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https://api.github.com/repos/huggingface/transformers/issues/5020 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5020/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5020/comments | https://api.github.com/repos/huggingface/transformers/issues/5020/events | https://github.com/huggingface/transformers/issues/5020 | 638,998,796 | MDU6SXNzdWU2Mzg5OTg3OTY= | 5,020 | Run error when run PPLM in example! | {
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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/5019 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5019/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5019/comments | https://api.github.com/repos/huggingface/transformers/issues/5019/events | https://github.com/huggingface/transformers/issues/5019 | 638,998,129 | MDU6SXNzdWU2Mzg5OTgxMjk= | 5,019 | Not able to reproduce XNLI results from Google's mBERT weights. | {
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"Edit: For some reason the model: xlm-mlm-tlm-xnli15-1024 (https://huggingface.co/transformers/pretrained_models.html), also doesn't learn properly. The train accuracy never goes beyond 0.35.\r\n\r\nFix for XLM is provided here: https://github.com/huggingface/transformers/pull/5035\r\n\r\nThe issue of mBERT (weight... | 1,592 | 1,598 | 1,598 | NONE | null | # 🐛 Bug
Hello,
I am using mBERT from https://github.com/google-research/bert/blob/master/multilingual.md and using it with the run_xnli.py file.
Language: Learning the model on English (en) and testing it on French (fr).
The problem arises when I download the mBERT's weights from: https://github.com/google-... | {
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https://api.github.com/repos/huggingface/transformers/issues/5018 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5018/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5018/comments | https://api.github.com/repos/huggingface/transformers/issues/5018/events | https://github.com/huggingface/transformers/issues/5018 | 638,989,851 | MDU6SXNzdWU2Mzg5ODk4NTE= | 5,018 | bart-large-xsum config task_specific_params['summarization_params'] wrong | {
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"set to `{}`"
] | 1,592 | 1,592 | 1,592 | CONTRIBUTOR | null | They are bart-large-cnn-params. | {
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https://api.github.com/repos/huggingface/transformers/issues/5017 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5017/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5017/comments | https://api.github.com/repos/huggingface/transformers/issues/5017/events | https://github.com/huggingface/transformers/issues/5017 | 638,941,743 | MDU6SXNzdWU2Mzg5NDE3NDM= | 5,017 | Add CRF layer after Transformer model | {
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"You can directly feed the output of a transformer's hidden states into a CRF implementation like this https://github.com/s14t284/TorchCRF\r\n\r\nHope it helps!",
"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 f... | 1,592 | 1,661 | 1,598 | NONE | null | I've read a paper titled "Named Entity Recognition in Chinese Electronic Medical Records Using Transformer-CRF".
It takes Transformer's output as CRF's input, as shown in the figure.
Which function could I use to implement it? model.add() doesn't work.
![Screenshot_20200615_173206_cn wps moffice_eng](https://user-... | {
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"Hi! This issue should have been solved by https://github.com/huggingface/transformers/pull/5116",
"Hi @LysandreJik: I just wanted to let you know that this issue is still not resolved as of v3.02. If you ensure the model files (and vocab, etc.) exist in the cache, and then you turn off wifi/internet, model loa... | 1,592 | 1,601 | 1,601 | NONE | null | # 🐛 Bug
## Information
For TF models in latest version of `transformers v2.11.0`, when the internet is turned off, `from_pretrained` throws an error even when the model has previously been downloaded to cache:
```python
# does not work (wifi/internet turned off)
model = TFBertModel.from_pretrained('bert-base-... | {
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https://api.github.com/repos/huggingface/transformers/issues/5015 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5015/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5015/comments | https://api.github.com/repos/huggingface/transformers/issues/5015/events | https://github.com/huggingface/transformers/pull/5015 | 638,920,444 | MDExOlB1bGxSZXF1ZXN0NDM0NTk1MTYz | 5,015 | Make DataCollator a callable | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5015?src=pr&el=h1) Report\n> Merging [#5015](https://codecov.io/gh/huggingface/transformers/pull/5015?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/66bcfbb130a3a60d873597fdca05a8d539ef3401&el=desc) will **increase... | 1,592 | 1,592 | 1,592 | COLLABORATOR | null | As discussed with @julien-c, change the `DataCollator` to be a callable (and the trainer now can take any function as data collator).
I removed the abstract class and made a type alias to keep the type annotations instead. | {
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https://api.github.com/repos/huggingface/transformers/issues/5014 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5014/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5014/comments | https://api.github.com/repos/huggingface/transformers/issues/5014/events | https://github.com/huggingface/transformers/pull/5014 | 638,910,201 | MDExOlB1bGxSZXF1ZXN0NDM0NTg2NzU5 | 5,014 | Add bart-base | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5014?src=pr&el=h1) Report\n> Merging [#5014](https://codecov.io/gh/huggingface/transformers/pull/5014?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/66bcfbb130a3a60d873597fdca05a8d539ef3401&el=desc) will **increase... | 1,592 | 1,592 | 1,592 | CONTRIBUTOR | null | Also adds two `@slow` integration test for fill mask tasks.
I made some guesses on the correct conversion, which will hopefully be confirmed by the authors in this [issue](https://github.com/pytorch/fairseq/issues/2242) | {
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https://api.github.com/repos/huggingface/transformers/issues/5010 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/5010/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/5010/comments | https://api.github.com/repos/huggingface/transformers/issues/5010/events | https://github.com/huggingface/transformers/issues/5010 | 638,806,360 | MDU6SXNzdWU2Mzg4MDYzNjA= | 5,010 | How can I print output attention on test data? | {
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"You should do it on the forward function of the model your are using so probably:\r\n```model = BartForConditionalGeneration.from_pretrained(\"bart-large\")\r\n model(input_ids, output_attentions=True)\r\n```"
] | 1,592 | 1,592 | 1,592 | 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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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5005?src=pr&el=h1) Report\n> Merging [#5005](https://codecov.io/gh/huggingface/transformers/pull/5005?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/9931f817b75ecb2c8bb08b6e9d4cbec4b0933935&el=desc) will **increase... | 1,592 | 1,592 | 1,592 | MEMBER | null | Supports all kind of models for all the pipelines we've except `summarization` because of `triu`not supported by ONNX. | {
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"Thanks for letting me know @patil-suraj !\r\n\r\nThis is almost done, blocked on 1 minor [issue](https://github.com/pytorch/fairseq/issues/2242)\r\n\r\nIf I don't get an answer there by Wednesday I will assume that the tokenizer is the same as bart.large and move forward.",
"Thanks @sshleifer for immediate resp... | 1,592 | 1,592 | 1,592 | MEMBER | null | # 🚀 Feature request
`bart-base` checkpoint is now available in fairseq repo
https://github.com/pytorch/fairseq/tree/master/examples/bart#pre-trained-models
so now it can be made available here `facebook/bart-base`
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"Just had to reinstall. I installed pytorch AFTER transformers, and I cloned the transformers repository. Just uninstalled and reinstalled with pip install transformers and the issue went away."
] | 1,592 | 1,592 | 1,592 | NONE | null | # 🐛 Bug
Can't import transformers, get a problem with signal.py. I see that an issue was recently fixed... should I install a nightly build, or...?
