566,721,632 | MDU6SXNzdWU1NjY3MjE2MzI= | 2,886 | Load Pretrained Model Error in Inherit Class | {
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"```\r\nclass RoBertaMultiwayMatch(nn.Module):\r\n def __init__(self, pretrainedConfigName, num_choices=4):\r\n super(RoBertaMultiwayMatch, self).__init__()\r\n self.num_choices = num_choices\r\n self.RoBerta = RobertaModel.from_pretrained(pretrainedConfigName)\r\n config = self.RoBer... | 1,582 | 1,588 | 1,588 | NONE | null | # ❓ Questions & Help
I wrote a new class based on RoBerta Model(pytorch)
## Details
The code is shown below
```
import torch
import numpy as np
import logging
import torch
from torch import nn
from torch.autograd import Variable
from torch.nn import CrossEntropyLoss
import torch.nn.functional as F
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2885?src=pr&el=h1) Report\n> Merging [#2885](https://codecov.io/gh/huggingface/transformers/pull/2885?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/d490b5d5003654f104af3abd0556e598335b5650?src=pr&el=desc) will **i... | 1,581 | 1,584 | 1,582 | MEMBER | null | This PR finally implements the following `bos_token_id, pad_token_id, eos_token_ids` logic for lm model generation.
1. If `bos_token_id` is None, then the input_ids must be defined otherwise, the model cannot generate text, which is checked by the asserts in the beginning. The `bos_token_id` is only relevant for sta... | {
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https://api.github.com/repos/huggingface/transformers/issues/2884 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2884/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2884/comments | https://api.github.com/repos/huggingface/transformers/issues/2884/events | https://github.com/huggingface/transformers/issues/2884 | 566,457,160 | MDU6SXNzdWU1NjY0NTcxNjA= | 2,884 | Evaluation and Inference added to run_glue.py | {
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"Hi! You can already provide `do_eval` to `run_glue` to do the evaluation. If you don't specify `do_train`, it will only do the evaluation, and no training.\r\n\r\nThe inference would be a nice addition.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed... | 1,581 | 1,588 | 1,588 | NONE | null | # 🚀 Feature request
It would be useful to have the following arguments added to `run_glue.py`, as well as probably the other task example scripts: `--eval_only` and `--inference_only`.
## Motivation
This will allow users to either provide a `.tsv` or `.csv` with either sentences and labels or just sentences a... | {
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"👍 "
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https://api.github.com/repos/huggingface/transformers/issues/2882 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2882/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2882/comments | https://api.github.com/repos/huggingface/transformers/issues/2882/events | https://github.com/huggingface/transformers/issues/2882 | 566,303,614 | MDU6SXNzdWU1NjYzMDM2MTQ= | 2,882 | No prediction for some words (BERT NER) when run on GPU | {
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"I tried to make the predictions using CPU, and it worked just fine. But the predictions made by CPU is totally different from the predictions made by GPU. Isn't a model supposed to give the same predictions irrespective of whether it is loaded in GPU or CPU?\r\n\r\nAny help would be appreciated.\r\nThanks in ad... | 1,581 | 1,588 | 1,588 | NONE | null | I have tried to make predictions over the test data using GPU, but ended up having no predictions for some words. Any help would be appreciated.
Following is the shell script used for prediction.
export MAX_LENGTH=128
export BERT_MODEL=bert-base-multilingual-cased
DATA_DIR=../DATA/after_preprocess
OUTPUT_DI... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2881?src=pr&el=h1) Report\n> Merging [#2881](https://codecov.io/gh/huggingface/transformers/pull/2881?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/6083c1566e261668a5de73cfe484c171ce232812?src=pr&el=desc) will **d... | 1,581 | 1,582 | 1,581 | MEMBER | null | adds one line to .gitignore | {
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https://api.github.com/repos/huggingface/transformers/issues/2880 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2880/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2880/comments | https://api.github.com/repos/huggingface/transformers/issues/2880/events | https://github.com/huggingface/transformers/pull/2880 | 566,091,985 | MDExOlB1bGxSZXF1ZXN0Mzc1OTY5MDEx | 2,880 | Transformers と Simpletransfomrersを使ったAlebertでのNERの対応 | {
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主に、modeling_albert.pyにAlbertForTokenClassificationを実装したのと、それと整合性をとるために、その他のコードの変更を行いました。 | {
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https://api.github.com/repos/huggingface/transformers/issues/2879 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2879/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2879/comments | https://api.github.com/repos/huggingface/transformers/issues/2879/events | https://github.com/huggingface/transformers/pull/2879 | 565,996,781 | MDExOlB1bGxSZXF1ZXN0Mzc1ODkyNzc5 | 2,879 | [model_cards] 🇹🇷 Add new (cased) BERTurk model | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2879?src=pr&el=h1) Report\n> Merging [#2879](https://codecov.io/gh/huggingface/transformers/pull/2879?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/6083c1566e261668a5de73cfe484c171ce232812?src=pr&el=desc) will **n... | 1,581 | 1,581 | 1,581 | COLLABORATOR | null | Hi,
this PR adds the model card for the (cased) community-driven 🇹🇷 BERTurk model.
Uncased model is coming soon! | {
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https://api.github.com/repos/huggingface/transformers/issues/2878 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2878/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2878/comments | https://api.github.com/repos/huggingface/transformers/issues/2878/events | https://github.com/huggingface/transformers/issues/2878 | 565,960,150 | MDU6SXNzdWU1NjU5NjAxNTA= | 2,878 | FileNotFoundError when python runs setup.py for sentencepiece | {
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"Sounds like a [sentencepiece](https://github.com/google/sentencepiece) issue?",
"I have an inquiry there as well since just a straight install of sentencepiece gives same results - I was just hoping there might be a way of using the HuggingFace Transformers without sentencepiece (although the name sentencepiece ... | 1,581 | 1,603 | 1,582 | NONE | null | # 🐛 Bug
FileNotFoundError when python runs setup.py for sentencepiece
I am Running Python 3.7, Tensorflow 2.1, Buster
Model I am using (Bert, XLNet ...): Would be using gpt-2 if I can install it...
