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https://api.github.com/repos/huggingface/transformers/issues/10935 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10935/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10935/comments | https://api.github.com/repos/huggingface/transformers/issues/10935/events | https://github.com/huggingface/transformers/issues/10935 | 842,656,498 | MDU6SXNzdWU4NDI2NTY0OTg= | 10,935 | Add DALL-E: Zero-Shot Text-to-Image Generation | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,616 | 1,696 | null | NONE | null | # 🚀 Feature request
Please add DALLE-E model to huggingface's Transformers library.
1. [Announcement](https://openai.com/blog/dall-e/)
2. [Abstract](https://arxiv.org/abs/2102.12092v2)
3. [Paper](https://arxiv.org/pdf/2102.12092v2.pdf)
4. Code:
- [openai/DALL-E](https://github.com/openai/DALL-E) (officia... | {
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https://api.github.com/repos/huggingface/transformers/issues/10934 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10934/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10934/comments | https://api.github.com/repos/huggingface/transformers/issues/10934/events | https://github.com/huggingface/transformers/pull/10934 | 842,621,511 | MDExOlB1bGxSZXF1ZXN0NjAyMTU0Njkx | 10,934 | Add `examples/multiple-choice/run_swag_no_trainer.py` | {
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"Tested on one GPU, two GPUs and TPUs, this runs fine everywhere. So just waiting for the small adjustments and it should be good to be merged :-) ",
"Thanks a lot!"
] | 1,616 | 1,617 | 1,617 | CONTRIBUTOR | null | This PR adds an example of a multiple-choice task on the SWAG dataset to show the functionalities of the new `accelerate` library.
<hr>
**Reviewers:** @sgugger | {
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https://api.github.com/repos/huggingface/transformers/issues/10933 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10933/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10933/comments | https://api.github.com/repos/huggingface/transformers/issues/10933/events | https://github.com/huggingface/transformers/issues/10933 | 842,596,293 | MDU6SXNzdWU4NDI1OTYyOTM= | 10,933 | Can't download the facebook/bart-large-mnli tensorflow model | {
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"@mayanb I don't think this model has a TF version till now, check:- https://huggingface.co/facebook/bart-large-mnli/tree/main",
"@frankhart2018 ah you're right! thanks!"
] | 1,616 | 1,616 | 1,616 | NONE | null | Hello! When I try to create a pipeline with the model specified as "facebook/bart-large-mnli" I get a 404 Client Error: Not Found for url: https://huggingface.co/facebook/bart-large-mnli/resolve/main/tf_model.h5
And when I try to go directly to that url I do also notice it throws a 404 error. Any ideas on how to fix t... | {
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https://api.github.com/repos/huggingface/transformers/issues/10932 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10932/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10932/comments | https://api.github.com/repos/huggingface/transformers/issues/10932/events | https://github.com/huggingface/transformers/pull/10932 | 842,573,616 | MDExOlB1bGxSZXF1ZXN0NjAyMTE5ODM1 | 10,932 | Updated colab links in readme of examples | {
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Updated the Google Colab links for the The Big Table of Tasks in the examples folder readme.
Google Colab links were replace to the appropriate examples found [here](https://github.com/huggingface/notebooks/tree/master/examples)
text_generation.ipynb is not present in the [notebook repo](ht... | {
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https://api.github.com/repos/huggingface/transformers/issues/10931 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10931/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10931/comments | https://api.github.com/repos/huggingface/transformers/issues/10931/events | https://github.com/huggingface/transformers/issues/10931 | 842,547,673 | MDU6SXNzdWU4NDI1NDc2NzM= | 10,931 | Another way to express masked_index = torch.nonzero(input_ids == self.tokenizer.mask_token_id, as_tuple=False) | {
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"Hello! Unfortunately, recent transformers versions only work with torch 1.4.0+. The README is incorrect respective to that, and I'll update it in the coming days.",
"> Hello! Unfortunately, recent transformers versions only work with torch 1.4.0+. The README is incorrect respective to that, and I'll update it in... | 1,616 | 1,620 | 1,620 | NONE | null | Dear,
We use PyTorch 1.1.0 to run a masked word completion with BERT. However, we found an error
`TypeError: nonzero() got an unexpected keyword argument 'as_tuple'`
The error refers to this:
`masked_index = torch.nonzero(input_ids == self.tokenizer.mask_token_id, as_tuple=False)`
Is there another way to exp... | {
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https://api.github.com/repos/huggingface/transformers/issues/10930 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10930/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10930/comments | https://api.github.com/repos/huggingface/transformers/issues/10930/events | https://github.com/huggingface/transformers/issues/10930 | 842,542,195 | MDU6SXNzdWU4NDI1NDIxOTU= | 10,930 | Error while predicting on single sentence for token classification task | {
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"@saurabhhssaurabh `trainer.predict()` expects an instance of `torch.utils.data.Dataset` to be passed and not a single sentence. I think it will be easier to use the trained model at self.model to predict rather than trying to use trainer object, as it does not have any single prediction method yet.",
"@frankhart... | 1,616 | 1,616 | 1,616 | NONE | null | Hi
I have fine-tuned BERT for NER task. I am predicting on the fine-tuned model as:
`output = self.tokenizer(text)
trainer = Trainer(model=self.model, tokenizer=self.tokenizer)
trainer.predict(output)`
This code snippet is throwing the following error:
File "run_ner_test_3.py", line 486, in <module>
... | {
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https://api.github.com/repos/huggingface/transformers/issues/10929 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10929/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10929/comments | https://api.github.com/repos/huggingface/transformers/issues/10929/events | https://github.com/huggingface/transformers/issues/10929 | 842,511,400 | MDU6SXNzdWU4NDI1MTE0MDA= | 10,929 | Training with DeepSpeed takes more GPU memory than without DeepSpeed | {
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"Also adding the logs from the beginning of training with deepspeed:\r\n\r\ndeepspeed examples/seq2seq/run_summarization.py --model_name_or_path t5-small --do_train --do_eval --dataset_name cnn_dailymail --dataset_config \"3.0.0\" --source_prefix \"summarize: \" --output_dir /tmp/tst-summarization --per_device_tr... | 1,616 | 1,620 | 1,620 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.5.0.dev0
- deepspeed version: 0.3.13
- Platform: Linux-4.15.0-66-generic-x86_64-with-Ubuntu-18.04-bionic
-... | {
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https://api.github.com/repos/huggingface/transformers/issues/10928 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10928/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10928/comments | https://api.github.com/repos/huggingface/transformers/issues/10928/events | https://github.com/huggingface/transformers/pull/10928 | 842,408,876 | MDExOlB1bGxSZXF1ZXN0NjAxOTk1MzI4 | 10,928 | Add example for registering callbacks with trainers | {
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"Thanks for updating, this looks great!"
