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https://api.github.com/repos/huggingface/transformers/issues/4012 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4012/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4012/comments | https://api.github.com/repos/huggingface/transformers/issues/4012/events | https://github.com/huggingface/transformers/issues/4012 | 607,510,007 | MDU6SXNzdWU2MDc1MTAwMDc= | 4,012 | Attribute error while using run_language_modeling.py with Transformer-XL | {
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"Hey, sorry, it's been a while, but this was fixed in #4759 since."
] | 1,587 | 1,592 | 1,592 | NONE | null | python3 /home/username/.local/lib/python3.7/site-packages/transformers/transformers/examples/run_language_modeling.py \
--output_dir=_outpath_
--model_type=Transformer-XL\
--model_name_or_path=transfo-xl-wt103 \
--do_train \
--train_data_file=_pathtodataset_
--per_gpu_train_batch_size=1\
... | {
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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"
] | 1,587 | 1,593 | 1,593 | NONE | null | Hi,
It would be nice if you wrote some minimum requirements in all of your models.
Like the size of the GPU (or the number of GPUs) for a batch size of 1 (or n_gpu).
This would make it really helpful for trying new staff.
For example what are the requirements of re-training or generating with CTRL?
Thanks in a... | {
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https://api.github.com/repos/huggingface/transformers/issues/4010 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4010/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4010/comments | https://api.github.com/repos/huggingface/transformers/issues/4010/events | https://github.com/huggingface/transformers/issues/4010 | 607,397,798 | MDU6SXNzdWU2MDczOTc3OTg= | 4,010 | fairseq-preprocess, Why are the number of rows in src and trg different? | {
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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",
"have you fixed this problem?"
] | 1,587 | 1,680 | 1,593 | 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/4009 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4009/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4009/comments | https://api.github.com/repos/huggingface/transformers/issues/4009/events | https://github.com/huggingface/transformers/pull/4009 | 607,350,919 | MDExOlB1bGxSZXF1ZXN0NDA5MzQxOTU3 | 4,009 | Implemented lazy line-by-line text data set loading for LM example script | {
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"Used this for training a model, worked great! Would love to see this integrated",
"@GCHQResearcher92457 @BramVanroy Does it work for you if we tweak the PR on your fork's branch so that we can remove the force_pad_token option and update a few things?\r\n\r\nPS: Sorry about the super long review time:)",
"> @G... | 1,587 | 1,605 | 1,605 | NONE | null | See PR #3388. Master changed substantially, requiring relocation of code into previously untouched files etc. Instead, here is a new PR using the same code but refactored to fit in to the new more modular structure of the scripts in `examples`. | {
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https://api.github.com/repos/huggingface/transformers/issues/4008 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4008/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4008/comments | https://api.github.com/repos/huggingface/transformers/issues/4008/events | https://github.com/huggingface/transformers/pull/4008 | 607,348,492 | MDExOlB1bGxSZXF1ZXN0NDA5MzM5OTcw | 4,008 | camembert-base-fquad | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4008?src=pr&el=h1) Report\n> Merging [#4008](https://codecov.io/gh/huggingface/transformers/pull/4008?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/4e817ff41885063e08bb3bcd63e5adfd835b9911&el=desc) will **decrease... | 1,587 | 1,588 | 1,588 | CONTRIBUTOR | null | Model card for illuin release of camembert-base-fquad | {
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https://api.github.com/repos/huggingface/transformers/issues/4007 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4007/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4007/comments | https://api.github.com/repos/huggingface/transformers/issues/4007/events | https://github.com/huggingface/transformers/pull/4007 | 607,343,601 | MDExOlB1bGxSZXF1ZXN0NDA5MzM1OTYz | 4,007 | Create model card | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4007?src=pr&el=h1) Report\n> Merging [#4007](https://codecov.io/gh/huggingface/transformers/pull/4007?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/4e817ff41885063e08bb3bcd63e5adfd835b9911&el=desc) will **decrease... | 1,587 | 1,588 | 1,588 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/4006 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4006/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4006/comments | https://api.github.com/repos/huggingface/transformers/issues/4006/events | https://github.com/huggingface/transformers/pull/4006 | 607,335,940 | MDExOlB1bGxSZXF1ZXN0NDA5MzI5NzY4 | 4,006 | Create model card | {
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"Nice!\r\n\r\n[model page](https://huggingface.co/mrm8488/bert-small-finetuned-typo-detection)",
"I plan to add a Colab to show the whole process: download, preprocess, train, eval and upload to HF"
] | 1,587 | 1,588 | 1,588 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/4005 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4005/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4005/comments | https://api.github.com/repos/huggingface/transformers/issues/4005/events | https://github.com/huggingface/transformers/issues/4005 | 607,315,954 | MDU6SXNzdWU2MDczMTU5NTQ= | 4,005 | Fast Tokenizers do not work when `return_offsets_mapping=True, return_tensors="pt"` | {
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"@GuillemGSubies I think this works with the lastest `master` version of Transformers and using `tokenizers` in version *0.7.0*:\r\n\r\n```python\r\nfrom transformers import BertTokenizerFast\r\nfast = BertTokenizerFast.from_pretrained(\"bert-base-cased\")\r\nfast.encode_plus(\"Hello I am tokenizing\", return_offse... | 1,587 | 1,588 | 1,588 | CONTRIBUTOR | null | # 🐛 Bug
## Information
When I try the following code:
```python
from transformers import BertTokenizerFast
fast = BertTokenizerFast.from_pretrained("bert-base-cased")
fast.encode_plus("Hello I am tokenizing", return_offsets_mapping=True)
```
It works as intended.
However, if I try:
```python
fro... | {
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https://api.github.com/repos/huggingface/transformers/issues/4004 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4004/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4004/comments | https://api.github.com/repos/huggingface/transformers/issues/4004/events | https://github.com/huggingface/transformers/issues/4004 | 607,260,981 | MDU6SXNzdWU2MDcyNjA5ODE= | 4,004 | ALBERT with Masked Language Model Input Processing from SavedModel | {
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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",
"Hi! I have the similar problem too. Have you fixed it? If so, how?"
] | 1,587 | 1,594 | 1,593 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): ALBERT
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)
```
input_ids=tf.convert_to_tens... | {
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https://api.github.com/repos/huggingface/transformers/issues/4003 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4003/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4003/comments | https://api.github.com/repos/huggingface/transformers/issues/4003/events | https://github.com/huggingface/transformers/issues/4003 | 607,243,113 | MDU6SXNzdWU2MDcyNDMxMTM= | 4,003 | Maybe it is a bug for Roberta vocab file. | {
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"Hi @czheng17,\r\n\r\nthat's because RoBERTa uses a byte-level BPE (like GPT-2), see section 4.4 in the original paper.\r\n\r\nA good explanation can be found here:\r\n\r\nhttps://github.com/pytorch/fairseq/issues/1716#issuecomment-588750983\r\n\r\n:)",
"Hi @stefan-it ,\r\n\r\nInteresting! Thank you for your help... | 1,587 | 1,588 | 1,588 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Roberta
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [1 ] the official example scripts: (give details below)
* [1] my own modified scripts: (give details below)
The tasks I am working on is:... | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
] | 1,587 | 1,593 | 1,593 | CONTRIBUTOR | null | # 🌟 New model addition
## Model description
Part of the abstract :
> In this paper, we present an efficient mobile NLP architecture, Lite Transformer to
facilitate deploying mobile NLP applications on edge devices. [...] brings consistent improvement over the vanilla transformer on three well-established lan... | {
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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 occu... | 1,587 | 1,603 | 1,603 | CONTRIBUTOR | null | # 🌟 New model addition
## Model description
BART is currently only available in Pytorch.
**Are you planning to release a TF version ?** | {
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https://api.github.com/repos/huggingface/transformers/issues/4000 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4000/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4000/comments | https://api.github.com/repos/huggingface/transformers/issues/4000/events | https://github.com/huggingface/transformers/pull/4000 | 607,210,813 | MDExOlB1bGxSZXF1ZXN0NDA5MjMyNzc5 | 4,000 | Adding --do_lower_case option | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4000?src=pr&el=h1) Report\n> Merging [#4000](https://codecov.io/gh/huggingface/transformers/pull/4000?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/4e817ff41885063e08bb3bcd63e5adfd835b9911&el=desc) will **decrease... | 1,587 | 1,588 | 1,588 | NONE | null | In SQuAD 1.1 using the uncased BERT model, **--do_lower_case** option must be used for initialization of a tokenizer.
