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https://api.github.com/repos/huggingface/transformers/issues/3013 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3013/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3013/comments | https://api.github.com/repos/huggingface/transformers/issues/3013/events | https://github.com/huggingface/transformers/issues/3013 | 570,709,317 | MDU6SXNzdWU1NzA3MDkzMTc= | 3,013 | Generation with gpt-2 | {
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"There is an example: https://github.com/huggingface/transformers/blob/master/examples/run_generation.py",
"Thanks!",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n"
] | 1,582 | 1,587 | 1,582 | CONTRIBUTOR | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
Tensorflow enthusiast can help you out. Make s... | {
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"The code snippet prints `True` for me.\r\nI have the versions:\r\ntransformers version: 2.5.1\r\nPlatform: Linux\r\nPython version: 3.6.9\r\nPyTorch version: 1.4.0+cpu\r\nCan you try `pip install --upgrade transformers` and see whether the error is still there?\r\n\r\n(Posted on behalf of @patrickvonplaten who's h... | 1,582 | 1,582 | 1,582 | NONE | null | # 🐛 Bug
## Information
Model I am using (BertTokenizer,):
Language I am using the model on: English
The problem arises when using:
* [ ] the official example scripts.
The tasks I am working on is:
* [ ] Simple batch tokenization task
## To reproduce
```
from transformers import BertTokenizer, Ber... | {
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https://api.github.com/repos/huggingface/transformers/issues/3011 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3011/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3011/comments | https://api.github.com/repos/huggingface/transformers/issues/3011/events | https://github.com/huggingface/transformers/pull/3011 | 570,660,178 | MDExOlB1bGxSZXF1ZXN0Mzc5NjU4MDYw | 3,011 | Add models special tokens to its pretrained configs | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3011?src=pr&el=h1) Report\n> Merging [#3011](https://codecov.io/gh/huggingface/transformers/pull/3011?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e693cd1e877aa191d3317faed33e87d1558c9406?src=pr&el=desc) will **d... | 1,582 | 1,583 | 1,583 | MEMBER | null | I think the token_ids for each specific model should also be added to their pretrain configs. This would also make the function generate() much easier to use for the user.
If ok, I can also add these tokens for models not having a LMHead. | {
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https://api.github.com/repos/huggingface/transformers/issues/3010 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3010/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3010/comments | https://api.github.com/repos/huggingface/transformers/issues/3010/events | https://github.com/huggingface/transformers/pull/3010 | 570,647,752 | MDExOlB1bGxSZXF1ZXN0Mzc5NjQ3NDcx | 3,010 | Possible improvement of padding logic in generate | {
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Instead of setting the `pad_token_id` to `eos_token_id` if `pad_token_id` is not defined and `eos_token_id` is defined, the following lo... | {
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https://api.github.com/repos/huggingface/transformers/issues/3009 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3009/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3009/comments | https://api.github.com/repos/huggingface/transformers/issues/3009/events | https://github.com/huggingface/transformers/pull/3009 | 570,492,033 | MDExOlB1bGxSZXF1ZXN0Mzc5NTE1NDQz | 3,009 | add crf layer to BERT, RoBERTa, XLMR | {
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"What do you think about just using https://github.com/harvardnlp/pytorch-struct (I'm biased)? It should remove the need for most of this code. \r\n\r\nAlso we now have a pytorch-lightning NER example which should make this much simpler. \r\n\r\nWould also be helpful to know if any of this improves prediction accur... | 1,582 | 1,584 | 1,584 | NONE | null | Building on pull request [ bert（+lstm）+crf #2249 ], I make it more generic and similar to run_ner.py . There is a CRF layer adapted from https://github.com/jiesutd/LatticeLSTM , which does not have additional package requirements, and was published in ACL 2018. | {
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https://api.github.com/repos/huggingface/transformers/issues/3008 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3008/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3008/comments | https://api.github.com/repos/huggingface/transformers/issues/3008/events | https://github.com/huggingface/transformers/pull/3008 | 570,474,899 | MDExOlB1bGxSZXF1ZXN0Mzc5NTAwODUw | 3,008 | [WIP] Remove tokenizers dependency | {
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https://api.github.com/repos/huggingface/transformers/issues/3007 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3007/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3007/comments | https://api.github.com/repos/huggingface/transformers/issues/3007/events | https://github.com/huggingface/transformers/issues/3007 | 570,440,246 | MDU6SXNzdWU1NzA0NDAyNDY= | 3,007 | [Benchmark] Pipeline for question answering | {
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"same experience with a 2080TI. It s like it s not batched...",
"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",
"As @pommedeterresautee mentioned, the samples are not batched. I've m... | 1,582 | 1,606 | 1,589 | NONE | null | # 🖥 Benchmarking `transformers`
## Benchmark
I'm trying to benchmark QA model with `bert-large-uncased-whole-word-masking-finetuned-squad`. But it seems it is extremely slow e.g. 3-4 sec for 1 question with 2 contexts.
I feel there is something I'm missing in pipeline.
## Sample Code:
```
def answer(self... | {
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https://api.github.com/repos/huggingface/transformers/issues/3006 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3006/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3006/comments | https://api.github.com/repos/huggingface/transformers/issues/3006/events | https://github.com/huggingface/transformers/pull/3006 | 570,385,755 | MDExOlB1bGxSZXF1ZXN0Mzc5NDI2ODYw | 3,006 | [FIX] not training when epoch is small | {
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"Cool, thanks @mataney! Do you mind running `make style` at the root of the repository to reformat the file according to `black` and `isort`, as indicated in our [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md#start-contributing-pull-requests)?\r\n\r\nThis is so the... | 1,582 | 1,584 | 1,584 | CONTRIBUTOR | null | Closes https://github.com/huggingface/transformers/issues/2995
Solving bug where for small epochs and large gradient_accumulation_steps we never train.
Explained further here: https://github.com/huggingface/transformers/issues/2995 | {
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https://api.github.com/repos/huggingface/transformers/issues/3005 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3005/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3005/comments | https://api.github.com/repos/huggingface/transformers/issues/3005/events | https://github.com/huggingface/transformers/issues/3005 | 570,371,044 | MDU6SXNzdWU1NzAzNzEwNDQ= | 3,005 | Output of pipeline feature extraction | {
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"I cannot reproduce this. Can you post a verifiable example with full code that I can just copy and paste?\r\n\r\nHere you see that I just get 7 tokens back:\r\n\r\n```python\r\nimport numpy as np\r\nfrom transformers import AutoTokenizer, AutoModel, pipeline\r\n\r\n\r\nmodel = AutoModel.from_pretrained('distilbert... | 1,582 | 1,588 | 1,588 | NONE | null | Hi,
I am using the new pipeline feature of transformers for feature extraction and I have to say it's amazing. However I would like to alter the output of the pipeline slightly but I am not sure how to and I was hoping some people of the community could point me into the right direction.
I am using the following ... | {
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https://api.github.com/repos/huggingface/transformers/issues/3004 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3004/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3004/comments | https://api.github.com/repos/huggingface/transformers/issues/3004/events | https://github.com/huggingface/transformers/issues/3004 | 570,369,585 | MDU6SXNzdWU1NzAzNjk1ODU= | 3,004 | BART : How can I train and evaluate BART on CNN/DM dataset | {
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"BART has only just been implemented and is not part of release code yet. I'm sure that examples will be added later on, you just need a bit more patience.",
"How is this going? I would like to train BART for text summarization with my own dataset and I have no idea of what preprocessing is needed or what inputs ... | 1,582 | 1,614 | 1,585 | CONTRIBUTOR | null | # ❓ Questions & Help
@sshleifer
I found examples for text summarization on CNN/DM dataset using BERT, but I couldn't find any example using BART.