] | 1,616 | 1,617 | 1,617 | CONTRIBUTOR | null | # What does this PR do?
Fixes the issue addressed in #9036 by adding an example for registering a custom callback with the Trainer.
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https:/... | {
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https://api.github.com/repos/huggingface/transformers/issues/10927 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10927/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10927/comments | https://api.github.com/repos/huggingface/transformers/issues/10927/events | https://github.com/huggingface/transformers/issues/10927 | 842,273,358 | MDU6SXNzdWU4NDIyNzMzNTg= | 10,927 | Add Pooler to DistilBERT | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,616 | 1,620 | 1,620 | NONE | null | # 🚀 Feature request
Hi, I'd like to add a Pooler class to the DistilBERT model, whose interface is similar to BertPooler [here](https://github.com/huggingface/transformers/blob/7da995c00c025c4180c7fb0357256b7f83d342ef/src/transformers/models/bert/modeling_bert.py#L610)
## Motivation
I was using your DistilBERT mo... | {
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https://api.github.com/repos/huggingface/transformers/issues/10926 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10926/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10926/comments | https://api.github.com/repos/huggingface/transformers/issues/10926/events | https://github.com/huggingface/transformers/issues/10926 | 842,256,586 | MDU6SXNzdWU4NDIyNTY1ODY= | 10,926 | Typo in examples/text-classification README | {
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"Indeed, do you want to open a PR with the fix since you found it?\r\n\r\nPS: I didn't know that \\`\\`\\`diff feature, it's soooo pretty 🤩 !",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n... | 1,616 | 1,620 | 1,620 | NONE | null | In the examples/text-classification README, the example scripts for "PyTorch version, no Trainer" are slightly incorrect. They should be adjusted as:
```diff
export TASK_NAME=mrpc
python run_glue_no_trainer.py \
--model_name_or_path bert-base-cased \
--task_name $TASK_NAME \
- --max_seq_length 128 \
+ ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10925 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10925/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10925/comments | https://api.github.com/repos/huggingface/transformers/issues/10925/events | https://github.com/huggingface/transformers/pull/10925 | 842,182,893 | MDExOlB1bGxSZXF1ZXN0NjAxODA3MzY2 | 10,925 | Sagemaker test | {
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"> LGTM! Should the images be added before merge?\r\n\r\nAre you referring to container images? they will be added after the release of `transformers`. If you are referring to the `TODO: Add a screenshot of PR + Text template to make it easy to open.` nope I would add them as soon as we went through the process. To... | 1,616 | 1,617 | 1,617 | MEMBER | null | # What does this PR do?
This PR creates tests for `SageMaker`. This PR creates tests for the `Pytorch` and `tensorflow` DLC. I added a documentation `README.md` which explains when the Tests need to be run and how. Currently, not all tests are leveraging our `examples/` due to limitations like `SageMakerTrainer` not... | {
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https://api.github.com/repos/huggingface/transformers/issues/10924 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10924/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10924/comments | https://api.github.com/repos/huggingface/transformers/issues/10924/events | https://github.com/huggingface/transformers/issues/10924 | 842,178,957 | MDU6SXNzdWU4NDIxNzg5NTc= | 10,924 | Models not able to run when packed with PyInstaller | {
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"Hello! Do you get the same error when not installing PyInstaller, instead using `haystack` in a virtual environment?",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues... | 1,616 | 1,685 | 1,620 | NONE | null | ## Environment info
- `transformers` version: 4.1.1
- Platform: Linux-5.8.0-48-generic-x86_64-with-glibc2.27
- Python version: 3.8.8
- PyTorch version (GPU?): 1.7.1 (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: <fill in>
- Using distributed or parallel set-up in script?: <fill i... | {
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https://api.github.com/repos/huggingface/transformers/issues/10923 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10923/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10923/comments | https://api.github.com/repos/huggingface/transformers/issues/10923/events | https://github.com/huggingface/transformers/issues/10923 | 842,167,096 | MDU6SXNzdWU4NDIxNjcwOTY= | 10,923 | /pytorch/xla/torch_xla/csrc/helpers.h:100 : Check failed: scalar_value.isIntegral() | {
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"I don't think Longformer is supported on TPU, @patrickvonplaten will confirm.",
"@sgugger Thanks!\r\nLooking forward to @patrickvonplaten confirmation. ",
"Hey @mabdullah1994, yeah `Longformer` is sadly not yet supported on TPU. We just merged Big Bird: https://huggingface.co/transformers/master/model_doc/bigb... | 1,616 | 1,656 | 1,624 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.4.2
- Platform: Linux-4.19.112+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.10
- PyTorch version... | {