Language I am using the model on is English
The problem arises when installing using
pip install tra... | {
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https://api.github.com/repos/huggingface/transformers/issues/2877 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2877/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2877/comments | https://api.github.com/repos/huggingface/transformers/issues/2877/events | https://github.com/huggingface/transformers/issues/2877 | 565,946,032 | MDU6SXNzdWU1NjU5NDYwMzI= | 2,877 | Error with run_language_modeling.py training from scratch | {
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"I ran into this with my own dataset. Following some discussion in #1538 I changed truncation to 256.\r\n\r\n> tokenizer.enable_truncation(max_length=256)\r\n\r\nI also had to make sure that the pad token had index 1, as that seems to be hardcoded in roberta.\r\n\r\nThis appears to work, though the previous error h... | 1,581 | 1,589 | 1,589 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Training from scratch
Language I am using the model on (English, Chinese ...): Training from scratch with Esperanto (per tutorial)
The problem arises when using:
* [ ] the official example scripts: (give details below) run_language_model.py
* [x]... | {
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https://api.github.com/repos/huggingface/transformers/issues/2876 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2876/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2876/comments | https://api.github.com/repos/huggingface/transformers/issues/2876/events | https://github.com/huggingface/transformers/pull/2876 | 565,912,816 | MDExOlB1bGxSZXF1ZXN0Mzc1ODMxMzE5 | 2,876 | Create bert-spanish-cased-finedtuned-ner.md | {
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"The file path should be `model_cards/mrm8488/bert-spanish-cased-finedtuned-ner/README.md` @mrm8488 "
] | 1,581 | 1,581 | 1,581 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/2875 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2875/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2875/comments | https://api.github.com/repos/huggingface/transformers/issues/2875/events | https://github.com/huggingface/transformers/pull/2875 | 565,895,256 | MDExOlB1bGxSZXF1ZXN0Mzc1ODE4NTM3 | 2,875 | Update README.md | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2875?src=pr&el=h1) Report\n> Merging [#2875](https://codecov.io/gh/huggingface/transformers/pull/2875?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/73028c5df0c28ca179fbe565482a9c2143787f61?src=pr&el=desc) will **n... | 1,581 | 1,581 | 1,581 | CONTRIBUTOR | null | I trained the model for more epochs so I improved the results. This commit will update the results of the model and add a gif using it with **transformers/pipelines** | {
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https://api.github.com/repos/huggingface/transformers/issues/2874 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2874/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2874/comments | https://api.github.com/repos/huggingface/transformers/issues/2874/events | https://github.com/huggingface/transformers/issues/2874 | 565,872,113 | MDU6SXNzdWU1NjU4NzIxMTM= | 2,874 | How to run TFBERT model in disable_eager_execution() mode | {
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"TFBERT model can only be loaded in tf>2.0 version.And,tf 2.0 onwards,eager_execution() is on by default"
] | 1,581 | 1,582 | 1,582 | NONE | null | How to run `TFBERT `model in `disable_eager_execution()` mode.
If it is possible please let me know, thanks! | {
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https://api.github.com/repos/huggingface/transformers/issues/2873 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2873/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2873/comments | https://api.github.com/repos/huggingface/transformers/issues/2873/events | https://github.com/huggingface/transformers/issues/2873 | 565,860,022 | MDU6SXNzdWU1NjU4NjAwMjI= | 2,873 | how to get "xlnet-base-cased-pytorch_model.bin" original 'last modified' date? | {
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"Just click on 'List all files in model' and you will see the upload date [1].\r\n\r\n[1] https://huggingface.co/xlnet-base-cased"
] | 1,581 | 1,581 | 1,581 | NONE | null | I'd like to test my finetuning on some wikipedia articles that have not been seen by the model.
For that, I can find the date of creation on the wikipedia article, but I'd also like to verify that this is after the 'last modified' date of the model.
How can I get the answer to when was the model parameters' last mod... | {
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https://api.github.com/repos/huggingface/transformers/issues/2872 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2872/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2872/comments | https://api.github.com/repos/huggingface/transformers/issues/2872/events | https://github.com/huggingface/transformers/issues/2872 | 565,858,800 | MDU6SXNzdWU1NjU4NTg4MDA= | 2,872 | Explanation of the results derived from fine tuning | {
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"@gofimofi You might want to look at https://github.com/jessevig/bertviz which is compatible with 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"
] | 1,581 | 1,589 | 1,589 | 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. -->
Hi,
It would be super nice if you can add a visualization util that can show why the model inferred a particular result such that which words of the "se... | {
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https://api.github.com/repos/huggingface/transformers/issues/2871 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2871/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2871/comments | https://api.github.com/repos/huggingface/transformers/issues/2871/events | https://github.com/huggingface/transformers/issues/2871 | 565,857,323 | MDU6SXNzdWU1NjU4NTczMjM= | 2,871 | RoBERTa has a token_type layer (just a cosmetic issue) | {
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"This is something that we're looking at with @LysandreJik and @thomwolf – In the meantime, feel free to open a draft PR.",
"As discussed in the other issues, it would be great if a lot of care is taken in maximising the compatibility between a tokenizer and its corresponding model, as I discussed in https://git... | 1,581 | 1,592 | 1,592 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): RoBERTa
Language I am using the model on (English, Chinese ...): Language-independent
The cosmetic problem:
The fairseq RoBERTa doesn't has a token_type layer:
```
TransformerSentenceEncoder(
(embed_tokens): Embedding(50265, 768, padding_idx=... | {
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https://api.github.com/repos/huggingface/transformers/issues/2870 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2870/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2870/comments | https://api.github.com/repos/huggingface/transformers/issues/2870/events | https://github.com/huggingface/transformers/pull/2870 | 565,848,089 | MDExOlB1bGxSZXF1ZXN0Mzc1Nzg0ODUx | 2,870 | distilberttokenizer.encode_plus() token_type_ids are non-default | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2870?src=pr&el=h1) Report\n> Merging [#2870](https://codecov.io/gh/huggingface/transformers/pull/2870?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/73028c5df0c28ca179fbe565482a9c2143787f61?src=pr&el=desc) will **i... | 1,581 | 1,586 | 1,586 | CONTRIBUTOR | null | DistilBert doesn't use token_type_ids. Therefore the encode_plus() method of the DistilBertTokenizer should generate them per default. This fix sets the default value of return_token_type_ids to False.
Closes #2702 | {
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https://api.github.com/repos/huggingface/transformers/issues/2869 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2869/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2869/comments | https://api.github.com/repos/huggingface/transformers/issues/2869/events | https://github.com/huggingface/transformers/issues/2869 | 565,847,977 | MDU6SXNzdWU1NjU4NDc5Nzc= | 2,869 | ValueError: too many dimensions 'str' | {
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"I suggest to close this topic and keep the discussion over at https://github.com/ThilinaRajapakse/simpletransformers/issues/229."
] | 1,581 | 1,582 | 1,582 | NONE | null | # 🐛 Bug
**To Reproduce**
Steps to reproduce the behavior:
Here is my Colab Notebook you can run to to see the error
https://colab.research.google.com/drive/1ESyf46RNBvrg-7DDQ5l8zhlKZjWGdqUv#scrollTo=MqlsdjFVMmMZ
```
---------------------------------------------------------------------------
ValueError ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2868 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2868/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2868/comments | https://api.github.com/repos/huggingface/transformers/issues/2868/events | https://github.com/huggingface/transformers/issues/2868 | 565,824,248 | MDU6SXNzdWU1NjU4MjQyNDg= | 2,868 | How can I run NER on ALBERT? | {
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"+1 \r\nSame for [run_language_modeling.py](https://github.com/huggingface/transformers/blob/master/examples/run_language_modeling.py)?",
"What do you think about moving the examples to `AutoModels` (in this case `AutoModelForTokenClassification`) @srush @LysandreJik @julien-c ?",
"@thomwolf Indeed, that would ... | 1,581 | 1,589 | 1,589 | NONE | null | I what to run NER on ALBERT, so I checked the [run_ner.py](https://github.com/huggingface/transformers/blob/master/examples/run_ner.py), but it seems like no ALBERT support.