**Are you going to add it later, or update the existing example to add BART, or it's not scheduled ?** | {
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https://api.github.com/repos/huggingface/transformers/issues/3001 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/3001/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/3001/comments | https://api.github.com/repos/huggingface/transformers/issues/3001/events | https://github.com/huggingface/transformers/issues/3001 | 570,163,848 | MDU6SXNzdWU1NzAxNjM4NDg= | 3,001 | Changing the loss function in BERT | {
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"This is a very general PyTorch question. Please post it on Stack Overflow. https://stackoverflow.com/\r\n\r\nAbout the BERT part: `outputs` is a tuple. `[0]` is the last hidden state (sequence output), `[1]` is the pooled output.\r\n\r\n"
] | 1,582 | 1,582 | 1,582 | NONE | null | # ❓ Questions & Help
Hello,
I'm trying to replace the _CrossEntropyLoss_ with the _KLDivLoss_ for a sentence classification task using some golden logits and the logits from the BERT model.
```
golden_logits = …
outputs = model(**inputs)
# the logits from BERT
logits = outputs[1]
loss_fct = KLDivLo... | {
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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"
] | 1,582 | 1,588 | 1,588 | MEMBER | null | Using `TransfomerXLTokenizer.from_pretrained()` when loading from `.save_pretrained()` generated files.
Python complains about missing <unknown> token:
```
line 175, in _build_from_file
raise ValueError("No <unkown> token in vocabulary")
ValueError: No <unkown> token in vocabulary
``` | {
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https://api.github.com/repos/huggingface/transformers/issues/2999 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2999/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2999/comments | https://api.github.com/repos/huggingface/transformers/issues/2999/events | https://github.com/huggingface/transformers/pull/2999 | 570,084,710 | MDExOlB1bGxSZXF1ZXN0Mzc5MTc3NjQz | 2,999 | Create README.md for the new model fine tuned for Spanish POS tagging | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2999?src=pr&el=h1) Report\n> Merging [#2999](https://codecov.io/gh/huggingface/transformers/pull/2999?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/8194df8e0cff8e5866ec2bcbda34e3892f10eb39?src=pr&el=desc) will **d... | 1,582 | 1,582 | 1,582 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/2998 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2998/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2998/comments | https://api.github.com/repos/huggingface/transformers/issues/2998/events | https://github.com/huggingface/transformers/pull/2998 | 570,075,765 | MDExOlB1bGxSZXF1ZXN0Mzc5MTY5ODUw | 2,998 | kwargs are passed to both model and configuration in AutoModels | {
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https://api.github.com/repos/huggingface/transformers/issues/2997 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2997/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2997/comments | https://api.github.com/repos/huggingface/transformers/issues/2997/events | https://github.com/huggingface/transformers/pull/2997 | 570,066,443 | MDExOlB1bGxSZXF1ZXN0Mzc5MTYxOTEz | 2,997 | add explaining example to XLNet LM modeling | {
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"> Cool! Indeed, if I remember the paper correctly there is no need to shift the labels. Maybe we could update the [associated docstring](https://github.com/huggingface/transformers/blob/master/src/transformers/modeling_xlnet.py#L980-L985) to make sure no one gets confused again?\r\n\r\nDone :-) ",
"# [Codecov](h... | 1,582 | 1,582 | 1,582 | MEMBER | null | 1) adds example explaining how XLNet could be used for standard auto-regressive modelling.
2) puts add_special_tokens=True for simple example to make sure no <sep> and <cls> are added to input. The are used for special training (similar to BERT) and might be confusing to user | {
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https://api.github.com/repos/huggingface/transformers/issues/2996 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2996/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2996/comments | https://api.github.com/repos/huggingface/transformers/issues/2996/events | https://github.com/huggingface/transformers/issues/2996 | 570,040,360 | MDU6SXNzdWU1NzAwNDAzNjA= | 2,996 | Trying to Use AlbertTokenizer With my own custom Vocab file | {
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"Hi, our Albert implementation only handles SentencePiece vocabulary.",
"Thank you for your response. I tried generating a sentencepiece vocab model via ..**_spm.SentencePieceTrainer.Train('--input=ALBERT_PEP3V.txt\r\n--model_prefix=albertv1 --vocab_size=10000 --hard_vocab_limit=False')_**....and a model is succ... | 1,582 | 1,594 | 1,594 | 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/2995 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2995/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2995/comments | https://api.github.com/repos/huggingface/transformers/issues/2995/events | https://github.com/huggingface/transformers/issues/2995 | 569,934,996 | MDU6SXNzdWU1Njk5MzQ5OTY= | 2,995 | No optimizer steps when gradient_accumulation_steps smaller than epoch_iterator length | {
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"In this scenario, the user would do a single optimizer step over the whole batch?\r\n\r\nSure, we would welcome a PR! Could you add a comment as well, so that the purpose of this line may be clear for the user?",
"After the change we would do a single optimizer step over each *epoch*.\r\nAdded a comment and crea... | 1,582 | 1,584 | 1,584 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Doesn't matter.
Language I am using the model on (English, Chinese ...): Doesn't matter.
The problem arises when using:
* [x] the official example scripts
* [ ] my own modified scripts
The tasks I am working on is:
* [x] an official GLUE/SQUa... | {
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"Hi! Indeed, there have been a few issues as this was the first release incorporating `tokenizers` by default. A new version of `tokenizers` and `transformers` will be available either today or tomorrow and should fix most of these.",
"For future reference, when you say that some code \"fails\", please also provi... | 1,582 | 1,587 | 1,583 | NONE | null | 1. It cannot be installed on MacOS. By runing `pip install -U transformers`, I got the following errors:
> Building wheels for collected packages: tokenizers
> Building wheel for tokenizers (PEP 517) ... error
> ERROR: Command errored out with exit status 1:
> command: /anaconda/bin/python /anaconda/lib/py... | {
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https://api.github.com/repos/huggingface/transformers/issues/2992 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2992/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2992/comments | https://api.github.com/repos/huggingface/transformers/issues/2992/events | https://github.com/huggingface/transformers/issues/2992 | 569,856,054 | MDU6SXNzdWU1Njk4NTYwNTQ= | 2,992 | Train TFXLNetForSequenceClassification model failed. | {
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Train TFXLNetForSequenceClassification model failed.
## Details
**train_dataset,dev_dataset:**
`<RepeatDataset shapes: ({input_ids: (None, None), attention_mask: (None, None), token_type_ids: (None, None)}, (None,)), types: ({input_ids: tf.int32, attention_mask: tf.int32, token_type_ids: tf... | {
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https://api.github.com/repos/huggingface/transformers/issues/2991 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2991/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2991/comments | https://api.github.com/repos/huggingface/transformers/issues/2991/events | https://github.com/huggingface/transformers/pull/2991 | 569,834,572 | MDExOlB1bGxSZXF1ZXN0Mzc4OTcyMDYx | 2,991 | run_ner.py / bert-base-multilingual-cased can output empty tokens | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2991?src=pr&el=h1) Report\n> Merging [#2991](https://codecov.io/gh/huggingface/transformers/pull/2991?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/38f5fe9e0277df67a01db80a1c640ac072a2381e?src=pr&el=desc) will **d... | 1,582 | 1,585 | 1,585 | MEMBER | null | This can happen when using bert-base-multilingual-cased with an input containing an unique space.
In this case, the tokenizer will output just an empty word_tokens thus leading to an non-consistent behavior
over the labels_ids tokens adding one more tokens than tokens vector. | {
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https://api.github.com/repos/huggingface/transformers/issues/2990 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2990/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2990/comments | https://api.github.com/repos/huggingface/transformers/issues/2990/events | https://github.com/huggingface/transformers/issues/2990 | 569,711,675 | MDU6SXNzdWU1Njk3MTE2NzU= | 2,990 | run_ner.py example | {
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"Are you looking for this? https://github.com/huggingface/transformers/blob/master/examples/ner/run_ner.py",
"On a (somewhat) related note: the code might still be there but on huggingface's webpage the following link doesn't point to anything: https://huggingface.co/transformers/examples.html#named-entity-recogn... | 1,582 | 1,589 | 1,582 | CONTRIBUTOR | null | # ❓ Questions & Help
## Details
It seem that examples/run_ner.py has been removed from github repo. Is there any issue with this code?