>>> import transformers
2020-06-15 05:40:54.098560: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101... | {
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"Reducing the batch size further doesn't raise this error. But a lot of RAM is left empty. If this is an issue, then RAM demand exceeded error should be raised.",
"I've seen this error, and think it happens right before `OutOfMemory`.\r\nI agree the traceback should be different.\r\nMarking wontfix for now since ... | 1,592 | 1,598 | 1,598 | CONTRIBUTOR | null | # 🐛 Bug
## Information
This bug/problem has been discussed on [Pytorch](https://github.com/pytorch/pytorch/issues/21819)/[Apex](https://github.com/NVIDIA/apex/issues/319) and [here](https://github.com/huggingface/transformers/issues/460) (bot marked it as stale) also.
I'm using Albert on GLUE (although this iss... | {
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"You would need to use `GPT2LMHeadModel` for that, and use a softmax layer to have scores. Here's an example:\r\n\r\n```py\r\nfrom transformers import GPT2LMHeadModel, GPT2Tokenizer\r\nimport torch\r\n\r\nmodel = GPT2LMHeadModel.from_pretrained(\"gpt2\")\r\ntokenizer = GPT2Tokenizer.from_pretrained(\"gpt2\")\r\n\r\... | 1,592 | 1,592 | 1,592 | NONE | null | I want to access the prediciton scores from the GPT2 model.
Follwoing the example given in the docstring, I am using the code
```
output = model(input_ids,labels=input_ids)
logit = output[1][0][-1,:].detach().numpy()
```
Is it correct ? I am expecting logit variable to be the same size as the vocabula... | {
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https://api.github.com/repos/huggingface/transformers/issues/4999 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4999/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4999/comments | https://api.github.com/repos/huggingface/transformers/issues/4999/events | https://github.com/huggingface/transformers/pull/4999 | 638,630,251 | MDExOlB1bGxSZXF1ZXN0NDM0MzU4MjIx | 4,999 | Improve ONNX logging | {
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https://api.github.com/repos/huggingface/transformers/issues/4998 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4998/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4998/comments | https://api.github.com/repos/huggingface/transformers/issues/4998/events | https://github.com/huggingface/transformers/pull/4998 | 638,622,488 | MDExOlB1bGxSZXF1ZXN0NDM0MzUxODU3 | 4,998 | Remove deprecation warning TF2.2 | {
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"The only CI message is :\r\n\r\n```\r\nwould reformat /home/circleci/transformers/src/transformers/trainer_tf.py\r\nOh no! 💥 💔 💥\r\n1 file would be reformatted, 299 files would be left unchanged.\r\n```\r\n\r\nHow can I see what to change to fit the code style ?",
"Thanks for the PR, but merging this, will re... | 1,592 | 1,592 | 1,592 | CONTRIBUTOR | null | `strategy.experimental_run_v2()` is deprecated in favor of `strategy.run()`
https://github.com/tensorflow/tensorflow/blob/2b96f3662bd776e277f86997659e61046b56c315/tensorflow/python/distribute/distribute_lib.py#L953-L957
Fix #4992 | {
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https://api.github.com/repos/huggingface/transformers/issues/4997 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4997/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4997/comments | https://api.github.com/repos/huggingface/transformers/issues/4997/events | https://github.com/huggingface/transformers/pull/4997 | 638,613,246 | MDExOlB1bGxSZXF1ZXN0NDM0MzQ0NDI3 | 4,997 | Fix importing transformers on Windows - SIGKILL not defined | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4997?src=pr&el=h1) Report\n> Merging [#4997](https://codecov.io/gh/huggingface/transformers/pull/4997?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/9931f817b75ecb2c8bb08b6e9d4cbec4b0933935&el=desc) will **increase... | 1,592 | 1,592 | 1,592 | MEMBER | null | On Windows platform there is no such `signal.SIGKILL`, we need to send `CTRL_C_EVENT` which is `Ctrl+C`.
This PR aims at:
1. Not importing the `signal.SIGKILL` on Windows platforms as it's undefined
2. Using the right `signal.CTRL_C_EVENT` on Windows platforms and `signal.SIGKILL` on Unix*. | {
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https://api.github.com/repos/huggingface/transformers/issues/4996 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4996/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4996/comments | https://api.github.com/repos/huggingface/transformers/issues/4996/events | https://github.com/huggingface/transformers/issues/4996 | 638,562,594 | MDU6SXNzdWU2Mzg1NjI1OTQ= | 4,996 | ❓ How to use TFTrainer on TPU ? Unable to destroy remote tensor handles | {
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"It seems to be related to the size of dataset : if I use `--training_steps` instead of `--num_epochs` I don't have the error.\r\n\r\n---\r\n\r\nBut a similar error appear at evaluation time :\r\n\r\n```\r\ntensorflow.python.framework.errors_impl.InvalidArgumentError: {{function_node __inference__evaluate_steps_517... | 1,592 | 1,598 | 1,598 | CONTRIBUTOR | null | # ❓ Questions & Help
I'm trying to train my model on TPU using `TFTrainer`. Training starts fine, but after a few training steps, I'm having this error :
> Unable to destroy remote tensor handles. If you are running a tf.function, it usually indicates some op in the graph gets an error: 4 root error(s) found.
... | {
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https://api.github.com/repos/huggingface/transformers/issues/4995 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4995/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4995/comments | https://api.github.com/repos/huggingface/transformers/issues/4995/events | https://github.com/huggingface/transformers/pull/4995 | 638,557,475 | MDExOlB1bGxSZXF1ZXN0NDM0Mjk4MzY2 | 4,995 | append keyword arguments to the output | {
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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"
] | 1,592 | 1,598 | 1,598 | CONTRIBUTOR | null | prepare_inputs_for_generation function receives keyword arguments (model_specific_kwargs)
However, these arguments are not ignored.
I fix this codes to return arguments including these keyword arguments.