So can I simply import `AlbertTokenizer`, `AlbertForTokenClassification` and
`AlbertConfig` in the script and add them to `MODEL_CLASSES` and `... | {
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https://api.github.com/repos/huggingface/transformers/issues/2867 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2867/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2867/comments | https://api.github.com/repos/huggingface/transformers/issues/2867/events | https://github.com/huggingface/transformers/issues/2867 | 565,781,926 | MDU6SXNzdWU1NjU3ODE5MjY= | 2,867 | from_pretrained making internet connection if internet turned on | {
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"I might be mistaken, but it seems that `s3_etag` verifies that the etag of a cached (downloaded) file is the same as the one that is in the S3 bucket, to ensure that you have the right files (in terms of versions, or corruption). If those files are not in the cached folder, they are downloaded.\r\n\r\nSee \r\n\r\n... | 1,581 | 1,671 | 1,582 | NONE | null | I'd like to ask why model.from_pretrained makes ssl connection event though I provide cache_dir? If I turn off the internet everything works just fine.
```
│ └─ 0.726 from_pretrained transformers/tokenization_utils.py:256
│ └─ 0.726 _from_pretrained transformers/tokenization_utils.py:311
│ ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2866 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2866/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2866/comments | https://api.github.com/repos/huggingface/transformers/issues/2866/events | https://github.com/huggingface/transformers/issues/2866 | 565,605,760 | MDU6SXNzdWU1NjU2MDU3NjA= | 2,866 | How to get the matrix that is used to combine output from multiple number of attention heads? | {
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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"
] | 1,581 | 1,588 | 1,588 | NONE | null | Hello,
if I am understanding transformers correctly, right before the feedforward layer, output of individual attention head are concatenated and multiplied by a matrix **H**, so that the outputs from the multiple number of heads will be combined into one output which will then be an input to the subsequent feedforw... | {
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https://api.github.com/repos/huggingface/transformers/issues/2865 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2865/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2865/comments | https://api.github.com/repos/huggingface/transformers/issues/2865/events | https://github.com/huggingface/transformers/issues/2865 | 565,535,048 | MDU6SXNzdWU1NjU1MzUwNDg= | 2,865 | UserWarning: The number of elements in the out tensor of shape [1] is 1 | {
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"It is likely that your SO question was downvoted because it is a lot of unreproducible code, and not a lot of explanation. In other words: when someone reads your qusetion, it is almost impossible to answer because we cannot try your code ourselves. Try reducing it to a minimal, verifiable, executable example.\r\n... | 1,581 | 1,587 | 1,587 | 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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https://api.github.com/repos/huggingface/transformers/issues/2864 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2864/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2864/comments | https://api.github.com/repos/huggingface/transformers/issues/2864/events | https://github.com/huggingface/transformers/pull/2864 | 565,491,325 | MDExOlB1bGxSZXF1ZXN0Mzc1NTE5Mjk1 | 2,864 | Update model card: new performance chart | {
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"looks good!",
"On fire! :D",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2864?src=pr&el=h1) Report\n> Merging [#2864](https://codecov.io/gh/huggingface/transformers/pull/2864?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/92e974196fc35eb826f64808ae82d20... | 1,581 | 1,581 | 1,581 | CONTRIBUTOR | null | We found a bug in our German conll03 data and fixed it. See deepset-ai/FARM#235
We reran the eval scripts on the new data and updated our charts accordingly. | {
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https://api.github.com/repos/huggingface/transformers/issues/2863 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2863/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2863/comments | https://api.github.com/repos/huggingface/transformers/issues/2863/events | https://github.com/huggingface/transformers/issues/2863 | 565,435,647 | MDU6SXNzdWU1NjU0MzU2NDc= | 2,863 | What does the variable 'present' represent? | {
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does the variable 'present' shown in [this](https://github.com/huggingface/transformers/blob/4e69104a1fba717026d6909d06288788e684c749/src/transformers/modeling_gpt2.py#L187) line of Hugging Face GPT-2 code represent final output of a single attention-head? (i.e. **not** the final output of the _output head_ ,... | {
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https://api.github.com/repos/huggingface/transformers/issues/2862 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2862/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2862/comments | https://api.github.com/repos/huggingface/transformers/issues/2862/events | https://github.com/huggingface/transformers/issues/2862 | 565,431,349 | MDU6SXNzdWU1NjU0MzEzNDk= | 2,862 | PreTrainedTokenizer returns potentially incorrect attention mask | {
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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"
] | 1,581 | 1,587 | 1,587 | NONE | null | # 🐛 Bug
## Information
When deriving the `attention_mask` `PreTrainedTokenizer` makes an assumption in `prepare_for_model` that the input hasn't been padded prior, this assumption can be false. For example, in the case where one precomputes padded token ids for sentences separately and then uses `BertTokenizer.e... | {
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https://api.github.com/repos/huggingface/transformers/issues/2861 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2861/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2861/comments | https://api.github.com/repos/huggingface/transformers/issues/2861/events | https://github.com/huggingface/transformers/issues/2861 | 565,400,199 | MDU6SXNzdWU1NjU0MDAxOTk= | 2,861 | DistilBERT distilbert-base-cased failed to load | {
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" Should be fixed with ee5a6856caec83e7f2f305418f3199b87ea6cc2d. I can execute your code without an error with the latest version from github.",
"> Should be fixed with [ee5a685](https://github.com/huggingface/transformers/commit/ee5a6856caec83e7f2f305418f3199b87ea6cc2d). I can execute your code without an error ... | 1,581 | 1,589 | 1,581 | NONE | null | **Issue**
DistilBERT **distilbert-base-cased** failed to load. _Please note, 'distilbert-base-uncased' works perfectly fine._
**Error Message**
OSError: Model name 'distilbert-base-cased' was not found in tokenizers model name list (distilbert-base-uncased, distilbert-base-uncased-distilled-squad, distilbert-base... | {
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https://api.github.com/repos/huggingface/transformers/issues/2860 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2860/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2860/comments | https://api.github.com/repos/huggingface/transformers/issues/2860/events | https://github.com/huggingface/transformers/issues/2860 | 565,279,628 | MDU6SXNzdWU1NjUyNzk2Mjg= | 2,860 | Post-padding affects the Bert embedding output | {