Thanks | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2989?src=pr&el=h1) Report\n> Merging [#2989](https://codecov.io/gh/huggingface/transformers/pull/2989?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/c913eb9c3894b4031dc059d22b42e38a5fcef989?src=pr&el=desc) will **i... | 1,582 | 1,651 | 1,582 | MEMBER | null | Updating documentation for tokenizers.
~Still left to do:~ will do in a future PR | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2988?src=pr&el=h1) Report\n> Merging [#2988](https://codecov.io/gh/huggingface/transformers/pull/2988?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/38f5fe9e0277df67a01db80a1c640ac072a2381e?src=pr&el=desc) will **d... | 1,582 | 1,588 | 1,585 | CONTRIBUTOR | null | Currently, the implementation of the GELU activation uses several unfused pointwise operations. In my experiments, computing this activation takes about 10% of forward time for GPT2-like networks for inputs of size similar to (32,128). This PR speeds up the execution of gelu_new during both forward (~3-5x) and backward... | {
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https://api.github.com/repos/huggingface/transformers/issues/2987 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2987/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2987/comments | https://api.github.com/repos/huggingface/transformers/issues/2987/events | https://github.com/huggingface/transformers/pull/2987 | 569,575,777 | MDExOlB1bGxSZXF1ZXN0Mzc4NzYzMDQ3 | 2,987 | Add preprocessing step for transfo-xl tokenization to avoid tokenizing words followed by punction to <unk> | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2987?src=pr&el=h1) Report\n> Merging [#2987](https://codecov.io/gh/huggingface/transformers/pull/2987?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/129f0604acb9e8b9cebd2897437324198fa37a0a?src=pr&el=desc) will **i... | 1,582 | 1,584 | 1,582 | MEMBER | null | The problem is well shown in Issue #2000 .
This PR adds a preprocessing step to transfo-xl tokenization to better deal with the problem.
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"Hi there. A few weeks or months ago, I wrote this notebook to introduce my colleagues to doing inference on LMs. In other words: how can I get a sentence representation out of them. You can have a look [here](https://github.com/BramVanroy/bert-for-inference/blob/master/introduction-to-bert.ipynb). It should be sel... | 1,582 | 1,596 | 1,582 | NONE | null | I know the stanford operation.
```python
tokenizer = RobertaTokenizer.from_pretrained('roberta-large')
model = RobertaModel.from_pretrained('roberta-large')
input_ids = torch.tensor(tokenizer.encode("Hello, my <span class="highlighter highlight-on">dog</span> is cute", add_special_tokens=True)).unsqueeze(0) # B... | {
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"Seems related to #2694",
"Indeed! I fixed the misleading documentation with #2998."
] | 1,582 | 1,582 | 1,582 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Bert (may apply to more)
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
The tasks I a... | {
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I tested NER fine-tuning on albert-base-v2, albert-large-v2 and albert-xlarge-v2 on the english CONLL 2003 dataset and they all get F1 of aro... | {
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https://api.github.com/repos/huggingface/transformers/issues/2982 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2982/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2982/comments | https://api.github.com/repos/huggingface/transformers/issues/2982/events | https://github.com/huggingface/transformers/pull/2982 | 569,545,742 | MDExOlB1bGxSZXF1ZXN0Mzc4NzQxODIy | 2,982 | Change masking to direct labeling for TPU support. | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2982?src=pr&el=h1) Report\n> Merging [#2982](https://codecov.io/gh/huggingface/transformers/pull/2982?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/d1ab1fab1be7199e082129dfbe46eb52bca92799?src=pr&el=desc) will **i... | 1,582 | 1,582 | 1,582 | CONTRIBUTOR | null | Torch XLA conversion is very sensitive to certain core pytorch operations. These result in TPU being slower than CPU operation. The most obvious are binary masking and calls to item().
https://github.com/pytorch/xla/blob/master/TROUBLESHOOTING.md
This PR replaces some of these calls that are in the example/NER p... | {
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https://api.github.com/repos/huggingface/transformers/issues/2981 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2981/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2981/comments | https://api.github.com/repos/huggingface/transformers/issues/2981/events | https://github.com/huggingface/transformers/issues/2981 | 569,525,918 | MDU6SXNzdWU1Njk1MjU5MTg= | 2,981 | Strange bug when Finetuning own pretrained model (with an even stranger solution) | {
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"Hi! This is an interesting use-case, I think the error stems from the `run_glue` script trying to re-use the different attributes the `run_language_modeling` script had saved.\r\n\r\nThat includes:\r\n- the optimizer state\r\n- the scheduler state\r\n- the current global step, which is inferred from the name\r\n\r... | 1,582 | 1,592 | 1,592 | NONE | null | # 🐛 Bug
## Information
Roberta
Language I am using the model on (English, Chinese ...): Latin script(migh have a mix of languages)
The problem arises when using:
run_glue on model obtained from run_language_modeling
The tasks I am working on is:
Sequence Classification(single)
Steps to reproduce th... | {
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https://api.github.com/repos/huggingface/transformers/issues/2980 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2980/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2980/comments | https://api.github.com/repos/huggingface/transformers/issues/2980/events | https://github.com/huggingface/transformers/issues/2980 | 569,518,803 | MDU6SXNzdWU1Njk1MTg4MDM= | 2,980 | Cannot install Transformers version >2.3.0 with pip on CentOS | {
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"Which version of Rust are you on? Looking at the trace [PyO3 ](https://pyo3.rs/v0.9.0-alpha.1/)requires at least 1.37.0-nightly 2019-07-19.",
"I am on version `1.41.0`",
"Interestingly, their website says 1.37.x is the requirement, but [on GitHub](https://github.com/PyO3/pyo3#usage) they say you need 1.42.0-ni... | 1,582 | 1,705 | 1,588 | CONTRIBUTOR | null | # 🐛 Bug
I cannot install `pip install transformers` for a release newer than `2.3.0`. The install errors out when trying to install `tokenizers`. This is similar to [another issue](https://github.com/huggingface/transformers/issues/2831), except I have a Rust Compiler in my environment so I do not see: `"error: can... | {
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https://api.github.com/repos/huggingface/transformers/issues/2979 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2979/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2979/comments | https://api.github.com/repos/huggingface/transformers/issues/2979/events | https://github.com/huggingface/transformers/issues/2979 | 569,504,848 | MDU6SXNzdWU1Njk1MDQ4NDg= | 2,979 | Question about output pipeline(feature-extraction) | {
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I'm new to python and transformers so please bare with me. I have the following code to use the pipeline wrapper of transformers.
```
from transformers import (
pipeline
)
import h5py
nlp = pipeline('feature-extraction', model='bert-base-cased', config='bert-base-cased', tokenizer='bert-base-cased'... | {
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https://api.github.com/repos/huggingface/transformers/issues/2978 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2978/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2978/comments | https://api.github.com/repos/huggingface/transformers/issues/2978/events | https://github.com/huggingface/transformers/issues/2978 | 569,483,225 | MDU6SXNzdWU1Njk0ODMyMjU= | 2,978 | unreadable codes in for utils_glue | {
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"Hi, thank you for your comment. Github allows you to look at older versions of the [code](https://github.com/huggingface/transformers/blob/v1.0.0/examples/utils_glue.py)."