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https://api.github.com/repos/huggingface/transformers/issues/10922 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10922/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10922/comments | https://api.github.com/repos/huggingface/transformers/issues/10922/events | https://github.com/huggingface/transformers/issues/10922 | 841,894,936 | MDU6SXNzdWU4NDE4OTQ5MzY= | 10,922 | Use reformer in down stream task meet problem | {
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"If I train the model on the crime-and-punishment\r\n```shell\r\npython examples/language-modeling/run_clm.py --model_name_or_path google/reformer-crime-and-punishment --dataset_name crime_and_punish --do_train --do_eval --output_dir /home2/zhenggo1/checkpoint/reformer_clm\r\n```\r\nthe bug is below\r\n```python\r\... | 1,616 | 1,620 | 1,620 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version:4.2.2
- Platform:CentOS
- Python version:3.7
- PyTorch version (GPU?):1.5.1 cpu only
- Tensorflow version (G... | {
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https://api.github.com/repos/huggingface/transformers/issues/10921 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10921/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10921/comments | https://api.github.com/repos/huggingface/transformers/issues/10921/events | https://github.com/huggingface/transformers/issues/10921 | 841,642,760 | MDU6SXNzdWU4NDE2NDI3NjA= | 10,921 | Tokenizer is adding ## to every word from the second. | {
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"Maybe @polm or @singletongue have an idea!",
"I didn't implement BertTokenizer so I'm a little out of my depth here, but the code below in a clean environment worked fine for me with no weird hashes.\r\n\r\n```\r\nfrom transformers import BertJapaneseTokenizer\r\n\r\nname = \"cl-tohoku/bert-base-japanese-whole-w... | 1,616 | 1,625 | 1,620 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.4.2
- Platform: Linux-5.8.0-44-generic-x86_64-with-Ubuntu-20.04-focal
- Python version: 3.6.13
- PyTorch v... | {
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https://api.github.com/repos/huggingface/transformers/issues/10920 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10920/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10920/comments | https://api.github.com/repos/huggingface/transformers/issues/10920/events | https://github.com/huggingface/transformers/pull/10920 | 841,637,670 | MDExOlB1bGxSZXF1ZXN0NjAxMzQ0OTg2 | 10,920 | Rename NLP library to Datasets library | {
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"@sgugger Please review"
] | 1,616 | 1,616 | 1,616 | CONTRIBUTOR | null | # What does this PR do?
Fixes #10897
## Who can review?
Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors which may be interested in your PR.
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https://api.github.com/repos/huggingface/transformers/issues/10919 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10919/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10919/comments | https://api.github.com/repos/huggingface/transformers/issues/10919/events | https://github.com/huggingface/transformers/issues/10919 | 841,621,101 | MDU6SXNzdWU4NDE2MjExMDE= | 10,919 | GPT2 on TPU, training is so slow. | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,616 | 1,620 | 1,620 | NONE | null | When training GPT2 on TPU from scratch, training loss is constant & evaluation loss is decreasing very small amount.
> [INFO|trainer.py:1776] 2021-03-26 04:06:22,551 >> Num examples = 100000
> [INFO|trainer.py:1777] 2021-03-26 04:06:22,551 >> Batch size = 2
> {'eval_loss': 4.687133312225342, 'eval_runtime'... | {
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https://api.github.com/repos/huggingface/transformers/issues/10918 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10918/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10918/comments | https://api.github.com/repos/huggingface/transformers/issues/10918/events | https://github.com/huggingface/transformers/issues/10918 | 841,597,170 | MDU6SXNzdWU4NDE1OTcxNzA= | 10,918 | OSError: file bert-base-uncased/config.json not found | {
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"I'm also facing the same issue. Did you find any fix yet . ??",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https... | 1,616 | 1,705 | 1,629 | NONE | null | ## Environment info
- `transformers` version: 4.4.2
- Python version: 3.6
- PyTorch version (GPU?): 1.8.0 (Tesla V100)
## Information
The problem arises when using:
```
from transformers import BertModel
model = BertModel.from_pretrained('bert-base-uncased')
```
Error Info (Some personal info has be... | {
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https://api.github.com/repos/huggingface/transformers/issues/10917 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10917/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10917/comments | https://api.github.com/repos/huggingface/transformers/issues/10917/events | https://github.com/huggingface/transformers/issues/10917 | 841,556,861 | MDU6SXNzdWU4NDE1NTY4NjE= | 10,917 | longformer speed compared to bert model | {
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"Hi,\r\n\r\nIs it possible to ask questions related to training on the [forum](https://discuss.huggingface.co/) rather than here? For example, all questions related to training LongFormer can be found [here](https://discuss.huggingface.co/search?q=longformer).\r\n\r\nThe authors of Transformers like to keep Github ... | 1,616 | 1,616 | 1,616 | NONE | null | We are trying to use a LongFormer and Bert model for multi-label classification of different documents.
When we use the BERT model (BertForSequenceClassification) with max length 512 (batch size 8) each epoch takes approximately 30 minutes.