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"Hi, please look into the documentation of the [attention mask](https://huggingface.co/transformers/glossary.html#attention-mask).",
"Actually, it was a valid question. The output will be numerically different for sure since there are extra positions to attend and even if those are paddings -> there is a differen... | 1,581 | 1,617 | 1,582 | NONE | null | # 🐛 Bug
## Information
Model: BertModel
Language: English
The problem arises when using:
```
# Load model
from transformers import *
import torch
model_class = BertModel
tokenizer_class = BertTokenizer
pretrained_weights = 'bert-base-uncased'
tokenizer = tokenizer_class.from_pretrained(pretrained_w... | {
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https://api.github.com/repos/huggingface/transformers/issues/2859 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2859/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2859/comments | https://api.github.com/repos/huggingface/transformers/issues/2859/events | https://github.com/huggingface/transformers/pull/2859 | 565,253,320 | MDExOlB1bGxSZXF1ZXN0Mzc1MzI5ODM4 | 2,859 | Added model card for bert-base-multilingual-uncased-sentiment | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2859?src=pr&el=h1) Report\n> Merging [#2859](https://codecov.io/gh/huggingface/transformers/pull/2859?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/925a13ced1e155ea7e55e14e177a7b5ae7ad174c?src=pr&el=desc) will **n... | 1,581 | 1,581 | 1,581 | CONTRIBUTOR | null | Added the model card for nlptown/bert-base-multilingual-uncased-sentiment | {
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"Hi @ARDUJS can you update your issue title to something more descriptive? Thanks!",
"Should be correct -> 80% masked, that means 20% is left. Using this 20% in 50 % the random word is used, 50% original token is kept. So both random word and original has an overall prob. of 10%.\r\n\r\nOriginal BERT is using the... | 1,581 | 1,582 | 1,582 | NONE | null | ERROR: type should be string, got "https://github.com/huggingface/transformers/blob/master/examples/run_language_modeling.py\r\nin 225 row\r\n\r\n\r\n\r\n# 10% of the time, we replace masked input tokens with random word\r\nbut write 0.5 \r\nis ok?" | {
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https://api.github.com/repos/huggingface/transformers/issues/2857 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2857/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2857/comments | https://api.github.com/repos/huggingface/transformers/issues/2857/events | https://github.com/huggingface/transformers/pull/2857 | 565,211,701 | MDExOlB1bGxSZXF1ZXN0Mzc1Mjk2NDc5 | 2,857 | Fix typos | {
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https://api.github.com/repos/huggingface/transformers/issues/2855 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2855/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2855/comments | https://api.github.com/repos/huggingface/transformers/issues/2855/events | https://github.com/huggingface/transformers/pull/2855 | 565,104,179 | MDExOlB1bGxSZXF1ZXN0Mzc1MjExNDY5 | 2,855 | Fix typo | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2855?src=pr&el=h1) Report\n> Merging [#2855](https://codecov.io/gh/huggingface/transformers/pull/2855?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/925a13ced1e155ea7e55e14e177a7b5ae7ad174c?src=pr&el=desc) will **n... | 1,581 | 1,581 | 1,581 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/2854 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2854/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2854/comments | https://api.github.com/repos/huggingface/transformers/issues/2854/events | https://github.com/huggingface/transformers/pull/2854 | 565,088,898 | MDExOlB1bGxSZXF1ZXN0Mzc1MjAwMzQ4 | 2,854 | Create model card for 'distill-bert-base-spanish-wwm-cased-finetuned-spa-squad2-es' | {
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"Thanks!",
"Welcome, Julien!\nThis one won't be my last contribution! :)\nNot so easy :P\n\nEl vie., 14 feb. 2020 5:05, Julien Chaumond <notifications@github.com>\nescribió:\n\n> Thanks!\n>\n> —\n> You are receiving this because you authored the thread.\n> Reply to this email directly, view it on GitHub\n> <https... | 1,581 | 1,581 | 1,581 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/2852 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2852/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2852/comments | https://api.github.com/repos/huggingface/transformers/issues/2852/events | https://github.com/huggingface/transformers/pull/2852 | 565,037,055 | MDExOlB1bGxSZXF1ZXN0Mzc1MTYwMTAz | 2,852 | Update with additional information | {
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"Thanks for sharing!\r\n\r\nHow did you pre-train this model (infrastructure, number of epochs, etc.)?\r\nDo you have eval results on downstream tasks?\r\n\r\nAlso you can add a \r\n```\r\n---\r\nlanguage: greek\r\n---\r\n```\r\ntag to the top of the file\r\n\r\nI'll merge this in the meantime, thanks for sharing!... | 1,581 | 1,581 | 1,581 | NONE | null | {
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https://api.github.com/repos/huggingface/transformers/issues/2850 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2850/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2850/comments | https://api.github.com/repos/huggingface/transformers/issues/2850/events | https://github.com/huggingface/transformers/pull/2850 | 564,966,427 | MDExOlB1bGxSZXF1ZXN0Mzc1MTAxNDY4 | 2,850 | Adding usage examples for common tasks | {
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https://api.github.com/repos/huggingface/transformers/issues/2849 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2849/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2849/comments | https://api.github.com/repos/huggingface/transformers/issues/2849/events | https://github.com/huggingface/transformers/issues/2849 | 564,931,431 | MDU6SXNzdWU1NjQ5MzE0MzE= | 2,849 | PreTrainedEncoderDecoder does not work for LSTM | {
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"I put this as a bug because the code as-is does not hint that Model2LSTM does not work. \r\nhttps://github.com/huggingface/transformers/blob/90ab15cb7a8fcf8bf58c05453ddf1aa6a4fa00c1/src/transformers/modeling_encoder_decoder.py\r\nIt would be great to say that LSTM is not currently supported there. ",
"Indeed, my... | 1,581 | 1,582 | 1,582 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...):
If we want to have a BERT-based encoder and LSTM encoder, that is not currently possible with the current huggingface implementation, mostly because torch.nn.LSTM does not contain a config class variable.
## Stack Trace
File "/beegfs/yp913/anaco... | {
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https://api.github.com/repos/huggingface/transformers/issues/2848 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2848/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2848/comments | https://api.github.com/repos/huggingface/transformers/issues/2848/events | https://github.com/huggingface/transformers/issues/2848 | 564,885,131 | MDU6SXNzdWU1NjQ4ODUxMzE= | 2,848 | Add `masked_lm_labels` argument to `TFAlbertForMaskedLM` | {
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"Hi! This feature would be great to have.\r\n\r\nI'm curious how `TFBertMaskedLM` (and the like) are supposed to be used with the keras `fit()` functionality?\r\n\r\nIt seems like one is supposed to loop through the training data and calculate the cross-entropy loss for each batch (#2926). I see there was related d... | 1,581 | 1,591 | 1,591 | CONTRIBUTOR | null | # 🚀 Feature request
The PyTorch `AlbertForMaskedLM` model has support for the `masked_lm_labels` parameter, while `TFAlbertForMaskedLM` does not. I'd like to bring feature parity.