Omitting this optional argument, the performance in development set would be lower around 8-9pt in both EM and F1 (In the official setting described in readme, the actual metrics were 72.09 (EM)/81.84 ... | {
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"Sorry to answer this late - can you try the following:\r\n```python\r\nmodel.from_pretrained(<path_to_model.ckpt>, from_tf=True) #even though you don't use TF\r\nmodel.save_pretrained(\"./\") # should be in .bin format\r\n```\r\n\r\nIf this does not work try the following:\r\n```python \r\nparser = argparse.Argume... | 1,587 | 1,588 | 1,588 | CONTRIBUTOR | null | # ❓ Questions & Help
I've recently tried to fine-tune T5 using bart's [finetune.py](https://github.com/huggingface/transformers/blob/master/examples/summarization/bart/finetune.py) (supports T5 fine-tuning as well). The model is saved in a `ckpt` format when I wanted it as a pytorch `bin`, so I found this [page](htt... | {
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] | 1,587 | 1,593 | 1,593 | NONE | null | I notice that the output linear weight for BertForMaskedLM is the same as input embedding. I don't read anywhere in the original paper that the output projection is tied with word embedding? Can you please explain the design choice here?
To reproduce:
```
m = transformers.BertForMaskedLM.from_pretrained('bert-bas... | {
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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"
] | 1,587 | 1,593 | 1,593 | CONTRIBUTOR | null | # 🚀 Feature request
To have a small(toy) in terms of number of parameters versions of models e.g.:
- `gpt2-toy`
- `bert-toy-uncased`
etc.
Alternative: to have separate model type `toy-transformer`.
## Motivation
Working on the project and using transformers package our team noticed that it's difficult fo... | {
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"[Model page](https://huggingface.co/monsoon-nlp/hindi-bert)"
] | 1,587 | 1,588 | 1,588 | CONTRIBUTOR | null | Trained with Google ELECTRA and Hindi Corpus (OSCAR CommonCrawl and latest Hindi Wikipedia)
README offers more details and links to notebooks showing pretraining and finetuning on movie reviews | {
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This PR allows the user to try to setup `max_len_single_sentence` and `max_len_sentences_pair`. If the value if the same as the pre-computed, we display a deprecation warning (avoid breaking old code in... | {
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## Information
Model I am using (Bert, XLNet ...): BertForSequenceClassification
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 tas... | {
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https://api.github.com/repos/huggingface/transformers/issues/3991 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3991/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3991/comments | https://api.github.com/repos/huggingface/transformers/issues/3991/events | https://github.com/huggingface/transformers/pull/3991 | 607,091,868 | MDExOlB1bGxSZXF1ZXN0NDA5MTQyMzI5 | 3,991 | Fix the typos | {
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"That's not a typo :)\r\n\r\nhttps://en.wikipedia.org/wiki/Interval_(mathematics)",
"Ohhh! I am not aware of this notation before. (only [X, Y) is in my knowledge-base). Thanks for the clarification."
] | 1,587 | 1,588 | 1,588 | CONTRIBUTOR | null | Fix the typos of "[0.0, 1.0[" --> "[0.0, 1.0]". | {
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https://api.github.com/repos/huggingface/transformers/issues/3990 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3990/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3990/comments | https://api.github.com/repos/huggingface/transformers/issues/3990/events | https://github.com/huggingface/transformers/issues/3990 | 607,085,934 | MDU6SXNzdWU2MDcwODU5MzQ= | 3,990 | Language generation not possible with roberta? | {
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"`Roberta` has not really been trained on generating text. Small models that work well for generation are `distilgpt2` and `gpt2` for example."
] | 1,587 | 1,588 | 1,588 | NONE | null | Hi,
I have a small question.
I finetuned a roberta model and then I was about to do generation and I understood this was not possible on my model, but only in a smaller collection of model, where most of them are quite huge.
Why is that? Is there another way to generate language with roberta?
Thanks in a advanc... | {
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https://api.github.com/repos/huggingface/transformers/issues/3989 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3989/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3989/comments | https://api.github.com/repos/huggingface/transformers/issues/3989/events | https://github.com/huggingface/transformers/pull/3989 | 607,063,705 | MDExOlB1bGxSZXF1ZXN0NDA5MTIxMjQy | 3,989 | Model cards for KoELECTRA | {
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"That's great! Model pages: \r\nhttps://huggingface.co/monologg/koelectra-base-generator\r\nhttps://huggingface.co/monologg/koelectra-base-discriminator\r\n\r\ncc'ing @LysandreJik and @clarkkev for information"
] | 1,587 | 1,588 | 1,588 | CONTRIBUTOR | null | Hi:)
I've recently uploaded `KoELECTRA`, pretrained ELECTRA model for Korean:)
Thanks for supporting this great library and S3 storage:)
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https://api.github.com/repos/huggingface/transformers/issues/3988 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3988/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3988/comments | https://api.github.com/repos/huggingface/transformers/issues/3988/events | https://github.com/huggingface/transformers/pull/3988 | 607,054,720 | MDExOlB1bGxSZXF1ZXN0NDA5MTE0NDA3 | 3,988 | [Trainer] Add more schedules to trainer | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3988?src=pr&el=h1) Report\n> Merging [#3988](https://codecov.io/gh/huggingface/transformers/pull/3988?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/cb3c2212c79d7ff0a4a4e84c3db48371ecc1c15d&el=desc) will **decrease... | 1,587 | 1,588 | 1,588 | MEMBER | null | Adds all available schedules to trainer and also add beta1 and beta2 for Adam to args.
@julien-c | {
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"No, this isn't correct. This was consistent with other scripts (before they were ported to the new Trainer in #3800) where we always saved the model and its tokenizer before re-loading it for eval \r\n\r\nSo I think that code is currently right. (but again, should be re-written to Trainer pretty soon)"
] | 1,587 | 1,588 | 1,588 | CONTRIBUTOR | null | Fixing #3950
It seems that `output_dir` has been used in place of `tokenizer_name` in `run_xnli.py`. I have corrected this typo.
I am not that familiar with code style in this repo, in a lot of instances I used:
`args.tokenizer_name if args.tokenizer_name else args.model_name_or_path`
Instead, I believe I ... | {
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"You need to install transformers from source as specified in the README"
] | 1,587 | 1,588 | 1,588 | NONE | null | # 🐛 Bug
## Information
Run the example, it returns error as below. The version in April 17 doesn't have the problem.
python ./examples/run_multiple_choice.py \
> --task_name swag \
> --model_name_or_path roberta-base \
> --do_train \
> --do_eval \
> --data_dir $SWAG_DIR \
> --learning_rate 5e-5 \
> --num_t... | {
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https://api.github.com/repos/huggingface/transformers/issues/3985 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3985/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3985/comments | https://api.github.com/repos/huggingface/transformers/issues/3985/events | https://github.com/huggingface/transformers/issues/3985 | 606,998,741 | MDU6SXNzdWU2MDY5OTg3NDE= | 3,985 | Using the T5 model with huggingface's mask-fill pipeline | {
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"Correct me if I'm wrong @patrickvonplaten, but I don't think T5 is trained on masked language modeling (and does not have a mask token) so will not work with this pipeline.",
"Yeah, `T5` is not trained on the conventional \"Bert-like\" masked language modeling objective. It does a special encoder-decoder masked ... | 1,587 | 1,674 | 1,595 | NONE | null | Does anyone know if it is possible to use the T5 model with hugging face's mask-fill pipeline? The below is how you can do it using the default model but i can't seem to figure out how to do is using the T5 model specifically?