Actually, I don't have an idea about the purpose of prepare_logits_for_generation function, which only returns ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4994 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4994/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4994/comments | https://api.github.com/repos/huggingface/transformers/issues/4994/events | https://github.com/huggingface/transformers/issues/4994 | 638,506,361 | MDU6SXNzdWU2Mzg1MDYzNjE= | 4,994 | 🐛 TFTrainer not working on TPU (TF2.2) | {
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"Currently as a work-around I set the optimizer as an attribute and remove the argument :\r\n\r\nAfter this line :\r\nhttps://github.com/huggingface/transformers/blob/9931f817b75ecb2c8bb08b6e9d4cbec4b0933935/src/transformers/trainer_tf.py#L235\r\n\r\nI add :\r\n\r\n```python\r\nself.optimizer = optimizer\r\n```\r\n... | 1,592 | 1,598 | 1,598 | CONTRIBUTOR | null | # 🐛 Bug
## Information
The problem arises when using:
* [ ] the official example scripts
* [x] my own modified scripts
The tasks I am working on is:
* [x] an official GLUE/SQUaD task: CNN/DM
* [ ] my own task or dataset
## To reproduce
Steps to reproduce the behavior:
1. Install `transformers` fr... | {
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https://api.github.com/repos/huggingface/transformers/issues/4993 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4993/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4993/comments | https://api.github.com/repos/huggingface/transformers/issues/4993/events | https://github.com/huggingface/transformers/issues/4993 | 638,504,383 | MDU6SXNzdWU2Mzg1MDQzODM= | 4,993 | Importing transformers causes segmentation fault when setting cuda device | {
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"Hey @jcyk, \r\n\r\nwhen trying to reproduce this error with PyTorch 1.5.0, there is no problem.\r\n\r\nHowever, when I run your code with PyTorch 1.4.0 (as you did), I get the following error: \r\n\r\n```python \r\n1.4.0\r\n2.11.0\r\nFalse\r\nTraceback (most recent call last):\r\n File \"./bug_4993.py\", line 16,... | 1,592 | 1,605 | 1,599 | NONE | null | # 🐛 Bug
## Information
The problem arises when using:
my own modified scripts: (give details below)
## To reproduce
```
import torch
import transformers
def main(local_rank):
torch.cuda.set_device(local_rank)
device = torch.device('cuda', local_rank)
if __name__ == "__main__":
print ... | {
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"closes by #4998"
] | 1,592 | 1,592 | 1,592 | CONTRIBUTOR | null | # 🐛 Bug
When running my code with TFTrainer, I'm receiving :
>WARNING - tensorflow - From /home/me/.venv/bart/lib/python3.6/site-packages/transformers/trainer_tf.py:355: StrategyBase.experimental_run_v2 (from tensorflow.python.distribute.distribute_lib) is deprecated and will be removed in a future version.
I... | {
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https://api.github.com/repos/huggingface/transformers/issues/4991 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4991/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4991/comments | https://api.github.com/repos/huggingface/transformers/issues/4991/events | https://github.com/huggingface/transformers/issues/4991 | 638,438,083 | MDU6SXNzdWU2Mzg0MzgwODM= | 4,991 | evaluating with trainer.py with TPU results in sudden RAM spike and crash | {
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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",
"Any update on this? I've got a similar issue "
] | 1,592 | 1,618 | 1,598 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Roberta with the official how to train from scratch example
Language I am using the model on (English, Chinese ...): Esperanto
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4990 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4990/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4990/comments | https://api.github.com/repos/huggingface/transformers/issues/4990/events | https://github.com/huggingface/transformers/issues/4990 | 638,417,369 | MDU6SXNzdWU2Mzg0MTczNjk= | 4,990 | Save the Dataset for training GPT2 | {
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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"
] | 1,592 | 1,598 | 1,598 | NONE | null | # ❓ Questions & Help
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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"
] | 1,592 | 1,598 | 1,598 | NONE | null | Hi,
For my experiments, I need to make some changes to the forward pass of Roberta sequence classification model. Thus, I copied **RobertaForSequenceClassification** from _modeling_roberta.py_ into a [separate file](https://github.com/kevinghst/mixmatch_from_scratch/blob/master/models_roberta.py) in my repo.
And ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4987 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4987/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4987/comments | https://api.github.com/repos/huggingface/transformers/issues/4987/events | https://github.com/huggingface/transformers/pull/4987 | 638,359,035 | MDExOlB1bGxSZXF1ZXN0NDM0MTQ5ODAy | 4,987 | Fix Inconsistent NER Grouping (Pipeline) | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4987?src=pr&el=h1) Report\n> Merging [#4987](https://codecov.io/gh/huggingface/transformers/pull/4987?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/58cca47c16149e43d1b516623d59e3c5d97f695e&el=desc) will **decrease... | 1,592 | 1,594 | 1,594 | CONTRIBUTOR | null | ### This PR solves issue #4816 by:
1. Applying entity grouping to similar entity types with different prefixes (i.e. `B` and `I`)
2. Ensuring that separate entities at the last filtered index are no longer excluded from grouping.
Running the sample script below (based on reference issue #4816) returns the expe... | {
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"The mistake is on me. I forgot to download the tokenizer😂",
"I am getting the same error. What exactly do you mean by download the tokenizer? Doesn't it come with the transformers package?",
"I think what he meant was that use used the class, and not the instance, to encode text. You should always initialize ... | 1,592 | 1,694 | 1,592 | NONE | null | # 🐛 Bug
## Information
Tokenizer I am using is BertTokenizer and I've also tried using AlbertTokenizer, but it does not have any effect. So I'm thinking that the bug is in the base tokenizer
Language I am using the model on is English, but I don't believe that's the issue.
The problem arises when using:
*... | {
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"You can pass embeddings to the model by using the `input_embeds` keyword argument:\r\n```\r\nresult = model(input_embeds=...)\r\n```\r\nThey should be if shape `batch_size, sequence_length, hidden_size)`.",
"Hi @sgugger \r\nI tried the following code snippet but it is giving an error\r\n<pre>\r\n from transfo... | 1,592 | 1,592 | 1,592 | NONE | null | # ❓ Questions & Help
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"I do not think generally there's a way of knowing that a given token is usually a sub-token vs. a complete \"word\"\r\n\r\nMaybe a heuristic could be to do some kind of greedy decoding, iteratively adding a second `<mask>` after the first filled one and checking if the output score is above a certain threshold/abo... | 1,592 | 1,598 | 1,598 | CONTRIBUTOR | null | # 🚀 . Feature request
Not sure exactly if this is a bug/feature request/ or just me not understanding correctly :).
I am trying to use the [FillMaskPipeline](https://github.com/huggingface/transformers/blob/master/src/transformers/pipelines.py#L739) but as far as I understand the pipeline returns a single word-piece... | {
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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"
] | 1,592 | 1,598 | 1,598 | NONE | null | # ❓ Questions & Help
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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"
] | 1,592 | 1,598 | 1,598 | NONE | null | I am trying to train Bert and XLM on my own data. But I found that it seems run_language_modelling.py only tokenizes input text into ids, but it doesn't create token_type_ids or langs for Bert or XLM.
`batch_encoding = tokenizer.batch_encode_plus(lines, add_special_tokens=True, max_length=block_size)`
`self.example... | {
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https://api.github.com/repos/huggingface/transformers/issues/4979 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4979/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4979/comments | https://api.github.com/repos/huggingface/transformers/issues/4979/events | https://github.com/huggingface/transformers/pull/4979 | 638,186,591 | MDExOlB1bGxSZXF1ZXN0NDM0MDIzODgx | 4,979 | Add Code Coverage and Black badges to README | {
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https://github.com/huggingface/transformers/blob/403d3098572ac308416653648456a940860da39e/.circleci/config.yml#L101 | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4978?src=pr&el=h1) Report\n> Merging [#4978](https://codecov.io/gh/huggingface/transformers/pull/4978?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/68e19f1c228c92d5d800533f558faff24b57127a&el=desc) will **increase... | 1,592 | 1,592 | 1,592 | CONTRIBUTOR | null | Attempts to close issue #3879 by refactoring all models to take in an extra argument `output_hidden_states` in the `forward()` method.
@patrickvonplaten | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4977?src=pr&el=h1) Report\n> Merging [#4977](https://codecov.io/gh/huggingface/transformers/pull/4977?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ca5e1cdf8e314288bd0242a531815a6c75d8178e&el=desc) will **decrease... | 1,592 | 1,592 | 1,592 | MEMBER | null | {
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1. Remove duplicate parameter docstring in class OpenAIGPTModel.