When we use LongFormer (LongformerForSequenceClassification with the 'all... | {
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https://api.github.com/repos/huggingface/transformers/issues/10916 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10916/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10916/comments | https://api.github.com/repos/huggingface/transformers/issues/10916/events | https://github.com/huggingface/transformers/issues/10916 | 841,510,440 | MDU6SXNzdWU4NDE1MTA0NDA= | 10,916 | AttributeError: 'Trainer' object has no attribute 'log_metrics' | {
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"You should install Transformers from source. See #10446.",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://gi... | 1,616 | 1,620 | 1,620 | NONE | null | I try to fine tune the distilbert-base-uncased on my own dataset, which are csv made up of each news line by line.
here is my command:
```
nohup python run_mlm.py \
--model_name_or_path distilbert-base-uncased \
--train_file df_finetune_train.csv \
--validation_file df_finetune_test.csv \
--do... | {
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https://api.github.com/repos/huggingface/transformers/issues/10915 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10915/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10915/comments | https://api.github.com/repos/huggingface/transformers/issues/10915/events | https://github.com/huggingface/transformers/pull/10915 | 841,482,592 | MDExOlB1bGxSZXF1ZXN0NjAxMjE2ODQz | 10,915 | Bump pyyaml from 5.3.1 to 5.4 in /examples/research_projects/lxmert | {
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"Looks like pyyaml is up-to-date now, so this is no longer needed."
] | 1,616 | 1,616 | 1,616 | CONTRIBUTOR | null | Bumps [pyyaml](https://github.com/yaml/pyyaml) from 5.3.1 to 5.4.
<details>
<summary>Changelog</summary>
<p><em>Sourced from <a href="https://github.com/yaml/pyyaml/blob/master/CHANGES">pyyaml's changelog</a>.</em></p>
<blockquote>
<p>5.4 (2021-01-19)</p>
<ul>
<li><a href="https://github-redirect.dependabot.com/yaml/py... | {
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https://api.github.com/repos/huggingface/transformers/issues/10914 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10914/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10914/comments | https://api.github.com/repos/huggingface/transformers/issues/10914/events | https://github.com/huggingface/transformers/pull/10914 | 841,431,754 | MDExOlB1bGxSZXF1ZXN0NjAxMTcwNDMy | 10,914 | [vulnerability] fix dependency | {
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@LysandreJik | {
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https://api.github.com/repos/huggingface/transformers/issues/10913 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10913/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10913/comments | https://api.github.com/repos/huggingface/transformers/issues/10913/events | https://github.com/huggingface/transformers/issues/10913 | 841,429,738 | MDU6SXNzdWU4NDE0Mjk3Mzg= | 10,913 | pegasus xsum won't train on xsum dataset | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,616 | 1,620 | 1,620 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 5.0dev
- Platform: linux
- Python version: 3.6.9
- PyTorch version (GPU?): pip install torch==1.8.0+cu111 to... | {
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https://api.github.com/repos/huggingface/transformers/issues/10912 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10912/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10912/comments | https://api.github.com/repos/huggingface/transformers/issues/10912/events | https://github.com/huggingface/transformers/issues/10912 | 841,332,542 | MDU6SXNzdWU4NDEzMzI1NDI= | 10,912 | Summarization length not controlled by max_length, min_length | {
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"The `max_length` and `min_length` are in terms of tokens, not words. As some words consist of multiple tokens, this results in fewer words to be generated than you might expect. ",
"@NielsRogge\r\nThanks for the answer. It makes sense. But when are words consist of multiple tokens, can you give me some examples?... | 1,616 | 1,624 | null | NONE | null | I am using the pertained ctrlsum-cnndm model from transformers. I noticed that summarization text length is not exactly controlled by max_length, min_length arguments of model.generate(). Not sure why. It appears that empty spaces are included, but not sure. Please help. Thanks.
```
text1="The tower is 324 metres (... | {
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https://api.github.com/repos/huggingface/transformers/issues/10911 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10911/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10911/comments | https://api.github.com/repos/huggingface/transformers/issues/10911/events | https://github.com/huggingface/transformers/pull/10911 | 841,303,898 | MDExOlB1bGxSZXF1ZXN0NjAxMDU1NDg3 | 10,911 | Add nvidia megatron models | {
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"@LysandreJik - you'll see that the last test (marked 'slow') in tests/test_modeling_megatron_bert.py points to a checkpoint in examples/megatron-models (downloaded following the instructions described in examples/megatron-models/README.md). I was not sure how to deal with that so suggestions are welcome (for other... | 1,616 | 1,617 | 1,617 | CONTRIBUTOR | null | # What does this PR do?
Add the megatron_gpt2 model. That model reuses the existing GPT2 model. This
commit includes a script to convert a Megatron-GPT2 checkpoint downloaded
from NVIDIA GPU Cloud. See examples/megatron-models/README.md for details.