```
from transformers import pipeline
nlp_fill = pipeline('fill-mask')
nlp_fill('Huggin... | {
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"when we were training, the accuracy count method is like this: \r\ninput: [0,1,2,3,4,5,...,29]\r\nlabel: [1,2,3,4,5,6,...,30]\r\nso we count the right hits in 30 seqs.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Th... | 1,587 | 1,593 | 1,593 | NONE | null | # ❓ Questions & Help
hi, friends:
there is a problem , that we trained a good lm model on gpt2 and sequence len is 30,when we batch test in training with 30 seqlen, the accuracy can reach 90%. But when we test like this:
[1]->[2],[1,2]->[3],[1,2,3]-->[4], left is the input, and we hope it can predict the right, we ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3983 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3983/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3983/comments | https://api.github.com/repos/huggingface/transformers/issues/3983/events | https://github.com/huggingface/transformers/issues/3983 | 606,973,650 | MDU6SXNzdWU2MDY5NzM2NTA= | 3,983 | MLM Loss not decreasing when pretraining Bert from scratch | {
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https://api.github.com/repos/huggingface/transformers/issues/3982 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3982/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3982/comments | https://api.github.com/repos/huggingface/transformers/issues/3982/events | https://github.com/huggingface/transformers/issues/3982 | 606,972,234 | MDU6SXNzdWU2MDY5NzIyMzQ= | 3,982 | Can't install transformers from sources using poetry | {
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"In the meantime as a workaround, you can do the following:\r\n\r\n1) Fork huggingface/transformers\r\n2) On your fork remove this line https://github.com/huggingface/transformers/blob/97a375484c618496691982f62518130f294bb9a8/setup.py#L79\r\n3) Install your fork with poetry",
"This issue has been automatically ma... | 1,587 | 1,593 | 1,593 | NONE | null | # 🐛 Bug
When installing transformers from sources using poetry
```bash
poetry add git+https://github.com/huggingface/transformers.git
```
The following exception is thrown:
```bash
[InvalidRequirement]
Invalid requirement, parse error at "'extra =='"
```
This is a problem on poetry side. The issue ... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3981?src=pr&el=h1) Report\n> Merging [#3981](https://codecov.io/gh/huggingface/transformers/pull/3981?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/4e817ff41885063e08bb3bcd63e5adfd835b9911&el=desc) will **decrease... | 1,587 | 1,594 | 1,594 | CONTRIBUTOR | null | This patch makes the code shorter, also solves a bug that is suppressed already[1]
old code:
split_on_token(tok = '[MASK]', text='')
> ['[MASK]']
This is a bug, because split_on_token shouldn't add token when the input doesn't have the token
[1] 21451ec (handle string with only whitespaces as empty, 2019-12-... | {
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https://api.github.com/repos/huggingface/transformers/issues/3980 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3980/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3980/comments | https://api.github.com/repos/huggingface/transformers/issues/3980/events | https://github.com/huggingface/transformers/issues/3980 | 606,963,060 | MDU6SXNzdWU2MDY5NjMwNjA= | 3,980 | When I run `import transformers` , it reports an error. But I had no problem with pyrotch-transformers before. Is it a TensorRT problem? | {
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when i run `import transformers`, i get this:
2020-04-26 17:02:59.210145: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:30] Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed prop... | {
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https://api.github.com/repos/huggingface/transformers/issues/3978 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3978/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3978/comments | https://api.github.com/repos/huggingface/transformers/issues/3978/events | https://github.com/huggingface/transformers/pull/3978 | 606,904,727 | MDExOlB1bGxSZXF1ZXN0NDA5MDA2Mzg2 | 3,978 | Fix t5 doc typos | {
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"Great thanks you @enzoampil "
] | 1,587 | 1,588 | 1,588 | CONTRIBUTOR | null | Read through the docs for T5 at `docs/source/model_doc/t5.rst` and found some typos. Hope this helps! | {
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https://api.github.com/repos/huggingface/transformers/issues/3977 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3977/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3977/comments | https://api.github.com/repos/huggingface/transformers/issues/3977/events | https://github.com/huggingface/transformers/issues/3977 | 606,903,449 | MDU6SXNzdWU2MDY5MDM0NDk= | 3,977 | xlnet large | {
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"Maybe the task is learning rate and batch size sensitive. You can try to decrease the learning rate when changing the batch size from 8 to 2. ",
"> Maybe the task is learning rate and batch size sensitive. You can try to decrease the learning rate when changing the batch size from 8 to 2.\r\n\r\nUsing xlnet-larg... | 1,587 | 1,593 | 1,593 | NONE | null | If you train in batch 8 at max length = 512 with the xlnet-base-cased, you will learn well with changes in values such as Loss, Accuracy, Precision, Recall, and F1-score.
However, if you train with batch 2 at max length = 512 with a xlnet-large-cased, even if you run several times, there is almost no change, and pre... | {
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https://api.github.com/repos/huggingface/transformers/issues/3976 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3976/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3976/comments | https://api.github.com/repos/huggingface/transformers/issues/3976/events | https://github.com/huggingface/transformers/pull/3976 | 606,897,497 | MDExOlB1bGxSZXF1ZXN0NDA5MDAxMTA1 | 3,976 | Fixed Style Inconsistency | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3976?src=pr&el=h1) Report\n> Merging [#3976](https://codecov.io/gh/huggingface/transformers/pull/3976?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/4e817ff41885063e08bb3bcd63e5adfd835b9911&el=desc) will **decrease... | 1,587 | 1,588 | 1,588 | CONTRIBUTOR | null | This fixes a style inconsistency in BertForSequenceClassification's constructor where 'config' is referenced using both the parameter 'config' and 'self.config' on the same line.
This line is the only instance in modeling_bert.py where the config parameter is referenced using self.config in a constructor. | {
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https://api.github.com/repos/huggingface/transformers/issues/3975 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3975/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3975/comments | https://api.github.com/repos/huggingface/transformers/issues/3975/events | https://github.com/huggingface/transformers/pull/3975 | 606,870,428 | MDExOlB1bGxSZXF1ZXN0NDA4OTgxMTg1 | 3,975 | Added support for pathlib.Path objects instead of string paths in from_pretrained() (resolves #3962) | {
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This only covers string paths in `from_pretrained` (so vocab_file paths for` __init__` for tokenizers aren't covered). This may or may not be a feature that is desired (since it's fairly easy for the client to convert a path-like to a string). With the changes, you would be able... | {
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"@patrickvonplaten - could you help elaborate on this?",
"Yeah, we need to clean this logging. The weights are correctly loaded into the model as far as I know (we have integration tests for pretrained GPT2 models so the weights have to be correctly loaded). Just need to clean up the logging logic there.",
"Act... | 1,587 | 1,591 | 1,591 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): gpt2
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)
## To reproduce
Steps to re... | {
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https://api.github.com/repos/huggingface/transformers/issues/3973 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3973/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3973/comments | https://api.github.com/repos/huggingface/transformers/issues/3973/events | https://github.com/huggingface/transformers/pull/3973 | 606,818,116 | MDExOlB1bGxSZXF1ZXN0NDA4OTQzMDUy | 3,973 | Pytorch 1.5.0 | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3973?src=pr&el=h1) Report\n> Merging [#3973](https://codecov.io/gh/huggingface/transformers/pull/3973?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/4e817ff41885063e08bb3bcd63e5adfd835b9911&el=desc) will **decrease... | 1,587 | 1,588 | 1,588 | MEMBER | null | PyTorch 1.5.0 doesn't allow specifying a standard deviation of 0 in normal distributions. We were testing that our models initialized with a normal distribution with a mean and a standard deviation of 0 had all their parameters initialized to 0.
This allows us to verify that all weights in the model are indeed init... | {
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"Did you discover any way of doing this?",
"@edmar Nothing solid yet! I Will update if I do.",
"Also looking for a solution\r\nhttps://github.com/google-research/text-to-text-transfer-transformer/issues/133",
"@franz101 @edmar \r\nThe closest thing I could come up with : \r\n\r\n```\r\nfrom transformers impor... | 1,587 | 1,637 | 1,604 | CONTRIBUTOR | null | In the Google T5 paper they mentioned :
For example, with the input, “I love peanut butter and _4_ sandwiches,” the outputs looked like:
I love peanut butter and jelly, which is what makes good sandwiches.
How do I achieve Multi Mask filling with T5 in hugging face transformers?
Code samples please :)
![image]... | {
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https://api.github.com/repos/huggingface/transformers/issues/3971 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3971/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3971/comments | https://api.github.com/repos/huggingface/transformers/issues/3971/events | https://github.com/huggingface/transformers/issues/3971 | 606,813,515 | MDU6SXNzdWU2MDY4MTM1MTU= | 3,971 | Problem with downloading the XLNetSequenceClassification pretrained xlnet-large-cased | {
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"Hey mate, I've encountered the same issue. How did you solve it?",
"I encounter this issue. How can I solve this?",
"the problem is when l import xlnet from pytorch_transformers. instead, you should be importing it from the module called 'transformers'"
] | 1,587 | 1,588 | 1,587 | NONE | null | I've run this before and it was fine. However, this time, i keep encountering this runtime error. In fact, when i tried to initialize model = XLNetModel.from_pretrained('xlnet-large-cased') - it also gives me the 'negative dimension' error.
`model = XLNetForSequenceClassification.from_pretrained("xlnet-large-cased"... | {
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https://api.github.com/repos/huggingface/transformers/issues/3970 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3970/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3970/comments | https://api.github.com/repos/huggingface/transformers/issues/3970/events | https://github.com/huggingface/transformers/pull/3970 | 606,812,090 | MDExOlB1bGxSZXF1ZXN0NDA4OTM4NzI1 | 3,970 | Fix GLUE TPU script | {
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"Pinging @jysohn23 to see if it fixed the issue.",
"Closing in favour of integrating TPU support for the trainer."
] | 1,587 | 1,651 | 1,588 | MEMBER | null | Temporary fix until we refactor this script to work with the trainer. | {
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https://api.github.com/repos/huggingface/transformers/issues/3969 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3969/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3969/comments | https://api.github.com/repos/huggingface/transformers/issues/3969/events | https://github.com/huggingface/transformers/pull/3969 | 606,807,127 | MDExOlB1bGxSZXF1ZXN0NDA4OTM1MjUz | 3,969 | override weights name | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3969?src=pr&el=h1) Report\n> Merging [#3969](https://codecov.io/gh/huggingface/transformers/pull/3969?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/4e817ff41885063e08bb3bcd63e5adfd835b9911&el=desc) will **increase... | 1,587 | 1,594 | 1,594 | NONE | null | Optional override of the weights name, relevant for cases where torch.save() is patched like in https://github.com/allegroai/trains | {
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https://api.github.com/repos/huggingface/transformers/issues/3968 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3968/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3968/comments | https://api.github.com/repos/huggingface/transformers/issues/3968/events | https://github.com/huggingface/transformers/pull/3968 | 606,785,268 | MDExOlB1bGxSZXF1ZXN0NDA4OTE5Mzkw | 3,968 | Remove boto3 dependency | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3968?src=pr&el=h1) Report\n> Merging [#3968](https://codecov.io/gh/huggingface/transformers/pull/3968?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/4e817ff41885063e08bb3bcd63e5adfd835b9911&el=desc) will **increase... | 1,587 | 1,588 | 1,588 | MEMBER | null | Downloading a model from `s3://` urls was not documented anywhere and I suspect it doesn't work with our `from_pretrained` methods anyways.