2. Fix docstring due to web page display problems. | {
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"Merging readme file. "
] | 1,592 | 1,592 | 1,592 | CONTRIBUTOR | null | {
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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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my dataset_info.json copy from https://github.com/tensorflow/datasets/b... | {
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"hi, did you find a solution to this problem?"
] | 1,592 | 1,595 | 1,592 | NONE | null | I am trying to use torch multiprocessing to parallelize the predictions from two separate huggingface distillbert classification models. It seems to be deadlocked at the prediction step. I am using python 3.6.5, torch 1.5.0 and huggingface transformers version 2.11.0. The output from running the code is
```
Tree enc... | {
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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"
] | 1,592 | 1,599 | 1,599 | CONTRIBUTOR | null | If checkpoint has additional weights, then the current code will fail to load ignoring those weights. | {
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"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n",
"I'd also be interested in this. The current distilgpt2 is great for use-cases that need cheap/fast compute, but distilled versions of t... | 1,592 | 1,652 | 1,598 | NONE | null | # Plans for distilgpt2-medium and distilgpt2-large
## Motivation
While distilgpt2 is useful, I was wondering if there are any plans to create a distilgpt2-medium and distilgpt2-large. I'm also wondering how the result of distilgpt2-medium compare to gpt2, and distilgpt2-large compare to gpt2-medium, in size and per... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4968?src=pr&el=h1) Report\n> Merging [#4968](https://codecov.io/gh/huggingface/transformers/pull/4968?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/439aa1d6e9c953069f75fc23c737221d0df2c977&el=desc) will **increase... | 1,592 | 1,592 | 1,592 | MEMBER | null | This PR adds Explain Like I'm Five scripts and models to Transformers.
The `examples/eli5` folder contains training code for the dense retriever and to fine-tune a BART model, the jupyter notebook for the [blog post](https://yjernite.github.io/lfqa.html), and the code for the live demo.
The RetriBert model impl... | {
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https://api.github.com/repos/huggingface/transformers/issues/4967 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4967/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4967/comments | https://api.github.com/repos/huggingface/transformers/issues/4967/events | https://github.com/huggingface/transformers/issues/4967 | 638,043,727 | MDU6SXNzdWU2MzgwNDM3Mjc= | 4,967 | Add Linformer model | {
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"Here is an pytorch implementation\r\nhttps://github.com/tatp22/linformer-pytorch",
"Just another implementation by the authors\r\nhttps://github.com/facebookresearch/pytext/pull/1407\r\n",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further... | 1,592 | 1,606 | 1,601 | NONE | null | # 🌟 New model addition
## Model description
### Linformer: Self-Attention with Linear Complexity
Paper published June 9th on ArXiv: https://arxiv.org/abs/2006.04768
Large transformer models have shown extraordinary success in achieving state-of-the-art results in many natural language processing applicatio... | {
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https://api.github.com/repos/huggingface/transformers/issues/4966 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4966/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4966/comments | https://api.github.com/repos/huggingface/transformers/issues/4966/events | https://github.com/huggingface/transformers/issues/4966 | 638,012,658 | MDU6SXNzdWU2MzgwMTI2NTg= | 4,966 | Spanbert TACRED model not found, despite model card | {
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"Vocab file for that model is indeed missig, /cc @mrm8488 \r\n\r\nBut in the meantime I think you can use:\r\n\r\n```python\r\ntokenizer = AutoTokenizer.from_pretrained(\"SpanBERT/spanbert-base-cased\")\r\n```",
"I will upload it ASAP. Thank you for letting me know!",
"Tokenizer files have been uploaded!!! @mic... | 1,591 | 1,598 | 1,598 | NONE | null | I am trying to load this model: https://huggingface.co/mrm8488/spanbert-large-finetuned-tacred in Transformers 2.11.0. My exact code is:
` tokenizer = AutoTokenizer.from_pretrained("mrm8488/spanbert-large-finetuned-tacred") model = AutoModel.from_pretrained("mrm8488/spanbert-large-finetuned-tacred")`.
However, I... | {
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https://api.github.com/repos/huggingface/transformers/issues/4965 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4965/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4965/comments | https://api.github.com/repos/huggingface/transformers/issues/4965/events | https://github.com/huggingface/transformers/issues/4965 | 638,010,501 | MDU6SXNzdWU2MzgwMTA1MDE= | 4,965 | How to Paraphrase with GPT2? | {
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"You should rather use a seq2seq model for paraphrasing like T5 or BART. But if you want to do it using GPT-2 then maybe you can use this format\r\n\r\n`input: input_text paraphrase: parahrase_text`\r\n\r\n while training, set attention mask to 0 on the paraphrased text\r\n\r\nand when generating just pass `input:... | 1,591 | 1,618 | 1,600 | 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/4964 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4964/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4964/comments | https://api.github.com/repos/huggingface/transformers/issues/4964/events | https://github.com/huggingface/transformers/issues/4964 | 638,003,308 | MDU6SXNzdWU2MzgwMDMzMDg= | 4,964 | GPT: Weights not being initialized | {
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"Never mind, resolved now!!\r\nThanks!! ",
"How did you resolve?"
] | 1,591 | 1,593 | 1,591 | NONE | null | Hello covid-19 survivors,
I have been trying to use GPT for token classification, however currently there is none from hugging face, hence I copied your code from berttokenclassification and stitched the below code. But it says all the weights not initialized. Did I make a mistake, please help me!!!
`
class GPTC... | {
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https://api.github.com/repos/huggingface/transformers/issues/4963 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4963/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4963/comments | https://api.github.com/repos/huggingface/transformers/issues/4963/events | https://github.com/huggingface/transformers/issues/4963 | 637,947,824 | MDU6SXNzdWU2Mzc5NDc4MjQ= | 4,963 | Cannot load optimizer and lr_scheduler states with TPU training | {
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"Thanks @misrasaurabh1, I'll look into it.\r\nWe'll have to add such a test into the TPU CI once we have it (sooner rather than later).",
"Any updates on getting rid of this error?\r\nMakes it hard to use TPUs because preemptible machines cannot be used in Google Cloud if there is no way to resume from checkpoint... | 1,591 | 1,603 | 1,603 | CONTRIBUTOR | null | # 🐛 Bug
When restarting training and loading the optimizer.pt and scheduler.pt, the training crashes as the existing code does not know how to load it with TPU.