It looks like a similar feature is also missing for `TFBertForMaskedLM`, `TFRobertaForMaskedLM`, `TFDistilBertForMaskedLM`. I'd be ha... | {
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https://api.github.com/repos/huggingface/transformers/issues/2847 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2847/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2847/comments | https://api.github.com/repos/huggingface/transformers/issues/2847/events | https://github.com/huggingface/transformers/issues/2847 | 564,777,598 | MDU6SXNzdWU1NjQ3Nzc1OTg= | 2,847 | BART/T5 seq2seq example | {
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"We are hard at work on this! I'd estimate 6 weeks out.",
"Looking forward to this for the T5 model :)",
"@sshleifer any updates? ",
"The example doesn't seem to show training/fine-tuning, only evaluation of already fine-tuned models.",
"@sshleifer Hello, any updates for training/fine-tuning on text generat... | 1,581 | 1,587 | 1,583 | NONE | null | # 🚀 Feature request
Can we have a seq2seq example with training/fine-tuning and generation for BART/T5 models? | {
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https://api.github.com/repos/huggingface/transformers/issues/2846 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2846/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2846/comments | https://api.github.com/repos/huggingface/transformers/issues/2846/events | https://github.com/huggingface/transformers/issues/2846 | 564,768,880 | MDU6SXNzdWU1NjQ3Njg4ODA= | 2,846 | Error reported when running ''run_language_modeling.py" file | {
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"Hi, this is probably due to a version mismatch. Can you update your repository to be on the same version than the script's ? \r\n\r\nIf it's `run_language_modeling` (was `run_lm_finetuning` up until very recently), that would be version 2.4.1 (safe, but the script may have evolved a bit since the release 13 days a... | 1,581 | 1,587 | 1,587 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert and RoBerta):
Language I am using the model on (English).
The problem arises when using:
* [ ] the official example scripts: (give details below)
I followed the tutorial of how to fine tuning the Bert model on own corpus data, and used recommended corpus 'wik... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2845?src=pr&el=h1) Report\n> Merging [#2845](https://codecov.io/gh/huggingface/transformers/pull/2845?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ef74b0f07a190f19c69abc0732ea955e8dd7330f?src=pr&el=desc) will **d... | 1,581 | 1,651 | 1,582 | CONTRIBUTOR | null | Reasoning: While we diagnose the problem, better to keep circleci from randomly failing. | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2844?src=pr&el=h1) Report\n> Merging [#2844](https://codecov.io/gh/huggingface/transformers/pull/2844?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f54a5bd37f99e3933a396836cb0be0b5a497c077?src=pr&el=desc) will **n... | 1,581 | 1,582 | 1,581 | CONTRIBUTOR | null | @LysandreJik can you help me test this? | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2843?src=pr&el=h1) Report\n> Merging [#2843](https://codecov.io/gh/huggingface/transformers/pull/2843?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/21da895013a95e60df645b7d6b95f4a38f604759?src=pr&el=desc) will **n... | 1,581 | 1,583 | 1,581 | CONTRIBUTOR | null | This PR adds a model card for [severinsimmler/literary-german-bert](https://huggingface.co/severinsimmler/literary-german-bert), a domain-adapted and fine-tuned BERT for named entity recognition in German literary texts. | {
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"It is pretty easy to add the code yourself since RobertaForQuestionAnswering is already implemented and XLMRobertaForQuestionAnswering is just a wrapper around it. ",
"Thank you for your answering.\r\n\r\nI got your mention\r\n\r\nI have question one more\r\n\r\nIs it possible to learn XLM-Roberta data to Robert... | 1,581 | 1,582 | 1,582 | NONE | null | I will study squad of multilingual.
I found that question answer package did include in run_squad.py.
I wanna release that package
Are you plan to release XLMRobertaForQuestionAnwering?
please let me know. | {
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"Hi, could you please provide all the information required in the template so that we may help you? Namely which version of `transformers`, python and PyTorch are you using?\r\n\r\nYou seem to be using `pytorch-pretrained-BERT`, which is a very old version of this repository. Have you tried using the newer `transfo... | 1,581 | 1,631 | 1,581 | NONE | null | Hi , thank you for developing well-made pytorch version of BERT !
I am new to NLP area and have problem while coding like this:
```python
tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
```
The error discription is below:
```
INFO:pytorch_pretrained_bert.file_utils:https://s3.amazonaws.com/mod... | {
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https://api.github.com/repos/huggingface/transformers/issues/2840 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2840/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2840/comments | https://api.github.com/repos/huggingface/transformers/issues/2840/events | https://github.com/huggingface/transformers/pull/2840 | 564,591,633 | MDExOlB1bGxSZXF1ZXN0Mzc0NzkzMTIx | 2,840 | [WIP] Add patience argument to run_language_modeling script | {
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"Sounds great! I'll go ahead and fix the code quality check.",
"Since `run_langauge_modeling.py` now uses the `Trainer` class, I'll likely create a new PR that adds patience to `Trainer`."
] | 1,581 | 1,588 | 1,588 | NONE | null | # Summary
Often, we want to stop training if loss does not improve for a number of epochs. This PR adds a "patience" argument, which is a limit on the number of times we can get a non-improving eval loss before stopping training early.
It is implemented by other NLP frameworks, such as AllenNLP (see [trainer.py](ht... | {
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https://api.github.com/repos/huggingface/transformers/issues/2839 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2839/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2839/comments | https://api.github.com/repos/huggingface/transformers/issues/2839/events | https://github.com/huggingface/transformers/issues/2839 | 564,589,285 | MDU6SXNzdWU1NjQ1ODkyODU= | 2,839 | Fine-tuning the model using classification tasks | {
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"Hi, the `run_glue` example script was designed to showcase how to fine-tune any model to a classification task. It showcases many things you maybe don't need, such as data-parallel, checkpointing, half-precision, etc. You can adapt this script or study the training loop to create your own.",
"This issue has been... | 1,581 | 1,587 | 1,587 | NONE | null | Hello All,
Could anyone tell how can I fine-tune the language model using classification tasks, however not using any GLUE data, as I have my own custom dataset?