] | 1,582 | 1,582 | 1,582 | NONE | null | Hi
Previously the function "convert_examples_to_features" was implemented very nicely, and now this is implemented with so many nested function calls, which are all very hard to read and IMO unreadable codes. Could you return this implementation back to previous readable version?
thanks | {
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https://api.github.com/repos/huggingface/transformers/issues/2977 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2977/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2977/comments | https://api.github.com/repos/huggingface/transformers/issues/2977/events | https://github.com/huggingface/transformers/pull/2977 | 569,462,503 | MDExOlB1bGxSZXF1ZXN0Mzc4NjgyMTcz | 2,977 | Fix for case of multi-gpu | {
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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"
] | 1,582 | 1,588 | 1,588 | CONTRIBUTOR | null | When loading the optimizer and the scheduler in a multi gpu, the loading will put the optimizer and scheduler in cuda:0, it might not have enough mem to temporary store them (until the to.device below). | {
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https://api.github.com/repos/huggingface/transformers/issues/2976 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2976/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2976/comments | https://api.github.com/repos/huggingface/transformers/issues/2976/events | https://github.com/huggingface/transformers/issues/2976 | 569,441,565 | MDU6SXNzdWU1Njk0NDE1NjU= | 2,976 | XLMRobertaTokenizer vocab size | {
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"Running the following code caused error for me: \r\n\r\n> import transformers\r\n> tokenizer = transformers.AutoTokenizer.from_pretrained(\"xlm-roberta-base\")\r\n> tokenizer.convert_ids_to_tokens(range(tokenizer.vocab_size))\r\n\r\nActually, the `tokenizer.vocab_size` is `250005`, the last id `250004` is `<mask>`... | 1,582 | 1,593 | 1,593 | NONE | null | I think the XLMRobertaTokenizer vocab_size is off. Currently double counts ```'<unk>' | '<s>' | '</s>'```
Maybe change it to
```
def vocab_size(self):
return len(self.sp_model) + self.fairseq_offset
```
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https://api.github.com/repos/huggingface/transformers/issues/2975 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2975/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2975/comments | https://api.github.com/repos/huggingface/transformers/issues/2975/events | https://github.com/huggingface/transformers/issues/2975 | 569,441,134 | MDU6SXNzdWU1Njk0NDExMzQ= | 2,975 | GPT2 always has largest attention on first token? | {
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"Hi @sysu-zjw, this is indeed a very interesting observation that you made! \r\nOne thing to notice first is that GPT2 uses casual masking. So when looking at the attention weights ( corresponding to your variable `last_layer_attns_per_head` which I think should actually be called `last_layer_attns_avg_over_heads` ... | 1,582 | 1,582 | 1,582 | NONE | null | I am trying to print attentions from GPT2 model, and find something strange.
```
import torch
from transformers import *
device = torch.device("cuda")
tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
config = GPT2Config.from_pretrained("gpt2", output_attentions=True)
model = GPT2LMHeadModel.from_pretrained(... | {
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https://api.github.com/repos/huggingface/transformers/issues/2974 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2974/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2974/comments | https://api.github.com/repos/huggingface/transformers/issues/2974/events | https://github.com/huggingface/transformers/pull/2974 | 569,409,127 | MDExOlB1bGxSZXF1ZXN0Mzc4NjQyODI5 | 2,974 | New CLI using Typer | {
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"Closing as discussed in https://github.com/huggingface/transformers/issues/2959#issuecomment-619214142"
] | 1,582 | 1,587 | 1,587 | NONE | null | ## Summary
First pass at a New CLI using [Typer](https://typer.tiangolo.com/)
**745** total lines of code vs 917 for the old CLI, only adding one (optional) dependency (Typer) which is well documented/supported and has 99% test coverage.
Currently, this mostly keeps the same option names for each command but I thi... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2973?src=pr&el=h1) Report\n> Merging [#2973](https://codecov.io/gh/huggingface/transformers/pull/2973?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/c36416e53c29da8b6193f4a36d7b024c5f513495?src=pr&el=desc) will **i... | 1,582 | 1,582 | 1,582 | MEMBER | null | Spoiler alert: it wasn't.
closes #2960
closes #2658
closes #2654 | {
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"There isn't a way to retrieve that from the current API, but feel free to clone the repository and modify it to fit your needs.",
"Hello,\r\n\r\nThank you for your reply. Can I make a request to the Hugging Face so that the code can be modified for users to extract ```self.merge_heads(a)``` and ```self.c_proj(a)... | 1,582 | 1,588 | 1,588 | NONE | null | Hello,
Is there any way that I can extract the output of the ```self.merge_heads(a)``` and the ```self.c_proj(a)``` from the forward function for the Hugging Face GPT-2, which are found[ here](https://github.com/huggingface/transformers/blob/73028c5df0c28ca179fbe565482a9c2143787f61/src/transformers/modeling_gpt2.py#... | {
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Miss-order in the function call.
In line 785 of modeling_transfo_xl.py you call the ``new_mems = self._update_mems(hids, mems, mlen, qlen)``. Yet, the function declaration is ``def _update_mems(self, hids, mems, qlen, mlen)``
Apparently you invert the order of ``qlen`` and ``mlen``.
Yet the training p... | {
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## Information
Model I am using (Bert, XLNet ...): Bert
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [X ] my own modified scripts: (give details below)
The tasks I am working on is:
*... | {
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"Closing as discussed in https://github.com/huggingface/transformers/issues/2959#issuecomment-619214142"
] | 1,582 | 1,587 | 1,587 | NONE | null | This doesn't update dependencies on purpose. This is just meant to demonstrate migrating an example from using argparse to using Typer.
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https://api.github.com/repos/huggingface/transformers/issues/2961 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2961/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2961/comments | https://api.github.com/repos/huggingface/transformers/issues/2961/events | https://github.com/huggingface/transformers/pull/2961 | 569,242,251 | MDExOlB1bGxSZXF1ZXN0Mzc4NTIwNDcz | 2,961 | Fix max_length not taken into account when using pad_to_max_length on fast tokenizers | {
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"Should fix #2950",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2961?src=pr&el=h1) Report\n> Merging [#2961](https://codecov.io/gh/huggingface/transformers/pull/2961?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/94ff2d6ee8280c5595b92c1128c0f18e44925e56?sr... | 1,582 | 1,582 | 1,582 | MEMBER | null | On fast tokenizer calling encode/ encode_plus / batch_encode_plus was not taking into account max_length when setting the padding strategy. | {
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input_p = tokenizer_p.batch_encode_plus(
["This is a simple input 1", "This is a simple input 2"],
max_length=15,
pad_to_max_length=True
)
```
Output is not padded | {
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https://api.github.com/repos/huggingface/transformers/issues/2959 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2959/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2959/comments | https://api.github.com/repos/huggingface/transformers/issues/2959/events | https://github.com/huggingface/transformers/issues/2959 | 569,224,311 | MDU6SXNzdWU1NjkyMjQzMTE= | 2,959 | Switching from argparse to Typer | {
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"Looks like [sacremoses](https://github.com/alvations/sacremoses) already uses [Click](https://click.palletsprojects.com/en/7.x/) as a dependency so using Typer would be ideal as it's only dependency is Click and it provides a much nicer interface than Click using Python 3.6+ Type Hints",
"Also, since Typer is us... | 1,582 | 1,587 | 1,587 | NONE | null | # 🚀 Feature request
I'm pretty new to transformers and I'm finding the examples a bit hard to read. Mainly I think this is due to argparse being so verbose. Is there any interest in migrating to something like [Plac](https://micheles.github.io/plac/) or even better [Typer](https://typer.tiangolo.com/)?
I think it ... | {
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"This is a known issue (cf. https://github.com/huggingface/transformers/pull/2928). It will be fixed in another (cleaner) PR, though."