Removing boto3 also kills its transitive dependencies (some of which are slow to support new versions of Python), contributing to a leaner library:
```
boto3-1.12.46
botoco... | {
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https://api.github.com/repos/huggingface/transformers/issues/3967 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3967/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3967/comments | https://api.github.com/repos/huggingface/transformers/issues/3967/events | https://github.com/huggingface/transformers/pull/3967 | 606,774,696 | MDExOlB1bGxSZXF1ZXN0NDA4OTExNzAx | 3,967 | Proposal: saner num_labels in configs. | {
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"I like this better as well. Probably won't be backwards compatible with users that have their config with `_num_labels` though.",
"Like it better as well! Agree with @LysandreJik that some configs might need to be fixed manually",
"Well, `_num_labels` (if present) should always be consistent with the length of... | 1,587 | 1,588 | 1,588 | MEMBER | null | See https://github.com/guillaume-be/rust-bert/pull/21 for more context | {
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https://api.github.com/repos/huggingface/transformers/issues/3966 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3966/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3966/comments | https://api.github.com/repos/huggingface/transformers/issues/3966/events | https://github.com/huggingface/transformers/pull/3966 | 606,728,187 | MDExOlB1bGxSZXF1ZXN0NDA4ODc3Njk2 | 3,966 | Add CALBERT (Catalan ALBERT) base-uncased model card | {
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"Looks good! Model page for [CALBERT](https://huggingface.co/codegram/calbert-base-uncased)",
"One additional tweak: you should add a \r\n\r\n```\r\n---\r\nlanguage: catalan\r\n---\r\n```\r\n\r\nmetadata block at the top of the model page. Thanks!"
] | 1,587 | 1,587 | 1,587 | CONTRIBUTOR | null | Hi there!
I just uploaded a new ALBERT model pretrained on 4.3 GB of Catalan text. Thank you for these fantastic libraries and platform to make this a joy! | {
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https://api.github.com/repos/huggingface/transformers/issues/3965 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3965/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3965/comments | https://api.github.com/repos/huggingface/transformers/issues/3965/events | https://github.com/huggingface/transformers/pull/3965 | 606,707,384 | MDExOlB1bGxSZXF1ZXN0NDA4ODYyNzky | 3,965 | Remove hard-coded pad token id in distilbert and albert | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3965?src=pr&el=h1) Report\n> Merging [#3965](https://codecov.io/gh/huggingface/transformers/pull/3965?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/73d6a2f9019960c327f19689c1d9a6c0fba31d86&el=desc) will **decrease... | 1,587 | 1,589 | 1,589 | CONTRIBUTOR | null | As the config adds `pad_token_id` attribute, `padding_idx` set the value of `config.pad_token_id` in BertEmbedding. ( PR #3793 )
But it seems that not only the config of `Bert`, but also that of `DistilBert` and `Albert` has `pad_token_id`. ([Distilbert config](https://s3.amazonaws.com/models.huggingface.co/bert/dis... | {
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https://api.github.com/repos/huggingface/transformers/issues/3964 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3964/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3964/comments | https://api.github.com/repos/huggingface/transformers/issues/3964/events | https://github.com/huggingface/transformers/issues/3964 | 606,703,246 | MDU6SXNzdWU2MDY3MDMyNDY= | 3,964 | Error on dtype in modeling_bertabs.py file | {
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Traceback (most recent call last):
File "run_summarizationn.py", line 324, in <module>
main()
File "run_summarizationn.py", line 309, in main
evaluate(args)
File "run_summarizationn.py", line 84, in evaluate
batch_data = predictor.translate_batch(batch)
File "/kaggle/working/trans... | {
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https://api.github.com/repos/huggingface/transformers/issues/3963 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3963/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3963/comments | https://api.github.com/repos/huggingface/transformers/issues/3963/events | https://github.com/huggingface/transformers/issues/3963 | 606,699,847 | MDU6SXNzdWU2MDY2OTk4NDc= | 3,963 | run_language_modeling, RuntimeError: expected scalar type Half but found Float | {
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"What's your PyTorch version? Can you post the output of `transformers-cli env`\r\n\r\nThis does not seem specific to `examples/run_language_modeling.py` so I'm gonna ping @patrickvonplaten on this",
"@julien-c thanks for the prompt response.\r\n`- `transformers` version: 2.8.0\r\n- Platform: Linux-4.14.138+-x86_... | 1,587 | 1,588 | 1,588 | NONE | null | # 🐛 Bug
## Information
CUDA: 10.1
Python 3.6.8 (default, Oct 7 2019, 12:59:55)
Installed transformers from source.
Trying to train **gpt2-medium**
Command Line:
```
export TRAIN_FILE=dataset/wiki.train.raw
export TEST_FILE=dataset/wiki.test.raw
python3 examples/run_language_modeling.py --fp16 \
... | {
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https://api.github.com/repos/huggingface/transformers/issues/3962 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3962/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3962/comments | https://api.github.com/repos/huggingface/transformers/issues/3962/events | https://github.com/huggingface/transformers/issues/3962 | 606,699,601 | MDU6SXNzdWU2MDY2OTk2MDE= | 3,962 | `BertTokenizer.from_pretrained()` not working with native Python `pathlib` module | {
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"Looking into the `BertTokenizer` code, it inherits the `from_pretrained` function so the real issue is coming from `PreTrainedTokenizer`. To confirm this, I tried loading the pretrained `roberta-base` tokenizer and reproduced the same error:\r\n\r\n```\r\nmodel_name = 'roberta-base'\r\ntokenizer = AutoTokenizer.fr... | 1,587 | 1,596 | 1,596 | NONE | null | Consider this code that downloads models and tokenizers to disk and then uses `BertTokenizer.from_pretrained` to load the tokenizer from disk.
**ISSUE:** `BertTokenizer.from_pretrained()` does not seem to be compatible with Python's native [pathlib](https://docs.python.org/3/library/pathlib.html) module.
```
#... | {
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https://api.github.com/repos/huggingface/transformers/issues/3961 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3961/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3961/comments | https://api.github.com/repos/huggingface/transformers/issues/3961/events | https://github.com/huggingface/transformers/issues/3961 | 606,692,999 | MDU6SXNzdWU2MDY2OTI5OTk= | 3,961 | There are some warnings when I used AdamW and pytorch1.5. | {
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"same here",
"This is not a bug but because pytorch 1.5 displays warnings that it didn't displayed before.",
"It may be this file https://github.com/huggingface/transformers/blob/master/src/transformers/optimization.py#L96\r\n\r\nYou can modify the code on those `add`, `addcdiv`, `addcmul` and use `alpha` or `v... | 1,587 | 1,595 | 1,595 | NONE | null | # 🐛 Bug
## Information
pytorch/torch/csrc/utils/python_arg_parser.cpp:756: UserWarning: This overload of add_ is deprecated:
add_(Number alpha, Tensor other)
Consider using one of the following signatures instead:
add_(Tensor other, *, Number alpha)
| {
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https://api.github.com/repos/huggingface/transformers/issues/3960 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3960/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3960/comments | https://api.github.com/repos/huggingface/transformers/issues/3960/events | https://github.com/huggingface/transformers/issues/3960 | 606,674,081 | MDU6SXNzdWU2MDY2NzQwODE= | 3,960 | Question regarding glue examples | {
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"I don't understand the question. The labels for the test sets for GLUE are privately-held, if that's what you're asking.\r\n\r\n(Closing this as it's not really specific to this repo)"
] | 1,587 | 1,587 | 1,587 | NONE | null | hi,
I have used the run_glue.py for QQP dataset and the tested the saved model for a small test set. I get really high F1-score on dev set but get lower F1-score on the test set. My question is that, is the dev set used in glue examples is used to set parameters or is it a held out set?