## Information
The stacktrace -
```
Exception in device=TPU:5: don't know how to restore data location of torch.FloatStorage (tagged with xla:0)
Trac... | {
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https://api.github.com/repos/huggingface/transformers/issues/4962 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4962/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4962/comments | https://api.github.com/repos/huggingface/transformers/issues/4962/events | https://github.com/huggingface/transformers/issues/4962 | 637,946,366 | MDU6SXNzdWU2Mzc5NDYzNjY= | 4,962 | How to implement differential learning rates and still ensure "weight_decay" = 0 for the the parameters it should? | {
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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"
] | 1,591 | 1,598 | 1,598 | CONTRIBUTOR | null | I notice that most models are trained with the following parameter groups:
```
no_decay = ["bias", "LayerNorm.weight"]
optimizer_grouped_parameters = [
{
"params": [p for n, p in model.named_parameters() if not any(nd in n for nd in no_decay)],
"weight_decay": 1e-5,
},
{
"... | {
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https://api.github.com/repos/huggingface/transformers/issues/4961 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4961/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4961/comments | https://api.github.com/repos/huggingface/transformers/issues/4961/events | https://github.com/huggingface/transformers/issues/4961 | 637,910,097 | MDU6SXNzdWU2Mzc5MTAwOTc= | 4,961 | Extending Encoder Decoder to GPT-2 | {
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"It's on the roadmap :-) ",
"Thank you! Look forward to it :)",
"Hi - I've actually been working on this myself the past couple days, should I submit a PR when finished? ",
"That'd be great!",
"Will do - likely sometime this week. ",
"@djw1809 Any update on the PR? :)",
"@patrickvonplaten Hello Patrick... | 1,591 | 1,604 | 1,604 | NONE | null | Adding GPT2 initialization for EncoderDecoder model as pointed out in the issue below.
> Currently, only Bert works as a decoder. We might add GPT2 in a couple of weeks. Note that no model has `cross-attention` layers if it is not already an encoder-decoder model (like Bart or T5) and in this case it does not make s... | {
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https://api.github.com/repos/huggingface/transformers/issues/4960 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4960/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4960/comments | https://api.github.com/repos/huggingface/transformers/issues/4960/events | https://github.com/huggingface/transformers/issues/4960 | 637,873,847 | MDU6SXNzdWU2Mzc4NzM4NDc= | 4,960 | unexpected keyword argument 'lm_labels' when using BertModel as Decoder with EncoderDecoderModel | {
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"I'm facing the same problem. Since #4874 it seems like it should be just `labels` instead of `lm_labels`. According to the documentation it should do masked language modeling-loss, but from my debugging it seems like it actually does next word prediction-loss.",
"This issue has been automatically marked as stale... | 1,591 | 1,598 | 1,598 | NONE | null | The `BertModel.forward()` method does not expect a `lm_labels` and `masked_lm_labels` arguments. Yet, it looks like the `EncoderDecoderModel.forward()` method calls it's decoder's `forward()` method with those arguments which throws a TypeError when a BertModel is used as a decoder.
Am I using the BertModel incorrec... | {
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https://api.github.com/repos/huggingface/transformers/issues/4959 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4959/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4959/comments | https://api.github.com/repos/huggingface/transformers/issues/4959/events | https://github.com/huggingface/transformers/pull/4959 | 637,765,350 | MDExOlB1bGxSZXF1ZXN0NDMzNjkxOTA5 | 4,959 | Add AlbertForMultipleChoice | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4959?src=pr&el=h1) Report\n> Merging [#4959](https://codecov.io/gh/huggingface/transformers/pull/4959?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/02e5f79662d72cccdca81a47e3001a5f6d36e5b1&el=desc) will **increase... | 1,591 | 1,591 | 1,591 | COLLABORATOR | null | Cleaning up the rebase and opening a fresh PR. | {
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https://api.github.com/repos/huggingface/transformers/issues/4958 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4958/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4958/comments | https://api.github.com/repos/huggingface/transformers/issues/4958/events | https://github.com/huggingface/transformers/issues/4958 | 637,683,576 | MDU6SXNzdWU2Mzc2ODM1NzY= | 4,958 | Issue with an inline code comment | {
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## Information
Model I am using (Bert, XLNet ...):
Language I am using the model on (English, Chinese ...):
The problem arises when using:
* [x ] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
The tasks I am working on is:
* [ x] an offi... | {
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https://api.github.com/repos/huggingface/transformers/issues/4957 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4957/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4957/comments | https://api.github.com/repos/huggingface/transformers/issues/4957/events | https://github.com/huggingface/transformers/issues/4957 | 637,619,157 | MDU6SXNzdWU2Mzc2MTkxNTc= | 4,957 | Memory leakage with bert-large-uncased-whole-word-masking-finetuned-squad | {
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"Hi, @ashispapu, you might wanna wrap the inference code with\r\n`with torch.no_grad():`",
"Thanks for the response. Should not it be grad disabled by default like other models in transformer during inference.",
"I don't think so, how would the model know that you are doing training or inference. You can use `... | 1,591 | 1,592 | 1,592 | NONE | null | # 🐛 Bug
## Information
I am using 'bert-large-uncased-whole-word-masking-finetuned-squad' and observed an memory leak during the inference. Below the code snippet to reproduce it
tokenizer = AutoTokenizer.from_pretrained("bert-large-uncased-whole-word-masking-finetuned-squad")
model = AutoModelForQuestionAns... | {
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https://api.github.com/repos/huggingface/transformers/issues/4956 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4956/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4956/comments | https://api.github.com/repos/huggingface/transformers/issues/4956/events | https://github.com/huggingface/transformers/issues/4956 | 637,603,755 | MDU6SXNzdWU2Mzc2MDM3NTU= | 4,956 | RobertaForMaskedLM Failing for example code given on Hugging Face' documentation page | {
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"Which version of the library are you using? The documentation corresponds to the master branch and the change in the argument names was pretty recent, so I don't think it's in the latest release yet. You should either [install from source](https://github.com/huggingface/transformers#from-source) or change the code... | 1,591 | 1,593 | 1,593 | NONE | null | # 🐛 Bug
from transformers import RobertaTokenizer, RobertaForMaskedLM
import torch
tokenizer = RobertaTokenizer.from_pretrained('roberta-base')
model = RobertaForMaskedLM.from_pretrained('roberta-base')
input_ids = torch.tensor(tokenizer.encode("Hello, my dog is cute", add_special_tokens=True)).unsqueeze(0) ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4955 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4955/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4955/comments | https://api.github.com/repos/huggingface/transformers/issues/4955/events | https://github.com/huggingface/transformers/issues/4955 | 637,599,851 | MDU6SXNzdWU2Mzc1OTk4NTE= | 4,955 | How to use fine-tuned BERT to fill <mask> | {
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"Hi @Odimmsun , `BertForSequenceClassification` is used for classification task and not for mak-filling. You can use the pre-trained BERT model as it is for make-filling. There is pipeline for this task which you can find here https://huggingface.co/transformers/usage.html#masked-language-modeling\r\n\r\nBasically ... | 1,591 | 1,600 | 1,598 | 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/4954 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4954/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4954/comments | https://api.github.com/repos/huggingface/transformers/issues/4954/events | https://github.com/huggingface/transformers/pull/4954 | 637,557,800 | MDExOlB1bGxSZXF1ZXN0NDMzNTIyMTA5 | 4,954 | ElectraForMultipleChoice | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4954?src=pr&el=h1) Report\n> Merging [#4954](https://codecov.io/gh/huggingface/transformers/pull/4954?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/efeb75b8054cc299698cf8bc09f395ada2660745&el=desc) will **increase... | 1,591 | 1,592 | 1,592 | MEMBER | null | This PR add `ElectraForMultipleChoice`. One of the missing models in this [project](https://github.com/huggingface/transformers/projects/17).