] | 1,582 | 1,582 | 1,582 | NONE | null | # 🐛 Bug
According to this PR #2521, a link is created between the linear layer bias and the model attribute bias in `BertLMPredictionHead`. In the `__init__`:
```python
self.decoder = nn.Linear(config.hidden_size, config.vocab_size, bias=False)
self.bias = nn.Parameter(torch.zeros(config.vocab_size))
self.decod... | {
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https://api.github.com/repos/huggingface/transformers/issues/2956 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2956/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2956/comments | https://api.github.com/repos/huggingface/transformers/issues/2956/events | https://github.com/huggingface/transformers/pull/2956 | 569,188,312 | MDExOlB1bGxSZXF1ZXN0Mzc4NDc2MDA5 | 2,956 | adding support for commonsense qa for multiple choice question answering | {
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"Can somebody help me in fixing the failed test?",
"Hi, thanks for your addition, that's really cool! Did you check the [contributions guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md#start-contributing-pull-requests)?\r\n\r\nYou should make sure you have the correct versions of... | 1,582 | 1,588 | 1,588 | NONE | null | {
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https://api.github.com/repos/huggingface/transformers/issues/2955 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2955/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2955/comments | https://api.github.com/repos/huggingface/transformers/issues/2955/events | https://github.com/huggingface/transformers/pull/2955 | 569,181,977 | MDExOlB1bGxSZXF1ZXN0Mzc4NDcwNjg4 | 2,955 | Only use F.gelu for torch >=1.4.0 | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2955?src=pr&el=h1) Report\n> Merging [#2955](https://codecov.io/gh/huggingface/transformers/pull/2955?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/3e98f27e4a9bb0ac3d0fe24b94d30da42cdae8a7?src=pr&el=desc) will **d... | 1,582 | 1,583 | 1,582 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/2954 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2954/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2954/comments | https://api.github.com/repos/huggingface/transformers/issues/2954/events | https://github.com/huggingface/transformers/issues/2954 | 569,171,746 | MDU6SXNzdWU1NjkxNzE3NDY= | 2,954 | Distillation throws CUDA out of memory even with available GPU memory | {
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"An error trace would be useful.",
"> An error trace would be useful.\r\n\r\nThis is an error trace:\r\n\r\nF.softmax(t_logits_slct / self.temperature, dim=-1),\r\n File \"/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py\", line 550, in __call__\r\n result = self.forward(*input, **kwargs)\r\n... | 1,582 | 1,628 | 1,590 | NONE | null | # ❓ Questions & Help
## Details
<!-- Description of your issue -->
Hi! I am trying to run the distillation of XLM-Roberta to Albert (also little XLM-Roberta) on 4 GPUs (RTX 2080 Ti) after a bit of correction of the distillation script, so the training process goes through little chunks of dataset due to the diffic... | {
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"You need to tell the model that you wish to get all the hidden states\r\n\r\n```python\r\nmodel = BertModel.from_pretrained('bert-base-uncased', output_hidden_states=True)\r\n```\r\n\r\nThen, you'll find your expected output as the third item in the output tuple:\r\n```python\r\n encoded_layers = model(tokens_tens... | 1,582 | 1,582 | 1,582 | NONE | null | I'm having trouble migrating my code from `pytorch_pretrained_bert` to `pytorch_transformers`. I'm attempting to run a cosine similarity exercise. I want to extract text embeddings values of the second-to-last of the 12 hidden embedding layer.
```
import torch
from pytorch_pretrained_bert import BertTokenizer, ... | {
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"It is weird that there is a discrepancy between Windows and Linux.\r\n\r\nCould you try casting your variables `b_input_ids`, `b_input_mask` and `b_labels` to `torch.long`?\r\n\r\nAre you defining some of your variables on GPU? Does it fail if everything stays on CPU?",
"I often prototype on Windows and push to ... | 1,582 | 1,658 | 1,588 | NONE | null | # 🐛 Bug
```
File "C:\Users\temp\Aida\aida\agents\bertbot\Bert\bert_intent_classifier_pytorch.py", line 298, in process
logits = self.model(prediction_inputs, token_type_ids=None, attention_mask=prediction_masks)
File "C:\Users\temp\Anaconda3\envs\fresh\lib\site-packages\torch\nn\modules\module.py", line 53... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2951?src=pr&el=h1) Report\n> Merging [#2951](https://codecov.io/gh/huggingface/transformers/pull/2951?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/3e98f27e4a9bb0ac3d0fe24b94d30da42cdae8a7?src=pr&el=desc) will **n... | 1,582 | 1,582 | 1,582 | CONTRIBUTOR | null | Add image | {
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https://api.github.com/repos/huggingface/transformers/issues/2950 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2950/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2950/comments | https://api.github.com/repos/huggingface/transformers/issues/2950/events | https://github.com/huggingface/transformers/issues/2950 | 569,016,025 | MDU6SXNzdWU1NjkwMTYwMjU= | 2,950 | BertTokenizerFast ignores `pad_to_max_length` | {
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"Duplicate of #2947",
"Thanks @ranamihir @fte10kso, \r\n\r\nI'll have a look today. ",
"Thanks @mfuntowicz!"
] | 1,582 | 1,582 | 1,582 | NONE | null | # 🐛 Bug
Hi,
I noticed some strange behavior with the fast tokenizers in `v2.5.0`, which I think is a bug:
It seems `BertTokenizerFast` is ignoring the `pad_to_max_length` argument, as shown below:
```python
>>> from transformers import AutoTokenizer, BertTokenizer
>>> tok_auto = AutoTokenizer.from_pretrain... | {
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https://api.github.com/repos/huggingface/transformers/issues/2949 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2949/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2949/comments | https://api.github.com/repos/huggingface/transformers/issues/2949/events | https://github.com/huggingface/transformers/issues/2949 | 568,992,083 | MDU6SXNzdWU1Njg5OTIwODM= | 2,949 | Change the model type after fine-tuning? | {
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"Yes, you should be able to just load the finetuned model into another architecture. The weights of overlapping parameter names will be loaded, and the others will be ignored.",
"Awesome, thanks for the fast response ",
"Okay, I came across a followup question: \r\nSo from what I can tell, the pre-trained mode... | 1,582 | 1,611 | 1,588 | NONE | null | # ❓ Questions & Help
Is there a way in the transformer library to fine-tune a transformer on one downstream task and change to another model type (i.e. another downstream task architecture)?
An example:
We train a BertForQuestionAnswering model (with a linear layer for the span prediction in addition to the reg... | {
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"Please don't post screenshots. Post your code instead. Use code blocks to do that: https://help.github.com/en/github/writing-on-github/creating-and-highlighting-code-blocks",
"sorry, I changed\r\n",
"Could you give us the content of the `/share/nas165/Wendy/BERTYiChen2.0/trained_model/3371筆_word2Vec/config.jso... | 1,582 | 1,588 | 1,588 | NONE | null | # 🐛 Bug
## Information
Model I am using Bert:
Language I am using the model on (Chinese ):
The problem arises when using BertForSequenceClassification:
I want to Concatenation pooled_output and word2vec. I change the code of BertForSequenceClassification like this and successfully trained the model.
I us... | {
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https://api.github.com/repos/huggingface/transformers/issues/2947 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2947/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2947/comments | https://api.github.com/repos/huggingface/transformers/issues/2947/events | https://github.com/huggingface/transformers/issues/2947 | 568,939,750 | MDU6SXNzdWU1Njg5Mzk3NTA= | 2,947 | Fast tokenizers padding and prefix space | {
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"This should be fixed in master on commit cc6775cdf5b20ad382613d3bdbf0dd8364d23219.\r\n\r\nIf you want to give it a try, otherwise the first maintenance release will soon be live.",
"That fixed it for me, thank you!\r\n\r\nAlso figured out what i was doing wrong with `add_prefix_space`. Instead of passing it to e... | 1,582 | 1,582 | 1,582 | NONE | null | # 🐛 Bug
`pad_to_max_length=True` Doesn't seem to do anything when using fast tokenizers.
```python
tokenizer_roberta = RobertaTokenizer.from_pretrained('roberta-base')
tokenizer_roberta_fast = RobertaTokenizerFast.from_pretrained('roberta-base')
tokenizer_bert = BertTokenizer.from_pretrained('bert-base-uncase... | {
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"> `labels[~masked_indices] = -100 # We only compute loss on masked tokens`\r\n\r\n-100 is the default value that gets ignored by the PyTorch `CrossEntropyLoss` method. When doing masked language modeling, we only compute the loss on the masked tokens, as is said in the comment. \r\n\r\n> `Tokens with indices set t... | 1,582 | 1,637 | 1,582 | NONE | null | Recently I was using bert for my own project, and going through the function mask_tokens I found this line of code
`labels[~masked_indices] = -100 # We only compute loss on masked tokens`
I wonder why we do this?
like i get the part where we do
```
indices_replaced = torch.bernoulli(torch.full(labels.shape, 0... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2945?src=pr&el=h1) Report\n> Merging [#2945](https://codecov.io/gh/huggingface/transformers/pull/2945?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/53ce3854a16ad2a715bc6ac8af3e30c18b5a1d11?src=pr&el=desc) will **n... | 1,582 | 1,613 | 1,582 | CONTRIBUTOR | null | Fixes huggingface/transformers#2487 | {
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https://api.github.com/repos/huggingface/transformers/issues/2944 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2944/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2944/comments | https://api.github.com/repos/huggingface/transformers/issues/2944/events | https://github.com/huggingface/transformers/issues/2944 | 568,882,544 | MDU6SXNzdWU1Njg4ODI1NDQ= | 2,944 | output padding different to zero in embedding layer | {
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"Why? Typically, padding tokens are ignored in the model by the use of an attention mask. I don't understand why you want to only get the output of the embedding layer. (Perhaps you are confused with the good ol' word2vec embedding models, but you cannot/should not extract features from the embedding layer in a LM.... | 1,582 | 1,582 | 1,582 | NONE | null | # 🐛 Bug
On embedding layer, the token corresponding to the padding does not return 0.