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https://api.github.com/repos/huggingface/transformers/issues/3959 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3959/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3959/comments | https://api.github.com/repos/huggingface/transformers/issues/3959/events | https://github.com/huggingface/transformers/issues/3959 | 606,668,571 | MDU6SXNzdWU2MDY2Njg1NzE= | 3,959 | AttributeError: 'LambdaLR' object has no attribute 'get_last_lr' | {
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"I encountered the same problem, have you solved it？",
"Upgrading to PyTorch 1.4 would solve that issue :)\r\n\r\nCurrent `master` branch recommends that:\r\n\r\nhttps://github.com/huggingface/transformers/blob/4e817ff41885063e08bb3bcd63e5adfd835b9911/setup.py#L70",
"Thank you so much, I have solved it.",
"`g... | 1,587 | 1,589 | 1,589 | NONE | null | I am trying to run the summarization example using BART and getting the following error.
```
tqdm_dict = {"loss": "{:.3f}".format(avg_loss), "lr": self.lr_scheduler.get_last_lr()[-1]}
AttributeError: 'LambdaLR' object has no attribute 'get_last_lr'
```
The error occurred at this [line](https://github.com/huggi... | {
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https://api.github.com/repos/huggingface/transformers/issues/3958 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3958/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3958/comments | https://api.github.com/repos/huggingface/transformers/issues/3958/events | https://github.com/huggingface/transformers/issues/3958 | 606,666,022 | MDU6SXNzdWU2MDY2NjYwMjI= | 3,958 | model.multiple_choice_head( ) function for Hugging Face GPT2 models | {
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"Method's description says this\r\n\r\n\r\n _mc_token_ids (:obj:`torch.LongTensor` of shape :obj:`(batch_size, num_choices)`, `optional`, default to index of the last token of the input)\r\n Index of the classification token in each input sequence.\r\n Selected in the range ``[0, input_... | 1,587 | 1,592 | 1,592 | NONE | null | Hello,
I just have a quick question about the ```multiple_choice_head( )``` function for the Hugging Face GPT2 models.
when I execute the codes below, everything runs smoothly:
```python
# get pre-trained GPT2Model and GPT2DoubleHeadsModel
model_gpt2 = GPT2Model.from_pretrained('gpt2', output_hidden_states =... | {
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https://api.github.com/repos/huggingface/transformers/issues/3957 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3957/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3957/comments | https://api.github.com/repos/huggingface/transformers/issues/3957/events | https://github.com/huggingface/transformers/pull/3957 | 606,658,181 | MDExOlB1bGxSZXF1ZXN0NDA4ODI1MDMx | 3,957 | Allow the creation of "entity groups" for NerPipeline #3548 | {
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"Was hoping this could get added to the next release! Would be very useful for me.",
"_Note for @LysandreJik and myself_: We need to rebase the PR before merging, I've made some changes to the way batching is handled on pipelines, I just want to be sure we're not missing anything through the unittests.\r\n\r\nOth... | 1,587 | 1,665 | 1,589 | CONTRIBUTOR | null | ### This pull request applies the entity group transformation by setting the parameter: group=True.
This was done by reflecting the transformation inside NerPipeline. This is similar to a previously closed [PR](https://github.com/huggingface/transformers/pull/3607), which I closed because I accidentlly deleted my fo... | {
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https://api.github.com/repos/huggingface/transformers/issues/3956 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3956/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3956/comments | https://api.github.com/repos/huggingface/transformers/issues/3956/events | https://github.com/huggingface/transformers/issues/3956 | 606,611,082 | MDU6SXNzdWU2MDY2MTEwODI= | 3,956 | RuntimeError: Error(s) in loading state_dict for BertForTokenClassification | {
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"An update: after upgrading to transformers 2.8.0, the reported issue is gone. \r\n\r\nNevertheless, could you share an explanation please? ",
"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 contribution... | 1,587 | 1,593 | 1,593 | NONE | null | Since about 1600 BST, 24 Apr 2020, loading ner pipeline gives RuntimeError:
```
from transformers import pipeline
nlp = pipeline("ner", ignore_labels=[])
```
> Traceback (most recent call last):
File "test.py", line 2, in <module>
nlp = pipeline("ner", ignore_labels=[])
File "/Users/xxx/Github/xxx/xxx... | {
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https://api.github.com/repos/huggingface/transformers/issues/3955 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3955/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3955/comments | https://api.github.com/repos/huggingface/transformers/issues/3955/events | https://github.com/huggingface/transformers/pull/3955 | 606,587,662 | MDExOlB1bGxSZXF1ZXN0NDA4NzY4MTQ2 | 3,955 | Fix #3954 - GPT2 is not traceable | {
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"Need to remove the `math` import to pass the Flake test.",
"Just deleted the math import to make the code quality check happy - Thanks a lot for the PR @jazzcook15 and for linking the issue @minimaxir "
] | 1,587 | 1,588 | 1,588 | CONTRIBUTOR | null | This PR replaces the `math.sqrt(...)` computation with `(...)**0.5` which allows the model to be correctly traced by `torch.jit.trace`. | {
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https://api.github.com/repos/huggingface/transformers/issues/3954 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3954/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3954/comments | https://api.github.com/repos/huggingface/transformers/issues/3954/events | https://github.com/huggingface/transformers/issues/3954 | 606,582,061 | MDU6SXNzdWU2MDY1ODIwNjE= | 3,954 | GPT2 is not fully torch.jit.trace-able | {
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"see #3955 for a fix",
"Hi,\r\nI have the same issue even after updating to transformers 4.1.0. The results from the traced model are poor when compared to the original model. Following are the warnings returned when I try to create a traced version of a fine-tuned GPT2 model(using torch.jit.trace()).\r\n\r\n`/u... | 1,587 | 1,610 | 1,588 | NONE | null | # 🐛 Bug
## Information
I'm trying to use PyTorch's tracing on a pre-trained GPT2 model and running into the following warning emitted from torch.jit.trace:
```
/opt/miniconda3/envs/py3/lib/python3.6/site-packages/transformers/modeling_gpt2.py:144: TracerWarning: Converting a tensor to a Python float might caus... | {
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https://api.github.com/repos/huggingface/transformers/issues/3953 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3953/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3953/comments | https://api.github.com/repos/huggingface/transformers/issues/3953/events | https://github.com/huggingface/transformers/pull/3953 | 606,524,096 | MDExOlB1bGxSZXF1ZXN0NDA4NzE4Njk0 | 3,953 | Fix BERT example code for NSP and Multiple Choice | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3953?src=pr&el=h1) Report\n> Merging [#3953](https://codecov.io/gh/huggingface/transformers/pull/3953?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/b290c32e1617fa74f44ccd8b83365fe764437be9&el=desc) will **increase... | 1,587 | 1,590 | 1,590 | CONTRIBUTOR | null | After #3790 was merged I noticed that the examples for BERT NSP and Multiple Choice were wrong, too.
`token_type_id` wasn't being correctly set but that's necessary for the multi sequence tasks (NSP, Multiple Choice, Question Answering). So I changed it to use `encode_plus` / `batch_encode_plus` which takes care of ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3952 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3952/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3952/comments | https://api.github.com/repos/huggingface/transformers/issues/3952/events | https://github.com/huggingface/transformers/issues/3952 | 606,511,581 | MDU6SXNzdWU2MDY1MTE1ODE= | 3,952 | BertForSequenceClassification is not optimum | {
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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"
] | 1,587 | 1,593 | 1,593 | NONE | null | In the documentation about TFBertModel it says:
```
hidden_states (tuple(tf.Tensor), optional, returned when config.output_hidden_states=True):
tuple of tf.Tensor (one for the output of the embeddings + one for the output of each layer) of shape (batch_size, sequence_length, hidden_size).
```
Hidden-states of ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3951 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3951/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3951/comments | https://api.github.com/repos/huggingface/transformers/issues/3951/events | https://github.com/huggingface/transformers/issues/3951 | 606,484,661 | MDU6SXNzdWU2MDY0ODQ2NjE= | 3,951 | run_xnli doesn't execute | {
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## Information
(a related issue is this: #3950 )
I am trying to run the `run_xnli.py` script from the [Examples documentation](https://huggingface.co/transformers/examples.html#xnli), but I am getting an error. I am trying to run the script without training.
## To reproduce
Steps to reproduce th... | {
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https://api.github.com/repos/huggingface/transformers/issues/3950 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3950/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3950/comments | https://api.github.com/repos/huggingface/transformers/issues/3950/events | https://github.com/huggingface/transformers/issues/3950 | 606,470,697 | MDU6SXNzdWU2MDY0NzA2OTc= | 3,950 | In run_xnli.py, output_dir seems to be used in place of tokenizer_name | {
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"Hello! Could you show us with which arguments to do you run the script?",
"Hi!\r\n\r\nI am using the arguments as found in the Doc Example, except it is the uncased MultiBert, and the epochs are set to 1.0.\r\n\r\n```\r\nexport XNLI_DIR=/path/to/XNLI\r\n\r\npython run_xnli.py \\\r\n --model_type bert \\\r\n --... | 1,587 | 1,593 | 1,593 | CONTRIBUTOR | null | # 🐛 Bug
## Information
I am trying to run the `run_xnli` example as found in the documentation. Unfortunately, I get a strange error were the script thinks the `output_dir` argument contains a model name.