Since, for multiple choice pooled outputs are needed, added `ElectraPooler` class.
@sgugger , @LysandreJik | {
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https://api.github.com/repos/huggingface/transformers/issues/4953 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4953/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4953/comments | https://api.github.com/repos/huggingface/transformers/issues/4953/events | https://github.com/huggingface/transformers/pull/4953 | 637,546,349 | MDExOlB1bGxSZXF1ZXN0NDMzNTEzMzI2 | 4,953 | Added feature to move added tokens in vocabulary for Transformer-XL | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4953?src=pr&el=h1) Report\n> Merging [#4953](https://codecov.io/gh/huggingface/transformers/pull/4953?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/5620033115e571013325d017bcca92991b0a4ace&el=desc) will **increase... | 1,591 | 1,593 | 1,592 | CONTRIBUTOR | null | As discussed in #3554 the tokens in the tokenizer have to be shifted if adding a new token into aka resizing an embedding layer other than the last one. Of course this applies only for an `AdaptiveEmbedding` with more than one layer.
This implementation adds a function to move an added token in the tokenizer to a sp... | {
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https://api.github.com/repos/huggingface/transformers/issues/4952 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4952/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4952/comments | https://api.github.com/repos/huggingface/transformers/issues/4952/events | https://github.com/huggingface/transformers/issues/4952 | 637,472,648 | MDU6SXNzdWU2Mzc0NzI2NDg= | 4,952 | Data used for training MarianMT models | {
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"Hi, @yashkant, you might be able to find these details here https://github.com/Helsinki-NLP/Opus-MT"
] | 1,591 | 1,591 | 1,591 | NONE | null | # ❓ Questions & Help
Are there specifications available on the amount and type of training data used for the released MarianMT [models](https://huggingface.co/transformers/model_doc/marian.html)?
## Details
<!-- Description of your issue -->
I want to use these models for back translation in order to augment my c... | {
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https://api.github.com/repos/huggingface/transformers/issues/4951 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4951/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4951/comments | https://api.github.com/repos/huggingface/transformers/issues/4951/events | https://github.com/huggingface/transformers/pull/4951 | 637,464,478 | MDExOlB1bGxSZXF1ZXN0NDMzNDQ4NTA2 | 4,951 | [examples] SummarizationModule improvements | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4951?src=pr&el=h1) Report\n> Merging [#4951](https://codecov.io/gh/huggingface/transformers/pull/4951?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/c852036b4abca2c20e1adf92eda48472a7d84ef0&el=desc) will **increase... | 1,591 | 1,592 | 1,592 | CONTRIBUTOR | null | This PR makes the SummarizationTrainer much more usable, and when improvements are not unique to summarization, they are implemented in `lightning_base.py` instead.
- **Checkpointing** Before this PR, the code saves 5GB of PL checkpoints per epoch, now SummarizationTrainer saves the best checkpoint based on ROUGE 2 ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4950 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4950/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4950/comments | https://api.github.com/repos/huggingface/transformers/issues/4950/events | https://github.com/huggingface/transformers/issues/4950 | 637,422,058 | MDU6SXNzdWU2Mzc0MjIwNTg= | 4,950 | GPTDoubleHeadsModel Unexpected node type: onnx:: Sub | {
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"Hi @mihail911, thanks for reporting the issue and the script to reproduce.\r\n\r\nI can confirm the issue, as it seems to happen on PyTorch side, I suspect it's a bug on their side. @tianleiwu should we forward the issue on PyTorch issue tracker? \r\n\r\nSlightly updated the script to avoid errors: \r\n\r\n```pyth... | 1,591 | 1,592 | 1,592 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): GPT2DoubleHeadsModel
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
The tasks I am wo... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4949?src=pr&el=h1) Report\n> Merging [#4949](https://codecov.io/gh/huggingface/transformers/pull/4949?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/473808da0d476792070f0e7dfebcf1121a12a34f&el=desc) will **not chan... | 1,591 | 1,591 | 1,591 | CONTRIBUTOR | null | the expected logits must be in the same dtype as the resulting logits. | {
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"Hi @Guitaricet , if you only want to evaluate for loss (AFAIK this is the case for seq2seq models) then you can set `prediction_loss_only` to `True`",
"Hi! Thank you, but I need the metrics too. Workaround was to inherit from `Trainer` and override `_prediction_loop`. ",
"That sounds like a reasonable solution... | 1,591 | 1,602 | 1,602 | NONE | null | # 🐛 Bug
## Information
Hi! I can't thank you enough for Transformers. I know that the Trainer is still under development, but would like to report this just to know the current status.
Currently `Trainer._prediction_loop` assumes that different batches of data have the same shape.
Specifically, [this line](h... | {
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"Integration test error does not seem to be related to this PR.\r\n\r\n@jplu On another note, I got strange results while using `run_tf_glue` as learning rate goes quickly to 0.\r\n\r\nCommand:\r\n`run_tf_glue.py --model_name_or_path bert-base-cased --task_name MRPC --do_train --do_eval --max_seq_length 128 --per_d... | 1,591 | 1,592 | 1,592 | CONTRIBUTOR | null | This PR supersedes PR #4756
I wanted initially to refactor logging between `Trainer` and `TFTrainer` but there seems to be too many differences between them for it to make sense (distributed training, logging methods, `wandb.watch`…).
Logging is now handled directly within each Trainer and all comments from previo... | {
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"Got around this by running the following code to generate the config.json and then running evaluate_cnn.py as above.\r\n\r\n```\r\nfrom lightning_base import BaseTransformer\r\nfrom finetune import SummarizationTrainer\r\nimport torch\r\nfrom argparse import Namespace\r\n\r\nargs = Namespace(adam_epsilon=1e-08, ca... | 1,591 | 1,592 | 1,592 | NONE | null | Hello,
I used the [finetune_bart.sh ](https://github.com/huggingface/transformers/blob/master/examples/summarization/finetune_bart.sh) and was able to finetune the model on my task. I checked the output directory and checkpoints were stored and there were no errors.
Following the training, i ran evaluate_cnn.py u... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4944?src=pr&el=h1) Report\n> Merging [#4944](https://codecov.io/gh/huggingface/transformers/pull/4944?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/473808da0d476792070f0e7dfebcf1121a12a34f&el=desc) will **decrease... | 1,591 | 1,598 | 1,598 | COLLABORATOR | null | Opening the discussion about refactoring the dupe code in all task-specific models. This is a proposal of design that still leaves the specific classes and their docstrings, does not change the name of their attributes for backward compatibility but delegates the actual forward method to a task-specific method in `PreT... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4943?src=pr&el=h1) Report\n> Merging [#4943](https://codecov.io/gh/huggingface/transformers/pull/4943?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/473808da0d476792070f0e7dfebcf1121a12a34f&el=desc) will **increase... | 1,591 | 1,592 | 1,592 | COLLABORATOR | null | Hi,
this PR avoids adding an extra `</s>` symbol, so that the final sequence ends with `</s> </s>`.