## Information
Model I am using (Bert):
Language I am using the model on (English):
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details bel... | {
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"This is a duplicate of https://github.com/huggingface/transformers/issues/2940"
] | 1,582 | 1,582 | 1,582 | NONE | null | [gelu = getattr(F, "gelu", _gelu_python)](https://github.com/huggingface/transformers/blob/53ce3854a16ad2a715bc6ac8af3e30c18b5a1d11/src/transformers/activations.py#L21)
should be changed to:
```python
if torch.__version__ < '1.4.0':
gelu = _gelu_python
else:
gelu = getattr(F, "gelu", _gelu_python)
``... | {
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https://api.github.com/repos/huggingface/transformers/issues/2942 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2942/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2942/comments | https://api.github.com/repos/huggingface/transformers/issues/2942/events | https://github.com/huggingface/transformers/pull/2942 | 568,703,254 | MDExOlB1bGxSZXF1ZXN0Mzc4MDc3MTg1 | 2,942 | Create README.md for xlnet_large_squad | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2942?src=pr&el=h1) Report\n> Merging [#2942](https://codecov.io/gh/huggingface/transformers/pull/2942?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/53ce3854a16ad2a715bc6ac8af3e30c18b5a1d11?src=pr&el=desc) will **n... | 1,582 | 1,582 | 1,582 | CONTRIBUTOR | null | {
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"`scores = np.exp(outputs) / np.exp(outputs).sum(-1).reshape(-1,1)` works for me, but I'm not sure whether it breaks other things.",
"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",
"... | 1,582 | 1,588 | 1,588 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): pipeline("sentiment-analysis")
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
The tas... | {
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https://api.github.com/repos/huggingface/transformers/issues/2940 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2940/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2940/comments | https://api.github.com/repos/huggingface/transformers/issues/2940/events | https://github.com/huggingface/transformers/issues/2940 | 568,624,741 | MDU6SXNzdWU1Njg2MjQ3NDE= | 2,940 | BERT model breaks during FP16 Apex training on the latest update (2.5.0) - due to gelu function | {
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BERT breaks during FP16 training due to the gelu function.
```
File "/home/user/miniconda/envs/py36/lib/python3.6/site-packages/transformers/modeling_bert.py", line 407, in forward
hidden_states, attention_mask, head_mask[i], encoder_hidden_states, encoder_attention_mask
File "/home/user/miniconda... | {
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https://api.github.com/repos/huggingface/transformers/issues/2939 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2939/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2939/comments | https://api.github.com/repos/huggingface/transformers/issues/2939/events | https://github.com/huggingface/transformers/pull/2939 | 568,558,438 | MDExOlB1bGxSZXF1ZXN0Mzc3OTY0NDQ1 | 2,939 | Add standardized get_vocab method to tokenizers | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2939?src=pr&el=h1) Report\n> Merging [#2939](https://codecov.io/gh/huggingface/transformers/pull/2939?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ea8eba35e2984882c3cd522ff669eb8060941a94?src=pr&el=desc) will **d... | 1,582 | 1,598 | 1,582 | CONTRIBUTOR | null | This PR adds a `get_vocab` method to the `PretrainedTokenizers` to standardize extracting vocabularies from tokenizers.
Comments:
- I didn't do anything with fast tokenizers. cc'ing @mfuntowicz for his thoughts there.
- I opted to keep it a method rather than a `@property` in order to encourage users to primarily ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2938 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2938/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2938/comments | https://api.github.com/repos/huggingface/transformers/issues/2938/events | https://github.com/huggingface/transformers/issues/2938 | 568,557,334 | MDU6SXNzdWU1Njg1NTczMzQ= | 2,938 | OpenAIGPTDoubleHeadsModel throws CUDA OOM with large number of candidates | {
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"Isn't that to be expected? The large model just doesn't fit on your GPU's memory.",
"@BramVanroy is that expected behavior with just 1 training example though?\r\n\r\nI initially suspected that this is a training-specific behavior (due to the need to store gradients, etc.), so I decided to fix the number of cand... | 1,582 | 1,588 | 1,588 | NONE | null | # 🐛 Bug
I am trying to train the `OpenAIGPTDoubleHeadsModel`. I find that large number of candidates can cause CUDA OOM errors.
Case 1 (single training example with 67 candidates): CUDA OOM
```
input_ids.shape: torch.Size([1, 67, 275])
mc_token_ids.shape: torch.Size([1, 67])
lm_labels.shape: torch.Size([1, 6... | {
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https://api.github.com/repos/huggingface/transformers/issues/2937 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2937/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2937/comments | https://api.github.com/repos/huggingface/transformers/issues/2937/events | https://github.com/huggingface/transformers/pull/2937 | 568,546,409 | MDExOlB1bGxSZXF1ZXN0Mzc3OTU0NTc5 | 2,937 | Small fix: default args for torch-lightning | {
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https://api.github.com/repos/huggingface/transformers/issues/2936 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2936/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2936/comments | https://api.github.com/repos/huggingface/transformers/issues/2936/events | https://github.com/huggingface/transformers/issues/2936 | 568,530,878 | MDU6SXNzdWU1Njg1MzA4Nzg= | 2,936 | New tokenizers issue in NER demo | {
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"This might be https://github.com/huggingface/transformers/issues/2917",
"@srush I'm looking at it right now ",
"I have the same issue while running run_tf_ner.py on the German NER dataset. I got the same AssertionError as below:\r\n> File \"run_tf_ner.py\", line 655, in <module>\r\n> app.run(main)\r\n> ... | 1,582 | 1,592 | 1,592 | CONTRIBUTOR | null | # 🐛 Bug
When I use transformers 2.5 I get the following error when running the run_ner demo. It seems to work from when I use 2.4. I am guessing this is because of a slight difference in the tokenization script? It seems to fail even when running with the base German run.sh in the ner/ directory.