Add the megatron_bert model. That model is implemented as a mo... | {
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https://api.github.com/repos/huggingface/transformers/issues/10910 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10910/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10910/comments | https://api.github.com/repos/huggingface/transformers/issues/10910/events | https://github.com/huggingface/transformers/pull/10910 | 841,282,894 | MDExOlB1bGxSZXF1ZXN0NjAxMDM3NzM0 | 10,910 | Wav2Vec2 CommonVoice training - Save the processor before training starts | {
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Currently, the Wav2Vec2 processor is saved at the end of training. However, the vocabulary is non-deterministic and varies between runs. Thus, if the training is killed before it's done, the processor is not saved, meaning that the checkpoints do not contain the processor configuration files,... | {
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https://api.github.com/repos/huggingface/transformers/issues/10909 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10909/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10909/comments | https://api.github.com/repos/huggingface/transformers/issues/10909/events | https://github.com/huggingface/transformers/issues/10909 | 841,261,323 | MDU6SXNzdWU4NDEyNjEzMjM= | 10,909 | LengthGroupedSampler slowly iterates over dataset | {
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"I think the solution you suggested on the forums (leaving the length computation up to the user in the dataset) is a bit better. Will investigate a bit more.",
"> I think the solution you suggested on the forums (leaving the length computation up to the user in the dataset) is a bit better. Will investigate a bi... | 1,616 | 1,617 | 1,617 | NONE | null | https://github.com/huggingface/transformers/blob/86c6f8a8b1f2bfc6c6d175590efc95a5e6facb51/src/transformers/trainer_pt_utils.py#L506
When using training arg "group_by_length", the sampler has to get the length of every input. it does so by iterating over the dataset in a simple for loop, without the use of a dataload... | {
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https://api.github.com/repos/huggingface/transformers/issues/10908 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10908/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10908/comments | https://api.github.com/repos/huggingface/transformers/issues/10908/events | https://github.com/huggingface/transformers/issues/10908 | 841,221,962 | MDU6SXNzdWU4NDEyMjE5NjI= | 10,908 | Improve the documentation for TrainingArguments.label_names, and if possible raise an error if users misinterpret this attribute like I did | {
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"### Update:\r\n\r\n**I was wrong, my error is originally coming from badly assigned TrainingArguments.label_names. However, I strongly recommend fixes.**\r\n\r\nContinued investigating and realised my error is appearing because I don't understand the attribute `TrainingArguments.label_names`. I thought that it sho... | 1,616 | 1,678 | 1,620 | NONE | null | ### Original Issue Title: Possible typo in trainer.py: prediction_step(), forgetting to exclude loss item of outputs dict when assigning logits
_**Update**: I determined the root cause of my error to stem from an incorrect assignment of `TrainingArgument.label_names`. **There is not a typo** in `Trainer.prediction_s... | {
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https://api.github.com/repos/huggingface/transformers/issues/10907 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10907/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10907/comments | https://api.github.com/repos/huggingface/transformers/issues/10907/events | https://github.com/huggingface/transformers/issues/10907 | 841,204,042 | MDU6SXNzdWU4NDEyMDQwNDI= | 10,907 | Exception: cannot import name 'Regex' from 'tokenizers' | {
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"same problem.\r\n\r\nEdit: I updated the package \"tokenizers\" to the latest version and it works fine.",
"Hi! Do you have a colab so we can reproduce the issue? Or some commands we can run to obtain the same environment you have and test it out?",
"This issue has been automatically marked as stale because it... | 1,616 | 1,620 | 1,620 | NONE | null | From: site-packages/transformers/convert_slow_tokenizer.py
When first-time call:
from transformers import XLMRobertaTokenizer
tokenizers-0.10.1 transformers-4.4.2 | {
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https://api.github.com/repos/huggingface/transformers/issues/10906 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10906/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10906/comments | https://api.github.com/repos/huggingface/transformers/issues/10906/events | https://github.com/huggingface/transformers/pull/10906 | 841,123,665 | MDExOlB1bGxSZXF1ZXN0NjAwOTAzODg2 | 10,906 | Return global attentions (see #7514) | {
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<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/10905 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10905/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10905/comments | https://api.github.com/repos/huggingface/transformers/issues/10905/events | https://github.com/huggingface/transformers/pull/10905 | 841,102,619 | MDExOlB1bGxSZXF1ZXN0NjAwODg2MTU5 | 10,905 | Add ImageFeatureExtractionMixin | {
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This PR adds a new `ImageFeatureExtractionMixin` to implement the common functionality needed for images (conversion to PIL Image / NumPy array /normalize/ resize) in a framework agnostic way. While it only adds support for torch (not tf) tensors as input, support for TF tensors is easy to ad... | {
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https://api.github.com/repos/huggingface/transformers/issues/10904 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10904/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10904/comments | https://api.github.com/repos/huggingface/transformers/issues/10904/events | https://github.com/huggingface/transformers/pull/10904 | 841,077,094 | MDExOlB1bGxSZXF1ZXN0NjAwODY0ODE0 | 10,904 | ONNX export: move sample input to same device as model when inferring shapes | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,616 | 1,619 | 1,619 | CONTRIBUTOR | null | # What does this PR do?
Training a model on a GPU and exporting it afterwards to ONNX has raised a `RuntimeError`, because the model and the [sample input](https://github.com/huggingface/transformers/blob/1a3e0c4fe6868b4eb1105dfe601a79d7e5d11a0f/src/transformers/convert_graph_to_onnx.py#L196) in [`transformers.conve... | {
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https://api.github.com/repos/huggingface/transformers/issues/10903 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10903/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10903/comments | https://api.github.com/repos/huggingface/transformers/issues/10903/events | https://github.com/huggingface/transformers/pull/10903 | 841,046,562 | MDExOlB1bGxSZXF1ZXN0NjAwODM5MDgw | 10,903 | Add 3D attention mask to T5 model (#9643) | {
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"Hey @lexhuismans,\r\n\r\nThanks a lot for your PR! Could you also add a test to verify that T5 can be used with a 3D mask?\r\n",
"Hey @patrickvonplaten,\r\n\r\nThanks for your message. I had a shot in adding a test for the 3D attention mask. The test passed on my device. \r\n\r\nI based the test on a similar tes... | 1,616 | 1,618 | 1,618 | CONTRIBUTOR | null | # What does this PR do?
It allows for 3D attention mask in T5 model (modeling_t5.py).
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https://api.github.com/repos/huggingface/transformers/issues/10902 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10902/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10902/comments | https://api.github.com/repos/huggingface/transformers/issues/10902/events | https://github.com/huggingface/transformers/pull/10902 | 841,024,243 | MDExOlB1bGxSZXF1ZXN0NjAwODIwMjg0 | 10,902 | Add `examples/run_ner_no_trainer.py` | {
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"Ok, added the missing part in Accelerate. In your code, before gathering the labels and predictions, you should pad them across the processes running if `pad_to_max_length` is False:\r\n```python\r\nif not args.pad_to_max_length:\r\n predictions = accelerator.pad_across_processes(predictions, dim=1, pad_index=-... | 1,616 | 1,617 | 1,617 | CONTRIBUTOR | null | This PR adds an example of token classification tasks (`"ner", "pos", "chunk"`) to show the functionalities of the new `accelerate` library.