The documentation clearly states, that ther's only one `</s>` expected at the end of a single sequence:
https://huggingface.co/transformers/model_doc/roberta.html#transformers.RobertaTokenizer.build_inputs_with_... | {
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"I also have the same issue.",
"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"
] | 1,591 | 1,602 | 1,602 | NONE | null | # ❓ Questions & Help
I notice that when doing inference/training with a pre-trained language model in a Trainer, only one worker is used. For training it's not a problem as the batch size is usually small, however, for inference, I can largely increase it.
However, it seems that https://github.com/huggingface/tra... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4941?src=pr&el=h1) Report\n> Merging [#4941](https://codecov.io/gh/huggingface/transformers/pull/4941?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/699541c4b34479451c91b3c6c204d904f62bed83&el=desc) will **decrease... | 1,591 | 1,591 | 1,591 | MEMBER | null | Because of a wrong indentation, the memory usage was calculated incorrectly | {
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https://api.github.com/repos/huggingface/transformers/issues/4940 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4940/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4940/comments | https://api.github.com/repos/huggingface/transformers/issues/4940/events | https://github.com/huggingface/transformers/pull/4940 | 637,243,143 | MDExOlB1bGxSZXF1ZXN0NDMzMjY3Njc4 | 4,940 | Delay decay schedule until the end of warmup | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4940?src=pr&el=h1) Report\n> Merging [#4940](https://codecov.io/gh/huggingface/transformers/pull/4940?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/6293eb04dfef704e87a6e0b358848ffc41587b4f&el=desc) will **increase... | 1,591 | 1,595 | 1,593 | CONTRIBUTOR | null | The decay schedule should start at the end of the warmup steps. Without this simple edit, learning rate will drop at the end of the warmup steps, like the figure shown below:
<img width="378" alt="image" src="https://user-images.githubusercontent.com/15783079/84426617-c5820500-ac38-11ea-9579-2c0d5f374e33.png">
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@sshleifer
All tests seem to pass. Please review!
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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"
] | 1,591 | 1,598 | 1,598 | CONTRIBUTOR | null | This is a continuation of and very related to https://github.com/huggingface/transformers/issues/4586
but the issue here is `NaN` loss during finetuning, rather than `nan` in model outputs.
### Instructions to reproduce
From `examples/summarization`
Setup cnn tiny:
```bash
wget https://s3.amazonaws.com/datas... | {
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"Hi! The pooler is actually a linear layer, that is used on top of the BERT encoder (the hidden layers). It's not doing a pooling operation like average or max pooling.\r\n",
"Ok i read that somewhere. But my is on what component ? If you use a pooler on the last layer of bert encoder you will get an output of si... | 1,591 | 1,592 | 1,592 | NONE | null | # ❓ Questions & Help
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4936?src=pr&el=h1) Report\n> Merging [#4936](https://codecov.io/gh/huggingface/transformers/pull/4936?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/699541c4b34479451c91b3c6c204d904f62bed83&el=desc) will **increase... | 1,591 | 1,591 | 1,591 | MEMBER | null | {
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https://api.github.com/repos/huggingface/transformers/issues/4935 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4935/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4935/comments | https://api.github.com/repos/huggingface/transformers/issues/4935/events | https://github.com/huggingface/transformers/issues/4935 | 636,917,712 | MDU6SXNzdWU2MzY5MTc3MTI= | 4,935 | name 'ElectraForSequenceClassification' is not defined | {
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"Hi @Gemini77 , what is your transformers version ? \r\n\r\n`ElectraForSequenceClassification` is available in transformers >=2.10.0 version"
] | 1,591 | 1,592 | 1,592 | NONE | null | # ❓ Questions & Help
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https://api.github.com/repos/huggingface/transformers/issues/4934 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4934/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4934/comments | https://api.github.com/repos/huggingface/transformers/issues/4934/events | https://github.com/huggingface/transformers/issues/4934 | 636,916,731 | MDU6SXNzdWU2MzY5MTY3MzE= | 4,934 | Using LongformerForQuestionAnswering on large documents (40K+ characters) | {
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"_What model of GPU are you using ?_\r\n\r\nI didn't open your notebook, that's what I was looking for :\r\n```\r\nCUDA out of memory. Tried to allocate 4.92 GiB (GPU 0; 11.17 GiB total capacity; 4.64 GiB already allocated; 3.69 GiB free; 7.12 GiB reserved in total by PyTorch)\r\nDetached cpu cpu\r\n```",
"> What... | 1,591 | 1,592 | 1,592 | NONE | null | # ❓ Questions & Help
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https://api.github.com/repos/huggingface/transformers/issues/4933 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4933/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4933/comments | https://api.github.com/repos/huggingface/transformers/issues/4933/events | https://github.com/huggingface/transformers/pull/4933 | 636,869,702 | MDExOlB1bGxSZXF1ZXN0NDMyOTU3MTM5 | 4,933 | [AutoModel] Split AutoModelWithLMHead into clm, mlm, encoder-decoder | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4933?src=pr&el=h1) Report\n> Merging [#4933](https://codecov.io/gh/huggingface/transformers/pull/4933?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e80d6c689bd62f805a5c8d77ec0cc3b09f240d14&el=desc) will **increase... | 1,591 | 1,597 | 1,591 | MEMBER | null | This is a follow-up PR of #4874.
In #4874, `BertModelForMaskedLM` , was split into a clm `BertLMHeadModel` and mlm Bert Model `BertForMaskedLM`. In order for the encoder-decoder framework to work correctly, the `BertLMHeadModel` needs to be loaded, when instantiating an `EncoderDecoder.from_encoder_decoder_pretraine... | {
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https://api.github.com/repos/huggingface/transformers/issues/4932 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4932/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4932/comments | https://api.github.com/repos/huggingface/transformers/issues/4932/events | https://github.com/huggingface/transformers/issues/4932 | 636,813,821 | MDU6SXNzdWU2MzY4MTM4MjE= | 4,932 | Training ELECTRA model on TPU with the help of Trainer or TFTrainer classes | {
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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"
] | 1,591 | 1,598 | 1,598 | NONE | null | # ❓ Questions & Help
Hi there,
I am trying to train Electra model from scratch using HF's Trainer interface. My primary source is this colab:
https://colab.research.google.com/github/huggingface/blog/blob/master/notebooks/01_how_to_train.ipynb#scrollTo=ri2BIQKqjfHm
There are several questions about Electra ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4931 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4931/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4931/comments | https://api.github.com/repos/huggingface/transformers/issues/4931/events | https://github.com/huggingface/transformers/issues/4931 | 636,776,077 | MDU6SXNzdWU2MzY3NzYwNzc= | 4,931 | BertTokenizer from own vocab meet problem | {
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"ok, I fix it by using lower case"
] | 1,591 | 1,591 | 1,591 | NONE | null | # ❓ Questions & Help
I set up own vocab.txt and the item like 3-213,3A23 and so on. When use BertTokenizer.from_pretrained() it couldn't tokenize the '3-213'. Even when I write 'A' in vocab.txt ,and couldn't encode('A'). Do anyone know how to fix this issue?