```Traceback (... | {
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https://api.github.com/repos/huggingface/transformers/issues/2935 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2935/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2935/comments | https://api.github.com/repos/huggingface/transformers/issues/2935/events | https://github.com/huggingface/transformers/pull/2935 | 568,482,750 | MDExOlB1bGxSZXF1ZXN0Mzc3OTA0MTEx | 2,935 | Optimized squad.py multi-threading | {
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"This was a big performance hiccup for us. We managed to take a `QuestionAnswerAnsweringPipeline` down from 12 seconds to 6 seconds (with CUDA) and then to ~1 second (with the serialization removal optimization).",
"The code quality check is literally just that one line is too long.",
"> The code quality check ... | 1,582 | 1,595 | 1,588 | NONE | null | If there are few examples, don't bother multi-threading . The base cost of multi-threading in Python is expensive. I can't upload a picture of the call-stack visual profile because of my stupid company firewall, but multi-threading in python depends on serializing each object before sending it off. That process has a 5... | {
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https://api.github.com/repos/huggingface/transformers/issues/2934 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2934/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2934/comments | https://api.github.com/repos/huggingface/transformers/issues/2934/events | https://github.com/huggingface/transformers/pull/2934 | 568,460,504 | MDExOlB1bGxSZXF1ZXN0Mzc3ODg2NDM2 | 2,934 | Update README.md | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2934?src=pr&el=h1) Report\n> Merging [#2934](https://codecov.io/gh/huggingface/transformers/pull/2934?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e2a6445ebbc36121817c1f605d9a09a335f5fba5?src=pr&el=desc) will **n... | 1,582 | 1,582 | 1,582 | CONTRIBUTOR | null | - I added an example using the model with pipelines to show that we have set```{"use_fast": False}``` in the tokenizer for Q&A as noticed in [issue](https://github.com/huggingface/transformers/issues/2920)
- I added a Colab to play with the model and pipelines
- I added a Colab to discover Huggingface pipelines at th... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2933?src=pr&el=h1) Report\n> Merging [#2933](https://codecov.io/gh/huggingface/transformers/pull/2933?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/6a50d501ec54fd28eed57031ddbba6480768f9bc?src=pr&el=desc) will **d... | 1,582 | 1,651 | 1,582 | MEMBER | null | The name of generated file doesn't match between tokenizers and transformers tokenizers, so transformers is not able to load model saved with tokenizers models. | {
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https://api.github.com/repos/huggingface/transformers/issues/2932 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2932/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2932/comments | https://api.github.com/repos/huggingface/transformers/issues/2932/events | https://github.com/huggingface/transformers/pull/2932 | 568,388,811 | MDExOlB1bGxSZXF1ZXN0Mzc3ODI3Nzc5 | 2,932 | [WIP] Add a trainer tool class to make the TF2 model training easier | {
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I decided to open a cleaner PR because the other was a bit too messy in my opinion. Here the features that this Trainer class will be able to handle:
- [x] Single / Multiple GPU training. Distributed is across GPUs in the same host. Distribution across multiple machines will be for a future version.
- [ ]... | {
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https://api.github.com/repos/huggingface/transformers/issues/2931 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2931/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2931/comments | https://api.github.com/repos/huggingface/transformers/issues/2931/events | https://github.com/huggingface/transformers/pull/2931 | 568,317,784 | MDExOlB1bGxSZXF1ZXN0Mzc3NzY5NzAx | 2,931 | Fix spell: EsperBERTo, not EspertBERTo | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2931?src=pr&el=h1) Report\n> Merging [#2931](https://codecov.io/gh/huggingface/transformers/pull/2931?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/d490b5d5003654f104af3abd0556e598335b5650?src=pr&el=desc) will **n... | 1,582 | 1,582 | 1,582 | CONTRIBUTOR | null | This misspelling almost drove me crazy :) | {
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https://api.github.com/repos/huggingface/transformers/issues/2930 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2930/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2930/comments | https://api.github.com/repos/huggingface/transformers/issues/2930/events | https://github.com/huggingface/transformers/pull/2930 | 568,284,544 | MDExOlB1bGxSZXF1ZXN0Mzc3NzQzMDc0 | 2,930 | Add local_files_only parameter to pretrained items | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2930?src=pr&el=h1) Report\n> Merging [#2930](https://codecov.io/gh/huggingface/transformers/pull/2930?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/59c23ad9c931ac4fe719abeb3c3851df046ef3a6?src=pr&el=desc) will **d... | 1,582 | 1,584 | 1,582 | COLLABORATOR | null | closes https://github.com/huggingface/transformers/issues/2867
Setting local_files_only=True disables outgoing traffic:
- etags are not looked up
- files are not downloaded (config, tokenizer, model)
An appropriate error is thrown when this argument may be the cause why a model cannot be loaded.
```python
i... | {
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https://api.github.com/repos/huggingface/transformers/issues/2929 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2929/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2929/comments | https://api.github.com/repos/huggingface/transformers/issues/2929/events | https://github.com/huggingface/transformers/issues/2929 | 568,281,258 | MDU6SXNzdWU1NjgyODEyNTg= | 2,929 | Getting the same results when evaluating Model2Model with different encoder inputs. | {
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"It's in the forward pass of the EncoderDecoder:\r\n\r\nhttps://github.com/huggingface/transformers/blob/d490b5d5003654f104af3abd0556e598335b5650/src/transformers/modeling_encoder_decoder.py#L205-L237",
"> It's in the forward pass of the EncoderDecoder:\r\n> \r\n> https://github.com/huggingface/transformers/blob/... | 1,582 | 1,582 | 1,582 | NONE | null | After fine-tuning the Model2Model with 'bert-base-uncased', I am getting the same losses values, no matter what is the encoder input. On the PreTrainedEncoderDecoder documentation, it's said that "During prediction, we perform one forward pass through the encoder,
and then perform several forward passes with... | {
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https://api.github.com/repos/huggingface/transformers/issues/2928 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2928/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2928/comments | https://api.github.com/repos/huggingface/transformers/issues/2928/events | https://github.com/huggingface/transformers/pull/2928 | 568,280,437 | MDExOlB1bGxSZXF1ZXN0Mzc3NzM5ODMw | 2,928 | Make RobertaForMaskedLM implementation identical to fairseq | {
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"TODO: https://github.com/huggingface/transformers/pull/2913#issuecomment-588508153",
"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2928?src=pr&el=h1) Report\n> Merging [#2928](https://codecov.io/gh/huggingface/transformers/pull/2928?src=pr&el=desc) into [master](https://codecov.io/gh/huggingfa... | 1,582 | 1,582 | 1,582 | COLLABORATOR | null | closes https://github.com/huggingface/transformers/issues/1874
The implementation of RoBERTa in `transformers` differs from the original implementation in [fairseq](https://github.com/pytorch/fairseq/tree/master/fairseq/models/roberta), as results showed (cf. https://github.com/huggingface/transformers/issues/1874).... | {
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https://api.github.com/repos/huggingface/transformers/issues/2927 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2927/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2927/comments | https://api.github.com/repos/huggingface/transformers/issues/2927/events | https://github.com/huggingface/transformers/issues/2927 | 568,225,778 | MDU6SXNzdWU1NjgyMjU3Nzg= | 2,927 | What does ## mean in the bert vocab? | {
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"This question is better suited for [Stack Overflow](https://stackoverflow.com/). Please ask similar questions there in the future.\r\n\r\nIt indicates that the token is a subword unit, i.e. part of a larger word. For instance, the word \"potatoes\" might be tokenised as \"po, ##ta, ##toes\". If you want to learn m... | 1,582 | 1,582 | 1,582 | NONE | null | What does ## mean in the bert vocab?
some words are starts with ##, such as ##a ##m ##er ##h ，I don't quite understand。 | {
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https://api.github.com/repos/huggingface/transformers/issues/2926 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2926/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2926/comments | https://api.github.com/repos/huggingface/transformers/issues/2926/events | https://github.com/huggingface/transformers/issues/2926 | 568,169,280 | MDU6SXNzdWU1NjgxNjkyODA= | 2,926 | Masked LM implementation details | {
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"The method from google-research/bert you're showing returns the loss. We don't return the loss with `TFBertForMaskedLM`, we return the output distribution over the vocabulary. You can then use this output distribution to compute the loss, with a cross entropy loss for example.",
"I see, thanks."
] | 1,582 | 1,583 | 1,583 | NONE | null | I read the source code of `TFBertMLMHead`, it seems that, this layer just predict the whole sequence, rather than predict the `MASKED` tokens.
`TFBertMLMHead` just do these things:
* transform the `hidden state` from the last encoder layer
* `predictions = tf.matmul(hidden_state, input_embedding_matrix)`, with s... | {
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https://api.github.com/repos/huggingface/transformers/issues/2925 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2925/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2925/comments | https://api.github.com/repos/huggingface/transformers/issues/2925/events | https://github.com/huggingface/transformers/issues/2925 | 568,156,444 | MDU6SXNzdWU1NjgxNTY0NDQ= | 2,925 | DistilRoberta Model fine tuning on Squad dataset | {
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"Hello @graviraja \r\nYou don't need to remove the `token_type_ids` for RoBERTa models. There is one matrix of token type and it has only one type (a matrix of 0).\r\nYou can remove the `do_lower_case` flag for RoBERTa models. The vocabulary is case sensitive.\r\nHave you tried WITHOUT GPU? (`CUDA_VISIBLE_DEVICES=\... | 1,582 | 1,588 | 1,588 | NONE | null | # 🐛 Bug
I am trying to train the **distilroberta-base** model on **SQuAD** dataset using distillation code. I have trained the Roberta model on SQuAD 2.0 dataset, so that I can use it as a teacher model. I am using the **distilroberta-base** model as student.