Is there any solution and/or method to do the classification using a custom dataset? | {
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https://api.github.com/repos/huggingface/transformers/issues/2838 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2838/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2838/comments | https://api.github.com/repos/huggingface/transformers/issues/2838/events | https://github.com/huggingface/transformers/issues/2838 | 564,380,853 | MDU6SXNzdWU1NjQzODA4NTM= | 2,838 | A small model for CTRL | {
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"cc'ing @keskarnitish on this issue just in case!",
"Thank you, @julien-c.",
"hi, any update on this?",
"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"
] | 1,581 | 1,588 | 1,588 | NONE | null | # 🚀 Feature request
A smaller version of the pre-trained model CTRL, related to the stack overflow question;
[https://stackoverflow.com/questions/60142937/huggingface-transformers-for-text-generation-with-ctrl]
## Motivation
I've been trying to generate text using CTRL and I run to a memory insufficiency, si... | {
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https://api.github.com/repos/huggingface/transformers/issues/2837 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2837/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2837/comments | https://api.github.com/repos/huggingface/transformers/issues/2837/events | https://github.com/huggingface/transformers/issues/2837 | 564,370,795 | MDU6SXNzdWU1NjQzNzA3OTU= | 2,837 | Pretrained TFAlbertForMaskedLM returns seemingly random token predictions | {
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"Hi, thank you for opening an issue, there was indeed an error with the way the `TFAlbertModel` was implemented! It was fixed with https://github.com/huggingface/transformers/commit/1abd53b1aa2f15953bbbbbfefda885d1d9c9d94b.\r\n\r\nEven with the fix, the sequence `I <mask> you` is hard for ALBERT, but using your sam... | 1,581 | 1,587 | 1,587 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): BERT, ALBERT
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... | {
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https://api.github.com/repos/huggingface/transformers/issues/2836 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2836/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2836/comments | https://api.github.com/repos/huggingface/transformers/issues/2836/events | https://github.com/huggingface/transformers/issues/2836 | 564,354,398 | MDU6SXNzdWU1NjQzNTQzOTg= | 2,836 | Getting value of [UNK] labels | {
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"Did you try using the `add_tokens` method on the tokenizer alongside the `resize_token_embeddings` on the model, to add your tokens to the vocabulary? The won't be marked as `[UNK]` this way, but will instead receive brand new embeddings (which need to be trained).",
"This issue has been automatically marked as ... | 1,581 | 1,618 | 1,587 | 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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https://api.github.com/repos/huggingface/transformers/issues/2835 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2835/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2835/comments | https://api.github.com/repos/huggingface/transformers/issues/2835/events | https://github.com/huggingface/transformers/issues/2835 | 564,323,931 | MDU6SXNzdWU1NjQzMjM5MzE= | 2,835 | Failing slow RobertaModelIntegrationTest | {
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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"
] | 1,581 | 1,587 | 1,587 | CONTRIBUTOR | null | ```
RUN_SLOW=1 pytest tests/test_modeling_roberta.py::RobertaModelIntegrationTest::test_inference_masked_lm
```
Have not investigated at all, but wanted to record.
Traceback:
```
self = <tests.test_modeling_roberta.RobertaModelIntegrationTest testMethod=test_inference_masked_lm>
@slow
def test_infer... | {
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https://api.github.com/repos/huggingface/transformers/issues/2834 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2834/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2834/comments | https://api.github.com/repos/huggingface/transformers/issues/2834/events | https://github.com/huggingface/transformers/issues/2834 | 564,323,533 | MDU6SXNzdWU1NjQzMjM1MzM= | 2,834 | Failing slow AutoModelTest/BertForPreTraining | {
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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"
] | 1,581 | 1,587 | 1,587 | CONTRIBUTOR | null | ```
RUN_SLOW=1 pytest tests/test_modeling_auto.py::AutoModelTest::test_model_for_pretraining_from_pretrained
```
Have not investigated at all, but wanted to record since the slow test failures are evasive :)
Clues:
model: `transformers.modeling_bert.BertForPreTraining`
```
loading_info = {'missing_keys': ['c... | {
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https://api.github.com/repos/huggingface/transformers/issues/2833 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2833/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2833/comments | https://api.github.com/repos/huggingface/transformers/issues/2833/events | https://github.com/huggingface/transformers/pull/2833 | 564,314,638 | MDExOlB1bGxSZXF1ZXN0Mzc0NTY5NjM0 | 2,833 | add model_card flaubert-base-uncased-squad | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2833?src=pr&el=h1) Report\n> Merging [#2833](https://codecov.io/gh/huggingface/transformers/pull/2833?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f54a5bd37f99e3933a396836cb0be0b5a497c077?src=pr&el=desc) will **n... | 1,581 | 1,581 | 1,581 | CONTRIBUTOR | null | A baseline model for question-answering in french ([flaubert](https://github.com/getalp/Flaubert) model fine-tuned on [french-translated SQuAD 1.1 dataset](https://github.com/Alikabbadj/French-SQuAD))
Small error when trying it with the pipeline though:
```python-traceback
>>> nlp = pipeline('question-answering'... | {
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https://api.github.com/repos/huggingface/transformers/issues/2832 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2832/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2832/comments | https://api.github.com/repos/huggingface/transformers/issues/2832/events | https://github.com/huggingface/transformers/issues/2832 | 564,287,261 | MDU6SXNzdWU1NjQyODcyNjE= | 2,832 | 'distilbert-base-cased-distilled-squad' was not found error | {
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"Hi! This checkpoint was added six days ago but our latest release was 13 days ago, so you would need to install the repository from source to use that model:\r\n\r\n```\r\npip install git+https://github.com/huggingface/transformers\r\n```\r\n\r\nIt'll be available in a pip install once we do a new release."
] | 1,581 | 1,581 | 1,581 | NONE | null | # 🐛 Bug
## Information
Model I am using: distilbert-base-cased-distilled-squad
The problem arises when using: AutoTokenizer or AutoModelForQuestionAnswering
Steps to reproduce the behavior:
0. make sure you have everything on colab installed and imported
```
!pip install transformers
import torch
fro... | {
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https://api.github.com/repos/huggingface/transformers/issues/2831 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2831/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2831/comments | https://api.github.com/repos/huggingface/transformers/issues/2831/events | https://github.com/huggingface/transformers/issues/2831 | 564,230,995 | MDU6SXNzdWU1NjQyMzA5OTU= | 2,831 | Installation Error - Failed building wheel for tokenizers | {
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"Having the exact same issue on a Linux machine!",
"Environment: macOS Mojave Ver 10.14.6\r\nTried installing both from pip and source. Same issue:\r\n> Successfully built transformers\r\n> Failed to build tokenizers \r\n\r\nResult was that Transformers was not installed (not listed in pip freeze)\r\n\r\nThis how... | 1,581 | 1,706 | 1,594 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): N/A
Language I am using the model on (English, Chinese ...): N/A
The problem arises when using:
* [X] the official example scripts: (give details below)
Problem arises in transformers installation on Microsoft Windows 10 Pro, version 10.0.17763... | {
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https://api.github.com/repos/huggingface/transformers/issues/2830 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2830/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2830/comments | https://api.github.com/repos/huggingface/transformers/issues/2830/events | https://github.com/huggingface/transformers/issues/2830 | 564,185,272 | MDU6SXNzdWU1NjQxODUyNzI= | 2,830 | Reusing states for sequential decoding in BERTForMaskedLM | {
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"That's a cool idea.",
"Closed by #3059 "
] | 1,581 | 1,583 | 1,583 | NONE | null | # 🚀 Feature request
I am using Bert as a decoder (by setting is_decoder=True). However, during sequential decoding, there is no way of reusing the hidden states, so for every word to be generated we need to rerun the model on the ENTIRE decoded sequence, which renders decoding inefficient. Can you add something sim... | {
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https://api.github.com/repos/huggingface/transformers/issues/2829 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2829/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2829/comments | https://api.github.com/repos/huggingface/transformers/issues/2829/events | https://github.com/huggingface/transformers/issues/2829 | 564,152,367 | MDU6SXNzdWU1NjQxNTIzNjc= | 2,829 | BERT generating prediction in 120sec approx using squad 2.0 in prediction.json | {
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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"
] | 1,581 | 1,587 | 1,587 | NONE | null | I am using the below command to predict the question answer using BERT with squad but it taking too long to generate the prediction.json approx 120 sec. I wanna reduce this time to 10secs.