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https://api.github.com/repos/huggingface/transformers/issues/4930 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4930/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4930/comments | https://api.github.com/repos/huggingface/transformers/issues/4930/events | https://github.com/huggingface/transformers/pull/4930 | 636,769,794 | MDExOlB1bGxSZXF1ZXN0NDMyODc5MzYw | 4,930 | Update setup.py for sentencepiece. | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4929?src=pr&el=h1) Report\n> Merging [#4929](https://codecov.io/gh/huggingface/transformers/pull/4929?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e80d6c689bd62f805a5c8d77ec0cc3b09f240d14&el=desc) will **increase... | 1,591 | 1,592 | 1,592 | MEMBER | null | This PR fixes the QA example in the doc for `ElectraForQuestionAnswering`. In the last example `token_type_ids` were not used, this PR fixes that
@sgugger | {
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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"
] | 1,591 | 1,598 | 1,598 | NONE | null | # 🐛 Bug
## Information
Now the `sentencepiece` library has upgraded to `0.1.92` version which is incompatible with `transformers==2.8.0`.
## Error
`segmentation fault (core dumped)`
## location.
https://github.com/huggingface/transformers/blob/v2.8.0/setup.py#L113
## configurations
- Platf... | {
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https://api.github.com/repos/huggingface/transformers/issues/4927 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4927/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4927/comments | https://api.github.com/repos/huggingface/transformers/issues/4927/events | https://github.com/huggingface/transformers/issues/4927 | 636,755,292 | MDU6SXNzdWU2MzY3NTUyOTI= | 4,927 | Incorrect loss values calculated for TPU training. | {
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"@LysandreJik Any comments on this evaluation behavior with Trainer?",
"Could it be solved by adding a `if self.is_world_master` prior to calling `self._log` (or directly within that function)?",
"I think you are right. I was concerned that the evaluator is calculating all these eval loss values separately but ... | 1,591 | 1,598 | 1,598 | CONTRIBUTOR | null | # 🐛 Bug
Currently using Trainer on TPU calculates incorrect training and eval_during_training loss values. This leads to loss values logged on Wandb also being incorrect.
## Information
The problem seems to be that with a PyTorch/XLA training setup with multiprocessing, each processes trains and evals on disjoint (... | {
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https://api.github.com/repos/huggingface/transformers/issues/4926 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4926/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4926/comments | https://api.github.com/repos/huggingface/transformers/issues/4926/events | https://github.com/huggingface/transformers/pull/4926 | 636,738,653 | MDExOlB1bGxSZXF1ZXN0NDMyODU2MDQx | 4,926 | Fixing TPU training by disabling wandb.watch gradients logging | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4926?src=pr&el=h1) Report\n> Merging [#4926](https://codecov.io/gh/huggingface/transformers/pull/4926?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e80d6c689bd62f805a5c8d77ec0cc3b09f240d14&el=desc) will **increase... | 1,591 | 1,592 | 1,592 | CONTRIBUTOR | null | Fixes issue https://github.com/huggingface/transformers/issues/4814
PyTorch TPU trainer.py had a bug where the training would freeze up during the logging step. On investigation, the culprit was found to be a wandb.watch call which was trying to log gradients. This operation is suspected to be unsupported by Wandb for... | {
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https://api.github.com/repos/huggingface/transformers/issues/4925 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4925/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4925/comments | https://api.github.com/repos/huggingface/transformers/issues/4925/events | https://github.com/huggingface/transformers/pull/4925 | 636,669,342 | MDExOlB1bGxSZXF1ZXN0NDMyODAwNjY1 | 4,925 | Use dataloader_drop_last in TF dataset | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4925?src=pr&el=h1) Report\n> Merging [#4925](https://codecov.io/gh/huggingface/transformers/pull/4925?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e80d6c689bd62f805a5c8d77ec0cc3b09f240d14&el=desc) will **increase... | 1,591 | 1,591 | 1,591 | CONTRIBUTOR | null | Follows PR #4757, fixes issue #4891. I didn't realize then that `TFTrainingArguments` inherited `TrainingArguments` and all of the same options would be available there as well.
Adding this to get to feature parity across PyTorch and TF trainers. | {
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https://api.github.com/repos/huggingface/transformers/issues/4924 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4924/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4924/comments | https://api.github.com/repos/huggingface/transformers/issues/4924/events | https://github.com/huggingface/transformers/pull/4924 | 636,664,229 | MDExOlB1bGxSZXF1ZXN0NDMyNzk2NTk1 | 4,924 | Fix deprecation warnings due to invalid escape sequences. | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4924?src=pr&el=h1) Report\n> Merging [#4924](https://codecov.io/gh/huggingface/transformers/pull/4924?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e80d6c689bd62f805a5c8d77ec0cc3b09f240d14&el=desc) will **increase... | 1,591 | 1,592 | 1,592 | CONTRIBUTOR | null | Fixes #3754 | {
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https://api.github.com/repos/huggingface/transformers/issues/4923 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4923/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4923/comments | https://api.github.com/repos/huggingface/transformers/issues/4923/events | https://github.com/huggingface/transformers/issues/4923 | 636,637,964 | MDU6SXNzdWU2MzY2Mzc5NjQ= | 4,923 | Documentation doesn't include instructions for applying BertModel to documents using GPU acceleration | {
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"This is a pretty basic question that's not really about the library:)\r\n\r\nCheck out the PyTorch doc, in particular, the [60 minute blitz](https://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html). TL;DR: You'll need to move your model and inputs to the device you want with `.to(device)` calls.",
... | 1,591 | 1,592 | 1,591 | NONE | null | # 🐛 Bug
## Information
I am using `BertModel` to encode my documents using the representation I've just fine-tuned and it is not using the GPU to do the encoding. This is bad because encoding is very slow. I have it running on many cores but would prefer GPU acceleration. It is not clear from the documentation h... | {
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https://api.github.com/repos/huggingface/transformers/issues/4922 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4922/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4922/comments | https://api.github.com/repos/huggingface/transformers/issues/4922/events | https://github.com/huggingface/transformers/issues/4922 | 636,547,984 | MDU6SXNzdWU2MzY1NDc5ODQ= | 4,922 | Unexpected behavior encoding token_type_ids in GPT models | {
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## Information
When `token_type_ids` are passed into the `GPT2Model` and subclasses, they're encoded using the `nn.Embedding` lookup table as the vocabulary ([line](https://github.com/huggingface/transformers/blob/3ae2e86baffc1fea8b8b93695fb5a10941fd63dc/src/transformers/modeling_gpt2.py#L477)). Because ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4921 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4921/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4921/comments | https://api.github.com/repos/huggingface/transformers/issues/4921/events | https://github.com/huggingface/transformers/pull/4921 | 636,547,069 | MDExOlB1bGxSZXF1ZXN0NDMyNzAwNDAz | 4,921 | Make multiple choice models work with input_embeds | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4921?src=pr&el=h1) Report\n> Merging [#4921](https://codecov.io/gh/huggingface/transformers/pull/4921?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/466aa57a45bfb9fc47d4b75d22c02c34b4b4b0fc&el=desc) will **increase... | 1,591 | 1,591 | 1,591 | COLLABORATOR | null | Currently, all the multiple choice models will fail if we pass them `inputs_embeds` instead of `input_ids`. This PR fixes that on the pytorch side and adapts the corresponding test for common models. | {
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