## Information
Model I am using : Roberta
Langu... | {
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https://api.github.com/repos/huggingface/transformers/issues/2924 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2924/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2924/comments | https://api.github.com/repos/huggingface/transformers/issues/2924/events | https://github.com/huggingface/transformers/pull/2924 | 568,151,234 | MDExOlB1bGxSZXF1ZXN0Mzc3NjMzMDkx | 2,924 | Update modeling_tf_utils.py | {
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"This is great, thanks @BramVanroy !!"
] | 1,582 | 1,582 | 1,582 | COLLABORATOR | null | Tensorflow does not use .eval() vs .train().
closes https://github.com/huggingface/transformers/issues/2906 | {
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https://api.github.com/repos/huggingface/transformers/issues/2923 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2923/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2923/comments | https://api.github.com/repos/huggingface/transformers/issues/2923/events | https://github.com/huggingface/transformers/issues/2923 | 568,139,724 | MDU6SXNzdWU1NjgxMzk3MjQ= | 2,923 | Loading tensorflow first and then loading transformers errors | {
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"The import error seems to originate here:\r\n\r\n> tensorflow/stream_executor/cuda/cuda_blas.cc:238] failed to create cublas handle: CUBLAS_STATUS_NOT_INITIALIZED\r\n\r\nCan you try the answers provided here:\r\n\r\nhttps://stackoverflow.com/questions/38303974/tensorflow-running-error-with-cublas\r\n\r\nBy the way... | 1,582 | 1,588 | 1,588 | NONE | null | # 🐛 Bug
## Information
Model I am using: Bert
Language I am using the model on (English, Chinese ...):
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [X] my own modified scripts: (give details below)
The tasks I am working on is:
* [ ] an official GLUE/SQUaD... | {
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https://api.github.com/repos/huggingface/transformers/issues/2922 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2922/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2922/comments | https://api.github.com/repos/huggingface/transformers/issues/2922/events | https://github.com/huggingface/transformers/pull/2922 | 568,138,533 | MDExOlB1bGxSZXF1ZXN0Mzc3NjIyOTY2 | 2,922 | Tokenizer fast warnings | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2922?src=pr&el=h1) Report\n> Merging [#2922](https://codecov.io/gh/huggingface/transformers/pull/2922?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/d490b5d5003654f104af3abd0556e598335b5650?src=pr&el=desc) will **d... | 1,582 | 1,582 | 1,582 | MEMBER | null | - Warning abut padding should not trigger so often now, especially when no padding strategy is provided by the user.
- RoberTa warning is now in RoberTaTokenizer, not GPT2 base class. | {
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https://api.github.com/repos/huggingface/transformers/issues/2921 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2921/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2921/comments | https://api.github.com/repos/huggingface/transformers/issues/2921/events | https://github.com/huggingface/transformers/pull/2921 | 568,123,135 | MDExOlB1bGxSZXF1ZXN0Mzc3NjEwMzMw | 2,921 | Expose all constructor parameters for BertTokenizerFast | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2921?src=pr&el=h1) Report\n> Merging [#2921](https://codecov.io/gh/huggingface/transformers/pull/2921?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/d490b5d5003654f104af3abd0556e598335b5650?src=pr&el=desc) will **n... | 1,582 | 1,582 | 1,582 | MEMBER | null | Signed-off-by: Morgan Funtowicz <morgan@huggingface.co> | {
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https://api.github.com/repos/huggingface/transformers/issues/2920 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2920/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2920/comments | https://api.github.com/repos/huggingface/transformers/issues/2920/events | https://github.com/huggingface/transformers/issues/2920 | 568,040,921 | MDU6SXNzdWU1NjgwNDA5MjE= | 2,920 | Error arises when using pipeline with community model | {
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"Hi @ankandrew, \r\n\r\nThanks for reporting the issue. Effectively, the QA pipeline is not compatible with fast tokenizers for technical reasons (and I'm currently working on a fix for this).\r\n\r\nAs a workaround for now, you can disable fast tokenizers when allocating the pipeline:\r\n\r\n```python\r\nnlp = pip... | 1,582 | 1,588 | 1,588 | NONE | null | # 🐛 Bug
## Information
Model I am using is: `mrm8488/distill-bert-base-spanish-wwm-cased-finetuned-spa-squad2-es`
Language I am using the model on: Spanish
The problem arises when using:
* [ ] the official example scripts:
* [x] my own modified scripts:
The tasks I am working on is:
* [ ] an official... | {
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https://api.github.com/repos/huggingface/transformers/issues/2919 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2919/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2919/comments | https://api.github.com/repos/huggingface/transformers/issues/2919/events | https://github.com/huggingface/transformers/issues/2919 | 567,947,425 | MDU6SXNzdWU1Njc5NDc0MjU= | 2,919 | Fast tokenizers ignore `add_special_tokens=False` | {
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"This works now (but I can't close the issue).",
"I see now that it works with some changes:\r\n\r\n```python\r\nfrom transformers import AutoTokenizer\r\n\r\npretrained_model_name = \"bert-base-cased\"\r\n\r\nfast_tokenizer = AutoTokenizer.from_pretrained(pretrained_model_name,\r\n add_special_tokens=Fals... | 1,582 | 1,587 | 1,587 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Bert
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
The tasks I am working on is:
* ... | {
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https://api.github.com/repos/huggingface/transformers/issues/2918 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2918/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2918/comments | https://api.github.com/repos/huggingface/transformers/issues/2918/events | https://github.com/huggingface/transformers/pull/2918 | 567,931,063 | MDExOlB1bGxSZXF1ZXN0Mzc3NDU0NTM4 | 2,918 | Fast Tokenizers save pretrained should return the list of generated file paths. | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/2918?src=pr&el=h1) Report\n> Merging [#2918](https://codecov.io/gh/huggingface/transformers/pull/2918?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/2708b44ee9c151a2cdb84620d295c997af6fa7f0?src=pr&el=desc) will **i... | 1,582 | 1,582 | 1,582 | MEMBER | null | {
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https://api.github.com/repos/huggingface/transformers/issues/2917 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/2917/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/2917/comments | https://api.github.com/repos/huggingface/transformers/issues/2917/events | https://github.com/huggingface/transformers/issues/2917 | 567,929,157 | MDU6SXNzdWU1Njc5MjkxNTc= | 2,917 | Breaking-change behavior in BERT tokenizer when stripping accents | {
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"Yeah, I found the same problem in my code. The \"encode\" won't add padding even \"pad_to_max_length = True\".",
"HI @bryant1410, \r\n\r\nThanks for reporting the issue. The parameter `strip_accents` was indeed enabled on `BertTokenizerFast`. \r\n\r\nI've a PR exposing the missing parameters https://github.com/h... | 1,582 | 1,594 | 1,593 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Bert (could happen with other ones, don't know)
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 ... | {
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"This is in process of being addressed at huggingface/blog#3\r\n\r\n(You'll need to tweak the code of `run_language_modeling.py`, this is not – yet – a code-free tutorial) "
] | 1,582 | 1,582 | 1,582 | CONTRIBUTOR | null | # ❓ Questions & Help
I'm attempting to build a LM following the tutorial here (https://huggingface.co/blog/how-to-train).
Unfortunately, it is incomplete. It shows how to create a custom `Dataset` but not how to execute `run_language_modeling.py` so that it is used.
**Any chance we can get the full script f... | {
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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"
] | 1,582 | 1,588 | 1,588 | NONE | null | # ❓ Questions
## Details
I am trying to train `GPT2DoubleHeadsModel` for the tasks of generation and multiple-choice selection. My dataset has examples with variable number of candidates - some examples have 10 candidates, some have 15, etc.
I wanted to be able to create a single `TensorDataset` object for my da... | {
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