It seems that `output_dir` has been used in place of `tokenizer_name` in some instances, such as this: `t... | {
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https://api.github.com/repos/huggingface/transformers/issues/3949 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3949/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3949/comments | https://api.github.com/repos/huggingface/transformers/issues/3949/events | https://github.com/huggingface/transformers/issues/3949 | 606,469,414 | MDU6SXNzdWU2MDY0Njk0MTQ= | 3,949 | After reading the tutorial I can use the BertModel to extract word embedding but how to use it extract the sentence embedding? | {
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<!-- 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/3948 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3948/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3948/comments | https://api.github.com/repos/huggingface/transformers/issues/3948/events | https://github.com/huggingface/transformers/pull/3948 | 606,458,671 | MDExOlB1bGxSZXF1ZXN0NDA4NjY1OTA2 | 3,948 | Add Type Hints to modeling_utils.py Closes #3911 | {
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"I think this is good for merge, no? @julien-c ",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3948?src=pr&el=h1) Report\n> Merging [#3948](https://codecov.io/gh/huggingface/transformers/pull/3948?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/7b75aa9fa55be... | 1,587 | 1,590 | 1,590 | CONTRIBUTOR | null | Add Type Hints to methods in `modeling_utils.py`
Note: The coverage isn't 100%. Mostly skipped internal methods (and some I wasn't sure of). | {
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https://api.github.com/repos/huggingface/transformers/issues/3947 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3947/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3947/comments | https://api.github.com/repos/huggingface/transformers/issues/3947/events | https://github.com/huggingface/transformers/issues/3947 | 606,424,118 | MDU6SXNzdWU2MDY0MjQxMTg= | 3,947 | Many tests fails with PyTorch 1.5.0 | {
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These errors should not reflect real-life usage, and, therefore, should not impact user experience too much. | {
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"Try reinstalling using \r\n```pip install git+https://github.com/huggingface/transformers```",
"That didn't work, sorry",
"Try uninstalling before or starting again from a clean venv",
"Have the same issue, did force install; uninstall & install, same problem. If I even search the https://github.com/huggingf... | 1,587 | 1,660 | 1,591 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Using "from transformers import DefaultDataCollator" raises an ImportError on my system. Unsure if this is really a bug or if I'm doing something stupid. Any help would be appreciated.
Model I am using (Bert, XLNet ...): N/A
Language I am using the model on (English, Chinese ...): N/... | {
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https://api.github.com/repos/huggingface/transformers/issues/3945 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3945/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3945/comments | https://api.github.com/repos/huggingface/transformers/issues/3945/events | https://github.com/huggingface/transformers/issues/3945 | 606,351,639 | MDU6SXNzdWU2MDYzNTE2Mzk= | 3,945 | BertConfig.to_json_file('config.json') saves "num_labels" as "_num_labels" on Google Colab | {
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"Hello, I believe there's a mismatch between the versions on your computer and on Google colab. When running on master, saving the file as you did:\r\n\r\n```py\r\nfrom transformers import BertConfig\r\n\r\nNUM_LABELS = 3\r\nconfig = BertConfig.from_pretrained('bert-base-german-cased')\r\nconfig.num_labels = NUM_LA... | 1,587 | 1,588 | 1,588 | NONE | null | # 🐛 Bug
There is a problem with config.to_json_file() on Google Colab.
## Information
The "num_labels" key pair is saved as "_num_labels" key in the config.json file produced by BertConfig.to_json_file('config.json').
When this file is subsequently read with BertConfig.from_json_file('config.json') the "_num... | {
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"Hi Julian, would you please provide more information on this issue?",
"In our Trainer, in `torch.distributed` mode, eval/predict are currently running on a single node, even though there's no fundamental reason for this to be the case.\r\n\r\nSupporting would probably require writing a new instance of torch's [D... | 1,587 | 1,590 | 1,590 | MEMBER | null | Tagging this as a Good First issue if anyone's interested. | {
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https://api.github.com/repos/huggingface/transformers/issues/3943 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3943/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3943/comments | https://api.github.com/repos/huggingface/transformers/issues/3943/events | https://github.com/huggingface/transformers/issues/3943 | 606,270,838 | MDU6SXNzdWU2MDYyNzA4Mzg= | 3,943 | How to input hidden state vectors from GPT2Model directly into mc_head of the GPT2DoubleHeads Model? | {
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I want to perform the following task:
**1.** _Feed in a text sequence to a GPT2Model (the GPT-2 model without output head);_
**2.** _Extract the hidden state vectors of the text sequence that are generated at each layer of the GPT2Model;_
**3.** _Input the hidden state vectors from each layer of the ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3942 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3942/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3942/comments | https://api.github.com/repos/huggingface/transformers/issues/3942/events | https://github.com/huggingface/transformers/issues/3942 | 606,192,832 | MDU6SXNzdWU2MDYxOTI4MzI= | 3,942 | XLNetLMHeadModel: target mapping with num_predict > 1 and labels not working | {
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"Hi @hannodje,\r\n\r\nsorry to answer so late. Could you provide a complete code sample that can reproduce the error? One in which you set define all the variables `input`, `attention_mask`, `perm_mask`, `target_mapping`, `sequence_ids` and `target` and which defines which XLNetLMHeadModel you use. Ideally, I can c... | 1,587 | 1,591 | 1,591 | NONE | null | Hi,
While trying to fine tune the XLNetLMHeadModel, I ran into the following error message:
` File "[...]/lib/python3.8/site-packages/torch/nn/modules/module.py", line 532, in __call__
result = self.forward(*input, **kwargs)
File "[...]/lib/python3.8/site-packages/transformers/modeling_xlnet.py", line 10... | {
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https://api.github.com/repos/huggingface/transformers/issues/3941 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3941/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3941/comments | https://api.github.com/repos/huggingface/transformers/issues/3941/events | https://github.com/huggingface/transformers/issues/3941 | 606,093,836 | MDU6SXNzdWU2MDYwOTM4MzY= | 3,941 | Decoding output sequences from TFGPT2Model | {
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"Hi @xeb, sorry to reply so late. I think you are using the wrong model. Instead of using `TFGPT2Model` you should use GPT2 with a LM Head on top `GPT2LMHeadModel`. The code should work then :-) ",
"@patrickvonplaten could you please specify why he should GPT2LMHeadModel model instead of TFGPT2 ? I think a littl... | 1,587 | 1,692 | 1,589 | CONTRIBUTOR | null | # ❓ Questions & Help
I asked this on SO without any luck.
https://stackoverflow.com/questions/61222878/how-can-you-decode-output-sequences-from-tfgpt2model
## Details
I'm trying to get generated text from the TFGPT2Model in the Transformers library. I can see the output tensor, but I'm not able to decode it. Is... | {
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https://api.github.com/repos/huggingface/transformers/issues/3940 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3940/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3940/comments | https://api.github.com/repos/huggingface/transformers/issues/3940/events | https://github.com/huggingface/transformers/pull/3940 | 606,065,407 | MDExOlB1bGxSZXF1ZXN0NDA4MzQ5NTU5 | 3,940 | fix resize_token_embeddings to accept padding_idx for xlm-roberta models | {
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and it leads to the wrong embedding for xlm-roberta models
which needs embedding to have padding_idx as 1 not 0.
I fixed issue by adding option for padding_idx and considered padding_idx as None (which is 0 as default) for compatibility for other typ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3939 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3939/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3939/comments | https://api.github.com/repos/huggingface/transformers/issues/3939/events | https://github.com/huggingface/transformers/pull/3939 | 606,038,176 | MDExOlB1bGxSZXF1ZXN0NDA4MzI3OTk1 | 3,939 | Continue training args and tqdm in notebooks | {
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"Updates committed",
"Thanks!"
] | 1,587 | 1,588 | 1,588 | CONTRIBUTOR | null | Added a little more description to the metadata of training args for new scripts.
`--overwrite_output_dir` can be used to continue training from checkpoint if `--output_dir` points to a directory already having checkpoints.
This can help reduce the confusion when migrating from older script.
tqdm in colab pri... | {
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https://api.github.com/repos/huggingface/transformers/issues/3938 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3938/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3938/comments | https://api.github.com/repos/huggingface/transformers/issues/3938/events | https://github.com/huggingface/transformers/issues/3938 | 606,013,606 | MDU6SXNzdWU2MDYwMTM2MDY= | 3,938 | [Benchmark] Parameter settings of XLM-R on NER tasks | {
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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"
] | 1,587 | 1,593 | 1,593 | NONE | null | # 🖥 Benchmarking `transformers`
## Benchmark
`XLM-RoBerta` on CoNLL 03 English NER dataset
## Set-up
`model_name_path`: xlm-roberta-base
`max_steps`: 3000 (roughly 6 epochs)
`warmup_steps`: 300
`save_steps`: 200
`learning_rate`: 5e-5
`per_gpu_train_batch_size`: 8
`n_gpu`: 3 (Titan X)
## Results
91.... | {
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https://api.github.com/repos/huggingface/transformers/issues/3937 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3937/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3937/comments | https://api.github.com/repos/huggingface/transformers/issues/3937/events | https://github.com/huggingface/transformers/issues/3937 | 605,952,840 | MDU6SXNzdWU2MDU5NTI4NDA= | 3,937 | What should I do if I want to change the padding idx in pytorch bert(Huggingface)? | {
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"Hi @R-craft, \r\n\r\nThat's actually a bug. Thanks for spotting it :-) Will open a PR."