run_squad.py --vocab_file=uncased_L-12_H-768_A-12/vocab.txt --bert_config_file=uncased_L-12_H-768_A-12/bert_config.json --init_c... | {
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https://api.github.com/repos/huggingface/transformers/issues/2828 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2828/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2828/comments | https://api.github.com/repos/huggingface/transformers/issues/2828/events | https://github.com/huggingface/transformers/pull/2828 | 564,106,241 | MDExOlB1bGxSZXF1ZXN0Mzc0Mzk2MDE4 | 2,828 | [WIP] Create a Trainer class to handle TF2 model training | {
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"I'm not 100% sure which ones of those methods need to live on the model vs. in the training framework\r\n\r\nFor instance, over in #2816, @srush is implementing support for `pytorch-lightning`, which over in PyTorch world, handles a lot of those tasks. In PyTorch we wouldn't want to implement these in to the model... | 1,581 | 1,582 | 1,582 | CONTRIBUTOR | null | **EDIT**
Close this PR to create a cleaner, and more on purpose one.
Hello,
I'm opening the pull request I was talking about in the issue #2783. Here the proposed features in this PR:
- [x] add checkpoint manager in order to make a training fault-tolerant
- [x] add custom fit method to take into account the ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2827 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2827/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2827/comments | https://api.github.com/repos/huggingface/transformers/issues/2827/events | https://github.com/huggingface/transformers/issues/2827 | 564,095,688 | MDU6SXNzdWU1NjQwOTU2ODg= | 2,827 | OOM risk in RobertaTokenizer/GPT2Tokenizer | {
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"If lru_cache is used, the max size couldn't be configured at runtime or disabled completely. Trying to go around this with anonymous functions will cause pickling problems and is generally ugly.\r\n\r\nA more elegant and straightforward solution is to use a custom cache with ordered dict and a max size checked at ... | 1,581 | 1,587 | 1,587 | NONE | null | # 🐛 Bug
## Information
Model I am using: Roberta (_roberta-base_)
Language I am using the model on: English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts
I am using a modified version of the [examples/distillation/scripts/binariz... | {
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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"
] | 1,581 | 1,587 | 1,587 | NONE | null | I was trying to generate text and also reading the code to understand how it is working.
I found that, after providing some text as context (first iteration), it goes through the transformer and the output of the transformer (`output[0] `of `GPT2Model` ) is for each token position there is a vector. To my understandi... | {
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https://api.github.com/repos/huggingface/transformers/issues/2825 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2825/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2825/comments | https://api.github.com/repos/huggingface/transformers/issues/2825/events | https://github.com/huggingface/transformers/issues/2825 | 564,027,827 | MDU6SXNzdWU1NjQwMjc4Mjc= | 2,825 | binarized_data.py in distillation uses incorrect type casting | {
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"Good catch @Rexhaif \r\nI'll fix that. Thanks for pointing that out.\r\nVictor"
] | 1,581 | 1,581 | 1,581 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): possibly affected model is DistilBert(distilbert-base-multilingual-cased)
Language I am using the model on (English, Chinese ...): multiple
The problem arises when using:
* [x] the official example scripts: (give details below)
The tasks I am w... | {
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https://api.github.com/repos/huggingface/transformers/issues/2824 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2824/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2824/comments | https://api.github.com/repos/huggingface/transformers/issues/2824/events | https://github.com/huggingface/transformers/issues/2824 | 563,996,039 | MDU6SXNzdWU1NjM5OTYwMzk= | 2,824 | GPT-2 language model: multiplying decoder-transformer output with token embedding or another weight matrix | {
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"Hi, the input embeddings are tied to the output embeddings -> The `lm_head` attribute essentially shares its weights with the embedding layer. Passing the output of the transformer through that layer is the same as multiplying this output (the hidden states) with the token embedding matrix.",
"@LysandreJik Where... | 1,581 | 1,594 | 1,581 | NONE | null | I was reading the code of GPT2 language model. The transformation of hidden states to the probability distribution over the vocabulary has done in the following line:
`lm_logits = self.lm_head(hidden_states)`
Here,
`self.lm_head = nn.Linear(config.n_embd, config.vocab_size, bias=False)`
However, In the original... | {
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https://api.github.com/repos/huggingface/transformers/issues/2822 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2822/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2822/comments | https://api.github.com/repos/huggingface/transformers/issues/2822/events | https://github.com/huggingface/transformers/issues/2822 | 563,939,822 | MDU6SXNzdWU1NjM5Mzk4MjI= | 2,822 | bugs in xlnet XLNetLMHeadModel | {
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"I took a closer look into the XLNet model. As I understand the [paper](https://arxiv.org/pdf/1906.08237.pdf) and how the input/target lm training data is created in the code base (look [here](https://github.com/zihangdai/xlnet/blob/bbaa3a6fa0b3a2ee694e8cf66167434f9eca9660/data_utils.py#L616)), the language modelli... | 1,581 | 1,582 | 1,582 | NONE | null | # 🐛 Bug
## Information
Model I am using XLNet :
Language I am using the model on English :
The problem arises when using:
* [True ] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: ... | {
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"what is your GPU?",
"> what is your GPU?\r\n\r\nTITAN Xp\r\n",
"If I'm not mistaken the Titan XP has 12GB of VRAM? From my tests training RoBERTa-large with a batch size of 1 already requires 10GB of VRAM, so your GPU memory should be filled quickly. It is surprising that it crashes later though. Could you try... | 1,581 | 1,581 | 1,581 | CONTRIBUTOR | null | # 🐛 Bug
CUDA OOM in run_language_modeling.py after many steps.
## Information
It seems strange to get them so late in the training procedure.