<hr>
**Reviewers:** @sgugger | {
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https://api.github.com/repos/huggingface/transformers/issues/10901 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10901/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10901/comments | https://api.github.com/repos/huggingface/transformers/issues/10901/events | https://github.com/huggingface/transformers/issues/10901 | 840,959,563 | MDU6SXNzdWU4NDA5NTk1NjM= | 10,901 | Error with detecting cached files when running without Internet connection (related to #10067) | {
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"Related issue: https://github.com/huggingface/transformers/issues/9147, with proposed fix in https://github.com/huggingface/transformers/pull/9807",
"Why do we need this condition?\r\nhttps://github.com/huggingface/transformers/blob/1a3e0c4fe6868b4eb1105dfe601a79d7e5d11a0f/src/transformers/tokenization_utils_bas... | 1,616 | 1,619 | 1,619 | NONE | null | ## Environment info
- `transformers` version: 4.5.0.dev0
- Platform: Linux-3.10.0-957.5.1.el7.x86_64-x86_64-with-centos-7.6.1810-Core
- Python version: 3.7.10
- PyTorch version (GPU?): 1.8.0 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: no
- Using distributed or parallel set-up i... | {
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https://api.github.com/repos/huggingface/transformers/issues/10900 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10900/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10900/comments | https://api.github.com/repos/huggingface/transformers/issues/10900/events | https://github.com/huggingface/transformers/issues/10900 | 840,817,633 | MDU6SXNzdWU4NDA4MTc2MzM= | 10,900 | Getting a model to work on a system with no internet access | {
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"Yes, if you place all files which you find on the model page on the hub in a directory, then it will work.",
"You can even just `git clone` the model repo",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on... | 1,616 | 1,619 | 1,619 | NONE | null | ## Environment info
We are trying to use the model from https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment on a system that has no connection to the internet. Normally one can do:
`pipeline = Pipeline(model='model_name")`
and huggingface will fetch everything it needs from the internet. Unfortunately, ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10899 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10899/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10899/comments | https://api.github.com/repos/huggingface/transformers/issues/10899/events | https://github.com/huggingface/transformers/pull/10899 | 840,759,798 | MDExOlB1bGxSZXF1ZXN0NjAwNTk2MTQz | 10,899 | updates sagemaker documentation | {
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Extends **local environment** configuration and adds import to make it more clear. Also, replaced two links. | {
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https://api.github.com/repos/huggingface/transformers/issues/10898 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10898/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10898/comments | https://api.github.com/repos/huggingface/transformers/issues/10898/events | https://github.com/huggingface/transformers/pull/10898 | 840,650,991 | MDExOlB1bGxSZXF1ZXN0NjAwNTA2Nzk1 | 10,898 | run_glue_no_trainer: datasets -> raw_datasets | {
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"Creating a quick PR now to alert to some issues I'm encountering, will backfill with proper GitHub issues after I knock off from work.\r\n\r\nOther issues:\r\n- [ ] If task_name is `None`, `metrics` is undefined, and will throw `... metrics used before assignment`"
] | 1,616 | 1,616 | 1,616 | CONTRIBUTOR | null | # What does this PR do?
Use the correct variable (raw_datasets) instead of the module (datasets)
where appropriate. The script will otherwise fail with "module object is not subscriptable".
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10897 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10897/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10897/comments | https://api.github.com/repos/huggingface/transformers/issues/10897/events | https://github.com/huggingface/transformers/issues/10897 | 840,627,159 | MDU6SXNzdWU4NDA2MjcxNTk= | 10,897 | [doc] Custom datasets page reference dataset library as NLP library | {
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"Yes, the name should indeed be updated! If you want to do a PR with this, please go ahead!"
] | 1,616 | 1,616 | 1,616 | CONTRIBUTOR | null | ### Who can help
@sgugger
## Information
The page [Fine-tuning with custom datasets](https://huggingface.co/transformers/custom_datasets.html) is referencing dataset library a lot, but in the old name (NLP library), and I've noticed that this still holds true in the [source .rst](https://github.com/huggingfac... | {
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https://api.github.com/repos/huggingface/transformers/issues/10896 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10896/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10896/comments | https://api.github.com/repos/huggingface/transformers/issues/10896/events | https://github.com/huggingface/transformers/issues/10896 | 840,596,156 | MDU6SXNzdWU4NDA1OTYxNTY= | 10,896 | save only the best performing checkpoint | {
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"The checkpoints are saved to resume training in case you are interrupted, so saving only the best checkpoints wouldn't work with this.\r\n\r\nThe `load_best_model_at_end` functionality already keeps track of the best checkpoint during training and reloads it at the end, I think it should cover what you need.",
"... | 1,616 | 1,622 | 1,619 | CONTRIBUTOR | null | # 🚀 Feature request
In the Trainer - Enable an option to save only the best performing checkpoints (rather than the newsest)
## Motivation
Usually when we train a model we would like to keep only the best performing checkpoints (on the dev set according to the specified metric) rather than the newest checkpo... | {
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https://api.github.com/repos/huggingface/transformers/issues/10895 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10895/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10895/comments | https://api.github.com/repos/huggingface/transformers/issues/10895/events | https://github.com/huggingface/transformers/pull/10895 | 840,510,144 | MDExOlB1bGxSZXF1ZXN0NjAwMzg3MDI3 | 10,895 | Add missing global_attentions into the return_dict of Longformer models | {
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"Hey @joe32140,\r\n\r\nSorry, I think this PR already fixes the problem: https://github.com/huggingface/transformers/pull/10906/files"
] | 1,616 | 1,617 | 1,617 | NONE | null | The `global_attentions` is missing in the return_dict of `LongformerForSequenceClassification`, `LongformerForMaskedLM`, and `LongformerForTokenClassification` classes in `modeling_longformer.py`.