] | 1,587 | 1,588 | 1,588 | NONE | null |
I find ,in RobertaModel class, the padding idx is limited to 1(is it true?),which is different from my tokenizer and data.So what should I do to change or just apply the model structure...
###
class RobertaEmbeddings(BertEmbeddings):
"""
Same as BertEmbeddings with a tiny tweak for positional embeddings... | {
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https://api.github.com/repos/huggingface/transformers/issues/3936 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3936/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3936/comments | https://api.github.com/repos/huggingface/transformers/issues/3936/events | https://github.com/huggingface/transformers/issues/3936 | 605,950,237 | MDU6SXNzdWU2MDU5NTAyMzc= | 3,936 | Pytorch 1.5 DataParallel | {
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"I'm experiencing the same problem running `transformers/examples/run_language_modeling.py` with RoBERTa. Works well with PyTorch 1.4.0 tho.",
"Also happens with RoBERTa, but only in distributed mode (only tested with DataParallel for now)",
"@Rizhiy, do you mind putting a code example? I can't reproduce on `ma... | 1,587 | 1,615 | 1,590 | NONE | null | # 🐛 Bug
## Information
Can't run forward in PyTorch 1.5.0, works fine in 1.4.0
Model I am using (Bert, XLNet ...): XLNet
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 script... | {
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https://api.github.com/repos/huggingface/transformers/issues/3935 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3935/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3935/comments | https://api.github.com/repos/huggingface/transformers/issues/3935/events | https://github.com/huggingface/transformers/issues/3935 | 605,938,690 | MDU6SXNzdWU2MDU5Mzg2OTA= | 3,935 | How to feeding hidden state vectors from one transformer directly into a layer of different transformer | {
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"Did you ever find the answer? "
] | 1,587 | 1,591 | 1,587 | NONE | null | Hello,
I want to perform the following task:
**1.** _Feed in a text sequence to a GPT2Model (the GPT-2 model without output head);_
**2.** _Extract the hidden state vectors of the text sequence that are generated at each layer of the GPT2Model;_
**3.** _Feed the hidden state vectors from each layer of the G... | {
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https://api.github.com/repos/huggingface/transformers/issues/3934 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3934/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3934/comments | https://api.github.com/repos/huggingface/transformers/issues/3934/events | https://github.com/huggingface/transformers/pull/3934 | 605,930,385 | MDExOlB1bGxSZXF1ZXN0NDA4MjQ1MDgz | 3,934 | [qol] example scripts: parse args from .args file or JSON | {
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"Thanks for adding this! Could you also integrate it into the `run_ner` example 🤔",
"Yes @stefan-it I'll add it to all (Trainer-updated) scripts.\r\n\r\nDo you have a preference between the JSON approach and the args one? Or should we do both?",
"Perfect!!! it works like a charm. I think both would be nice.",
... | 1,587 | 1,588 | 1,588 | MEMBER | null | You can either:
- pass the path to a json file as the unique argument
- automatically load args from a .args file that's a sibling of the entrypoint script.
```json
{
"model_name_or_path": "bert-base-cased",
"task_name": "mnli",
"data_dir": "./data/glue/MNLI",
"output_dir": "./models/mnli"
}
```
... | {
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https://api.github.com/repos/huggingface/transformers/issues/3933 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3933/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3933/comments | https://api.github.com/repos/huggingface/transformers/issues/3933/events | https://github.com/huggingface/transformers/pull/3933 | 605,908,862 | MDExOlB1bGxSZXF1ZXN0NDA4MjI3NzIz | 3,933 | Add ALBERT to the Tensorflow to Pytorch model conversion cli | {
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"LGTM!"
] | 1,587 | 1,589 | 1,589 | CONTRIBUTOR | null | This PR adds ALBERT to the `convert` command of `transformers-cli` to allow the conversion of pre-trained models from Tensorflow to Pytorch. The documentation is updated to show how to run the conversion. | {
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https://api.github.com/repos/huggingface/transformers/issues/3932 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3932/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3932/comments | https://api.github.com/repos/huggingface/transformers/issues/3932/events | https://github.com/huggingface/transformers/pull/3932 | 605,886,906 | MDExOlB1bGxSZXF1ZXN0NDA4MjA5NzY2 | 3,932 | [ci] Load pretrained models into the default (long-lived) cache | {
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"Sorry I missed this. This is cool!"
] | 1,587 | 1,588 | 1,588 | MEMBER | null | There's an inconsistency right now where:
- we load some models into CACHE_DIR
- and some models in the default cache
- and often, in both for the same models
When running the RUN_SLOW tests, this takes a lot of disk space, time, and bandwidth.
I'd rather always use the default cache
| {
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"Hi! You can't directly load an official TensorFlow checkpoint in the PyTorch model, you first need to convert it. You can use this [script](https://github.com/huggingface/transformers/blob/master/src/transformers/convert_bert_original_tf_checkpoint_to_pytorch.py) to convert it to a PyTorch checkpoint.\r\n\r\nIf yo... | 1,587 | 1,619 | 1,589 | CONTRIBUTOR | null | Hi, there might be something I am doing wrong, but I cannot figure out what that is, then any help would be welcome.
After downloading a TF checkpoint (containing model.index, model.data, model.meta, config.json and vocab.txt files), I used it to perform pretraining using some more text, more relevant to the task I ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3930 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3930/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3930/comments | https://api.github.com/repos/huggingface/transformers/issues/3930/events | https://github.com/huggingface/transformers/issues/3930 | 605,739,018 | MDU6SXNzdWU2MDU3MzkwMTg= | 3,930 | How can i finetune an encode-decoder combination? | {
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"Well I found the summarization example, I'm going to read it and I'll close this issue if it helps. Would still be happy if you can help.",
"@Palipoor Can you please share the summarization example. I am looking for one.",
"> @Palipoor Can you please share the summarization example. I am looking for one.\r\n\r... | 1,587 | 1,593 | 1,593 | NONE | null | Hi, I want to finetune an encode-decoder model to train on a parallel dataset(something like translation) and I'm not sure what should I do. I read [this](https://medium.com/huggingface/encoder-decoders-in-transformers-a-hybrid-pre-trained-architecture-for-seq2seq-af4d7bf14bb8) blog post but It didn't help. It doesn't ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3929 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3929/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3929/comments | https://api.github.com/repos/huggingface/transformers/issues/3929/events | https://github.com/huggingface/transformers/pull/3929 | 605,733,236 | MDExOlB1bGxSZXF1ZXN0NDA4MDgxMTE4 | 3,929 | Add support for LayerNorm before residual connection in transformer | {
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"Because I just stumbled upon it: a counterpoint in [Understanding the Difficulty of Training Transformers](https://arxiv.org/abs/2004.08249), where the author founds that while this tends to stabilize the convergence, it also results in worse performances for the runs that do converge.\r\n\r\n(Still, nice PR, I wa... | 1,587 | 1,619 | 1,619 | CONTRIBUTOR | null | Recent work has shown that placing the layer norm before the residual connection in a transformer leads to better gradient propagation and more stable training. For example, [Learning Deep Transformer Models for Machine Translation](https://arxiv.org/abs/1906.01787) shows that when stacking more layers, the Pre-LN tran... | {
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https://api.github.com/repos/huggingface/transformers/issues/3928 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3928/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3928/comments | https://api.github.com/repos/huggingface/transformers/issues/3928/events | https://github.com/huggingface/transformers/pull/3928 | 605,705,066 | MDExOlB1bGxSZXF1ZXN0NDA4MDU3Nzkx | 3,928 | Fix TFAlbertForSequenceClassification classifier dropout probability.… | {
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https://api.github.com/repos/huggingface/transformers/issues/3927 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3927/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3927/comments | https://api.github.com/repos/huggingface/transformers/issues/3927/events | https://github.com/huggingface/transformers/issues/3927 | 605,678,028 | MDU6SXNzdWU2MDU2NzgwMjg= | 3,927 | ❓ DistilBert test perplexity based on WikiText-2: ppl is too low? | {
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"@VictorSanh can correct me if I'm wrong, but in general, the perplexity for masked language models like BERT is much lower than the perplexity for causal language models. \r\n\r\nThat's because the \"MLM perplexity\" isn't the actual perplexity (in the sense that it is the probability of a sentence, computed from ... | 1,587 | 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/3926 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3926/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3926/comments | https://api.github.com/repos/huggingface/transformers/issues/3926/events | https://github.com/huggingface/transformers/pull/3926 | 605,620,985 | MDExOlB1bGxSZXF1ZXN0NDA3OTg5MjQ2 | 3,926 | Remove 50k limits bug | {
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"This sounds good. We originally were trying to reimplement exactly the other examples. But now we can have the lightning examples support a wider range of options.",
"@srush I can take care of this when I go to work on #4494 if that's alright with you.",
"This issue has been automatically marked as stale becau... | 1,587 | 1,595 | 1,595 | CONTRIBUTOR | null | Hey guys!