Model I am using (Bert, XLNet ...):
roberta-large
Language I am using the model on (English, Chinese ...):
English
The problem arises when using:
* [ ] the official exa... | {
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https://api.github.com/repos/huggingface/transformers/issues/2820 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2820/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2820/comments | https://api.github.com/repos/huggingface/transformers/issues/2820/events | https://github.com/huggingface/transformers/issues/2820 | 563,815,966 | MDU6SXNzdWU1NjM4MTU5NjY= | 2,820 | ImportError: cannot import name 'GradientAccumulator' | {
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"Hi,\r\nanyone found workaround for this issue?\r\nThanks",
"This shouldn't happen with transformers v2.4.1 and tensorflow >= 2.0.0.\r\n\r\nI can't replicate this issue with the versions you mentioned.\r\n\r\nWould you mind telling me what gets printed out when you run the following snippet?\r\n\r\n```py\r\nfrom ... | 1,581 | 1,586 | 1,586 | NONE | null | transformers==2.4.1;
tensoflow==2.1.0;
torch==1.4.0;
when i start with follow code get some error and i didn't have tensoflow-gpu.
**code**
---------------------------------------------------------------------------
from transformers import (
TF2_WEIGHTS_NAME,
BertConfig,
BertTokenizer,
Dist... | {
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https://api.github.com/repos/huggingface/transformers/issues/2819 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2819/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2819/comments | https://api.github.com/repos/huggingface/transformers/issues/2819/events | https://github.com/huggingface/transformers/pull/2819 | 563,652,448 | MDExOlB1bGxSZXF1ZXN0Mzc0MDIyMjk2 | 2,819 | Create card for model bert-base-spanish-wwm-cased-finetuned-spa-squad2-es.md | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2819?src=pr&el=h1) Report\n> Merging [#2819](https://codecov.io/gh/huggingface/transformers/pull/2819?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e0b6247cf749c5a6c7b9543f6c16935b58370ce0?src=pr&el=desc) will **d... | 1,581 | 1,581 | 1,581 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/2818 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2818/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2818/comments | https://api.github.com/repos/huggingface/transformers/issues/2818/events | https://github.com/huggingface/transformers/issues/2818 | 563,633,876 | MDU6SXNzdWU1NjM2MzM4NzY= | 2,818 | Albert multilingual | {
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"As far as I know (from following https://github.com/google-research/ALBERT/issues/5 and https://github.com/google-research/ALBERT/issues/91), ALBERT multilingual is not yet released.\r\n\r\nWe'll make sure to support it once it's released.",
"https://github.com/google-research/ALBERT/pull/152/files\r\n\r\n😱😱😱... | 1,581 | 1,587 | 1,587 | NONE | null | # 🚀 Feature request
Provide multilingual pre-trained albert model.
## Motivation
Albert is a light weighted bert. It would be nice if it has the multilingual version.
## Your contribution
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https://api.github.com/repos/huggingface/transformers/issues/2817 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2817/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2817/comments | https://api.github.com/repos/huggingface/transformers/issues/2817/events | https://github.com/huggingface/transformers/issues/2817 | 563,519,994 | MDU6SXNzdWU1NjM1MTk5OTQ= | 2,817 | GPT2LMHeadModel with variable length batch input | {
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"Have you tried concatenating the sequences into one long string and using a separator token without changing any of the code? You can then use a moving window of 1024 to train the model. You can make each step of the window start after an <|endoftext|> to ensure the primary sequence is not truncated.\r\n\r\nYou ca... | 1,581 | 1,587 | 1,587 | NONE | null | I'm trying to repurpose the GPT2LMHeadModel for a seq2seq-like task, where I have an input prompt sequence of length L and I'm trying to ask the model to output a sequence to match a target sequence/sentence.
For a single input-output pair, I simply change the original code of
`shift_logits = lm_logits[..., :-1, :].... | {
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https://api.github.com/repos/huggingface/transformers/issues/2816 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2816/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2816/comments | https://api.github.com/repos/huggingface/transformers/issues/2816/events | https://github.com/huggingface/transformers/pull/2816 | 563,446,753 | MDExOlB1bGxSZXF1ZXN0MzczODU1OTE1 | 2,816 | Proposal: Update examples to utilize a new format. | {
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"Hi @srush, thanks for this PR :heart: Can't wait to test it!\r\n\r\nOne suggestion/RFC: could we rename it to something like `token_classification` instead of `ner`. I know PoS tagging is not really covered in recent papers, but I always test new models for this task with the \"identical\" implementation 😅 This ... | 1,581 | 1,582 | 1,582 | CONTRIBUTOR | null | This PR creates a new example coding style for the pytorch code.
* Uses pytorch-lightning for the underlying training.
* Separates out the base transformer loading from the individual training.
* Moves each individual example to its own directory.
* Move the code in the readme to bash scripts.
The only tw... | {
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https://api.github.com/repos/huggingface/transformers/issues/2815 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2815/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2815/comments | https://api.github.com/repos/huggingface/transformers/issues/2815/events | https://github.com/huggingface/transformers/pull/2815 | 563,432,757 | MDExOlB1bGxSZXF1ZXN0MzczODQ0NDA3 | 2,815 | Add more specific testing advice to Contributing.md | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2815?src=pr&el=h1) Report\n> Merging [#2815](https://codecov.io/gh/huggingface/transformers/pull/2815?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/bed38d3afec99ce99ef8610337cb279a8fb25033?src=pr&el=desc) will **i... | 1,581 | 1,581 | 1,581 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/2814 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2814/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2814/comments | https://api.github.com/repos/huggingface/transformers/issues/2814/events | https://github.com/huggingface/transformers/issues/2814 | 563,309,030 | MDU6SXNzdWU1NjMzMDkwMzA= | 2,814 | Repository with recipes how to pretrain model from scratch on my own data | {
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"Hi @ksopyla that's a great – but very broad – question.\r\n\r\nWe just wrote a blogpost that might be helpful: https://huggingface.co/blog/how-to-train\r\n\r\nThe post itself is on GitHub so feel free to improve/edit it too.",
"Thank you @julien-c. It will help to add new models to transformer model repository :... | 1,581 | 1,607 | 1,607 | NONE | null | # 🚀 Feature request
It would very useful to have documentation on how to train different models, not necessarily with the use of transformers, but with use external libs (like original BERT, fairseq, etc)
Maybe another repository with readmes or docs with recipes from those who already pretrain their model in ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2813 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2813/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2813/comments | https://api.github.com/repos/huggingface/transformers/issues/2813/events | https://github.com/huggingface/transformers/issues/2813 | 563,283,501 | MDU6SXNzdWU1NjMyODM1MDE= | 2,813 | PreTrainedModel.generate do_sample default argument is wrong in the documentation | {
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"In the documentation for [version 2.4.1/2.4.0](https://huggingface.co/transformers/v2.4.0/main_classes/model.html#transformers.PreTrainedModel.generate), it does indicate it is `False` by default. In the [master documentation](https://huggingface.co/transformers/main_classes/model.html#transformers.PreTrainedModel... | 1,581 | 1,581 | 1,581 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): GPT2LMHeadModel
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [X] my own modified scripts: (give details below)
The tasks I am working... | {
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