# What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/10894 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10894/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10894/comments | https://api.github.com/repos/huggingface/transformers/issues/10894/events | https://github.com/huggingface/transformers/issues/10894 | 840,459,883 | MDU6SXNzdWU4NDA0NTk4ODM= | 10,894 | Invalid argument: Incompatible shapes: [24,1536,12,514] vs. [24,1536,12,513] | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,616 | 1,678 | 1,619 | NONE | null | I had a 16 class classification dataset, but I am getting an error when using longformer, what am I doing wrong here?
```
from transformers import LongformerTokenizerFast, TFLongformerForSequenceClassification
import tensorflow as tf
import pickle
tokenizer = LongformerTokenizerFast.from_pretrained('allenai/lo... | {
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https://api.github.com/repos/huggingface/transformers/issues/10893 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10893/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10893/comments | https://api.github.com/repos/huggingface/transformers/issues/10893/events | https://github.com/huggingface/transformers/issues/10893 | 840,357,637 | MDU6SXNzdWU4NDAzNTc2Mzc= | 10,893 | [trainer] large scale models support | {
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"I'm not sure you are aware but the `Trainer` can take a `model_init` parameter that... well... creates the model ;-) Have you explored how it could help with this particular problem?\r\n\r\nThe changes in the other parts of the lib look reasonable to me at first glance.",
"Thanks for the very detailed summary @s... | 1,616 | 1,621 | 1,621 | CONTRIBUTOR | null | As I am integrating DeepSpeed ZeRO-3 which can run on hundreds of gpus and train models with Trillion of params
https://github.com/huggingface/transformers/pull/10753 I see an emerging need to adjust how the trainer is used.
Currently the usage is:
```
model = T5ForConditionalGeneration.from_pretrained("t5-smal... | {
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https://api.github.com/repos/huggingface/transformers/issues/10892 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10892/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10892/comments | https://api.github.com/repos/huggingface/transformers/issues/10892/events | https://github.com/huggingface/transformers/issues/10892 | 840,219,002 | MDU6SXNzdWU4NDAyMTkwMDI= | 10,892 | ImportError: cannot import name 'BertLayerNorm' when upgrading to latest transformers | {
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"There is no `BertLayerNorm` anymore since all it was adding has been ported to main PyTorch. The BERT model is now jusing `torch.nn.LayerNorm`.\r\n\r\nSo to make your code working, instead of trying to import it from transformers, just define it as:\r\n```\r\nBertLayerNorm = torch.nn.LayerNorm\r\n```",
"@sgugger... | 1,616 | 1,617 | 1,617 | NONE | null | # 📚 Migration
## Getting error when upgrading from pytorch-transformers to transformers
<!-- Important 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: Yes
* [ ] ... | {
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(Separate note, doing a full replay for long runs is pretty annoying --> thi... | {
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https://api.github.com/repos/huggingface/transformers/issues/10890 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10890/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10890/comments | https://api.github.com/repos/huggingface/transformers/issues/10890/events | https://github.com/huggingface/transformers/pull/10890 | 840,061,982 | MDExOlB1bGxSZXF1ZXN0NTk5OTgwODUx | 10,890 | Remove version warning in pretrained BART models | {
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This PR fixes the warnings when loading any pretrained BART model:
```
Some weights of the model checkpoint at facebook/bart-large-mnli were not used when initializing BartModelForSequenceClassification: ['model.encoder.version', 'model.decoder.version']
- This IS expected if you are initi... | {
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https://api.github.com/repos/huggingface/transformers/issues/10889 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10889/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10889/comments | https://api.github.com/repos/huggingface/transformers/issues/10889/events | https://github.com/huggingface/transformers/pull/10889 | 840,057,322 | MDExOlB1bGxSZXF1ZXN0NTk5OTc2NzI5 | 10,889 | Fix overflowing bad word ids | {
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This is an issue when an invalid bad word ID is defined: if the vocab size is 30k, then defining a bad word ID for `30001` crashes the generation function with the following error:
```
torch.sparse.... | {
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https://api.github.com/repos/huggingface/transformers/issues/10888 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10888/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10888/comments | https://api.github.com/repos/huggingface/transformers/issues/10888/events | https://github.com/huggingface/transformers/pull/10888 | 840,049,189 | MDExOlB1bGxSZXF1ZXN0NTk5OTY5Nzcy | 10,888 | Instantiate model only once in pipeline | {
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"Checked all the slow tests run. I have no idea on how to implement a test that checks the model is only loaded once, so I'm going merge this and if anyone wants to tackle that, it can be done in a separate PR."
] | 1,616 | 1,617 | 1,617 | COLLABORATOR | null | # What does this PR do?
The current implementation of `pipeline` is inefficient in the sense it instantiates the model twice just to guess the proper framework. This PR does not add any breaking change but reworks the function that infers the framework from the model to:
1. instantiate the proper class of the model... | {
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"Please note: This checkpoint uses BertModel with XLMRobertaTokenizer so AutoTokenizer won't work with this checkpoint!"