Just looked through the transformer_base... why not also allow any of the trainer args to be used?
I imagine the best set up for you guys is:
- add default trainer args (since people can look into the lightning docs for details on this)
- add hf specific args (nlp related or whatever you guys need)
-... | {
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https://api.github.com/repos/huggingface/transformers/issues/3924 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3924/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3924/comments | https://api.github.com/repos/huggingface/transformers/issues/3924/events | https://github.com/huggingface/transformers/pull/3924 | 605,574,636 | MDExOlB1bGxSZXF1ZXN0NDA3OTUyMDA4 | 3,924 | Change uses of pow(x, 3) to pow(x, 3.0) to resolve #3873 | {
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https://api.github.com/repos/huggingface/transformers/issues/3923 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3923/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3923/comments | https://api.github.com/repos/huggingface/transformers/issues/3923/events | https://github.com/huggingface/transformers/pull/3923 | 605,548,630 | MDExOlB1bGxSZXF1ZXN0NDA3OTMwODQz | 3,923 | Feat/add model card | {
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"Thanks! [Model page](https://huggingface.co/lvwerra/gpt2-imdb-ctrl)"
] | 1,587 | 1,587 | 1,587 | MEMBER | null | Add model card for sentiment control model. | {
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https://api.github.com/repos/huggingface/transformers/issues/3922 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3922/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3922/comments | https://api.github.com/repos/huggingface/transformers/issues/3922/events | https://github.com/huggingface/transformers/issues/3922 | 605,508,819 | MDU6SXNzdWU2MDU1MDg4MTk= | 3,922 | LineByLineTextDataset limits the total number of examples to 50000 documents | {
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"It's a bug. Do you want to submit a PR to remove?",
"Yes that would be great",
"Closed by #3926"
] | 1,587 | 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,
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"Yes, you would now need to do it manually by calling `tokenizer.save_pretrained(training_args.output_dir)`\r\n\r\nI'll keep this issue open to see if many people ask for it (we can re-add if it's the case). cc @LysandreJik ",
"I think if an extra step is needed, it should say it in the guideline ;) \r\nSo perhap... | 1,587 | 1,594 | 1,587 | NONE | null | # 🐛 Bug
Hi,
While running new run_language_modeling.py, at the end it only saves pytorch model and config.json and training arguments
Unlike before it also used to store vocab.txt and tokenizer_config.json
I am not using any custom tokenizer, only using tokenizer provided by the model.
## Command Details... | {
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https://api.github.com/repos/huggingface/transformers/issues/3920 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3920/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3920/comments | https://api.github.com/repos/huggingface/transformers/issues/3920/events | https://github.com/huggingface/transformers/issues/3920 | 605,476,186 | MDU6SXNzdWU2MDU0NzYxODY= | 3,920 | run_language_modeling.py line 251: checking if it is a directory | {
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"I also faced the similler issue while the arguments \r\n--save_steps 200\r\n--save_total_limit 3 \r\nRemoving this arguments worked. But need to know what could be the issue",
"Did removing them worked through the end completely? Because there is a default value for save_steps, and I just set it to 1 to see if t... | 1,587 | 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/3919 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3919/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3919/comments | https://api.github.com/repos/huggingface/transformers/issues/3919/events | https://github.com/huggingface/transformers/issues/3919 | 605,470,867 | MDU6SXNzdWU2MDU0NzA4Njc= | 3,919 | xlm-roberta (large/base) : run_language_modeling.py cannot starting training | {
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"Have you tried launching a debugger to see exactly what takes a long time?\r\n\r\nI would use vscode remote debugging.",
"I would guess that your tokenization process takes too long. If you're training a new LM from scratch, I would recommend using the fast [Tokenizers library](https://github.com/huggingface/tok... | 1,587 | 1,588 | 1,588 | CONTRIBUTOR | null | Hi HuggingFace, thank you very much for your great contribution.
# ❓ Questions & Help
My problem is : run_language_modeling.py takes abnormally long time for `xlm-roberta-large & base` **_"before" start training_**
. It got stuck at the following step for 7 hours (so I gave up eventually) :
`transformers.da... | {
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https://api.github.com/repos/huggingface/transformers/issues/3918 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3918/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3918/comments | https://api.github.com/repos/huggingface/transformers/issues/3918/events | https://github.com/huggingface/transformers/pull/3918 | 605,343,657 | MDExOlB1bGxSZXF1ZXN0NDA3NzYzMTU5 | 3,918 | change scheduler.get_last_lr to get_lr to avoid bug | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3918?src=pr&el=h1) Report\n> Merging [#3918](https://codecov.io/gh/huggingface/transformers/pull/3918?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/cb3c2212c79d7ff0a4a4e84c3db48371ecc1c15d&el=desc) will **decrease... | 1,587 | 1,587 | 1,587 | CONTRIBUTOR | null | Learning rate scheduler function for getting last lr is `get_lr` instead of `get_last_lr`. | {
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https://api.github.com/repos/huggingface/transformers/issues/3917 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3917/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3917/comments | https://api.github.com/repos/huggingface/transformers/issues/3917/events | https://github.com/huggingface/transformers/pull/3917 | 605,292,178 | MDExOlB1bGxSZXF1ZXN0NDA3NzIxOTgy | 3,917 | Create README.md | {
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"Thanks! [Model page](https://huggingface.co/SparkBeyond/roberta-large-sts-b)",
"PS: you should upload an avatar for the SparkBeyond org here: https://huggingface.co/SparkBeyond"
] | 1,587 | 1,587 | 1,587 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/3916 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3916/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3916/comments | https://api.github.com/repos/huggingface/transformers/issues/3916/events | https://github.com/huggingface/transformers/pull/3916 | 605,271,013 | MDExOlB1bGxSZXF1ZXN0NDA3NzA1OTU5 | 3,916 | feat: add logging through Weights & Biases | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3916?src=pr&el=h1) Report\n> Merging [#3916](https://codecov.io/gh/huggingface/transformers/pull/3916?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/cb3c2212c79d7ff0a4a4e84c3db48371ecc1c15d&el=desc) will **decrease... | 1,587 | 1,588 | 1,588 | CONTRIBUTOR | null | Hi,
I've been using hugging-face for a while and I've been loving it. I think it could become a central reference for NLP problems and the new `Trainer` class made it so much easier to add new functionality.
I would like to contribute in solving a few limitations I observed:
* some models don't have clear detail... | {
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https://api.github.com/repos/huggingface/transformers/issues/3915 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3915/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3915/comments | https://api.github.com/repos/huggingface/transformers/issues/3915/events | https://github.com/huggingface/transformers/issues/3915 | 605,262,363 | MDU6SXNzdWU2MDUyNjIzNjM= | 3,915 | New run_language_modeling.py continuing trainng | {
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"Yes, we removed the `--should_continue` flag. You can just use your latest checkpoint as `--model_name_or_path`\r\n\r\nLet us know if this helps",
"Yup, The new script is really clean and understandable. To continue training, I should use `--overwrite_output_dir`? Because, when I point to last checkpoint direct... | 1,587 | 1,600 | 1,587 | CONTRIBUTOR | null | I tried using new script for Language Modeling to train model from scratch.
I was training model with old script. When I tried continuing using new one, there is no option for `--should_continue`.
Does `--overwrite_output_dir` makes it train from scratch if i use same directory for `--model_name_or_path` and `--o... | {
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https://api.github.com/repos/huggingface/transformers/issues/3914 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3914/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3914/comments | https://api.github.com/repos/huggingface/transformers/issues/3914/events | https://github.com/huggingface/transformers/issues/3914 | 605,254,015 | MDU6SXNzdWU2MDUyNTQwMTU= | 3,914 | Unknown Device when training GPT2 with TPUs in Colab | {
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"Fixed when building from source"
] | 1,587 | 1,588 | 1,588 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): DialoGPT2-small from microsoft
Language I am using the model on (English, Chinese ...): Spanish Conversations
The problem arises when using: Pytorch's XLA library for trying to train a GPT2 model on google colab TPUS
* [ ] the official example sc... | {
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https://api.github.com/repos/huggingface/transformers/issues/3913 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3913/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3913/comments | https://api.github.com/repos/huggingface/transformers/issues/3913/events | https://github.com/huggingface/transformers/pull/3913 | 605,253,145 | MDExOlB1bGxSZXF1ZXN0NDA3NjkxOTAw | 3,913 | Summarization | {
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