] | 1,616 | 1,616 | 1,616 | NONE | null | ## Code Snippet
```
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("microsoft/Multilingual-MiniLM-L12-H384")
model = AutoModel.from_pretrained("microsoft/Multilingual-MiniLM-L12-H384")
```
- `transformers` version: 4.1.1, 3.1.0 (error in both)
## Error
```
T... | {
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https://api.github.com/repos/huggingface/transformers/issues/10886 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10886/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10886/comments | https://api.github.com/repos/huggingface/transformers/issues/10886/events | https://github.com/huggingface/transformers/pull/10886 | 839,883,567 | MDExOlB1bGxSZXF1ZXN0NTk5ODI2MDE0 | 10,886 | Fix comment in modeling_t5.py | {
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This PR completes an incomplete comment in the modeling_t5.py file.
`# ourselves in which case we just need to make it broadcastable to all heads.`
to
```
# We can provide a self-attention mask of dimensions [batch_size, from_seq_length, to_seq_length]
# ourselves in which case we jus... | {
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"I tried adding\r\n```python\r\ndel training_args\r\ndel trainer\r\ndel model_config\r\ndel run\r\ngc.collect()\r\nth.cuda.empty_cache()\r\n```\r\nto the end of each loop, but it does not seem to change anything. ",
"I think the memory problem comes from the wandb integration. I do not see the problem without it:... | 1,616 | 1,616 | 1,616 | CONTRIBUTOR | null | The problem is that GPU memory allocated accumulates for each run. This eventually results in a `RuntimeError: CUDA out of memory` error. You can see the wandb GPU memory allocated, produced by the code below, here: [wandb](https://wandb.ai/jwa018/Bug/reports/Shared-panel-21-03-24-15-03-56--Vmlldzo1NTYxODI?accessToken=... | {
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https://api.github.com/repos/huggingface/transformers/issues/10884 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10884/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10884/comments | https://api.github.com/repos/huggingface/transformers/issues/10884/events | https://github.com/huggingface/transformers/issues/10884 | 839,690,619 | MDU6SXNzdWU4Mzk2OTA2MTk= | 10,884 | Wav2vec2 Training Loss not decreasing | {
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"It seems that your training epochs is set to 1500. Set it up to 5 for a quick trial",
"It is giving training loss of more than a 100 in that case!",
"Is your training finished or is still running? If it is the second, just try again with less number of epochs for example",
"This is the output for 5 epochs:\r... | 1,616 | 1,621 | 1,621 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version:4.4.0
- Platform: Google Colab
- Python version: python 3.6
@patrickvonplaten
Models:
wav2vec2
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Includes:
- a non-English example (English, French)
- DataCollatorForSeq2Seq
- label padding with -100 (ignore in loss)
- Wandb integration | {
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"Found solution from [#10446](https://github.com/huggingface/transformers/issues/10446).\r\n\r\nShould follow this step instead:\r\n`git clone https://github.com/huggingface/transformers`\r\n\r\n`cd transformers`\r\n\r\n`pip install .`\r\n\r\n"
] | 1,616 | 1,616 | 1,616 | NONE | null | **Environment**
Google Colab. Installed the '4.5.0.dev0' version of transformers by `!pip install git+https://github.com/huggingface/transformers
`
**Issues**
Hi guys, I tried to fine-tune RoBERTa on WikiText-2 by following the commands shared in the examples/language-modeling section of the [github page](htt... | {
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https://api.github.com/repos/huggingface/transformers/issues/10881 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10881/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10881/comments | https://api.github.com/repos/huggingface/transformers/issues/10881/events | https://github.com/huggingface/transformers/issues/10881 | 839,482,123 | MDU6SXNzdWU4Mzk0ODIxMjM= | 10,881 | MlFlow log artefacts | {
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"I have no written the `MLFlowCallback` (external integrations are maintained by contributors or the authors of the external libraries themselves) but I can confirm the command will indeed not log the model weights. The callback does get the model in the kwargs, so it's completely possible to get it from there and ... | 1,616 | 1,680 | 1,619 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.4.2
- Platform: Darwin-20.3.0-x86_64-i386-64bit
- Python version: 3.7.4
- PyTorch version (GPU?): 1.3.1 (F... | {
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https://api.github.com/repos/huggingface/transformers/issues/10880 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10880/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10880/comments | https://api.github.com/repos/huggingface/transformers/issues/10880/events | https://github.com/huggingface/transformers/issues/10880 | 839,425,154 | MDU6SXNzdWU4Mzk0MjUxNTQ= | 10,880 | Scheduler Not Pickleable | {
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"Succeed to reproduce with another model and dataset.\r\n\r\nhttps://gist.github.com/iamNCJ/a30afcbac392f6036bed65198ce5295e\r\n\r\n[gist](https://gist.github.com/iamNCJ/a30afcbac392f6036bed65198ce5295e)\r\n\r\nThis gist is derived from [an example provided by the pytorch lightening team](https://colab.research.goo... | 1,616 | 1,619 | 1,619 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.4.2
- Platform: Linux-3.10.0-1127.13.1.el7.x86_64-x86_64-with-glibc2.10
- Python version: 3.8.8 (Anaconda)
... | {
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https://api.github.com/repos/huggingface/transformers/issues/10879 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10879/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10879/comments | https://api.github.com/repos/huggingface/transformers/issues/10879/events | https://github.com/huggingface/transformers/pull/10879 | 839,393,774 | MDExOlB1bGxSZXF1ZXN0NTk5NDE2Nzky | 10,879 | error type of tokenizer in __init__ definition | {
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```
tokenizer: Optional["PreTrainedTokenizerBase"] = None,
```
it should be
```
tokenizer: Optional[PreTrainedTokenizerBase] = None,
```
# What does this PR do?
<!--
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https://api.github.com/repos/huggingface/transformers/issues/10878 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10878/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10878/comments | https://api.github.com/repos/huggingface/transformers/issues/10878/events | https://github.com/huggingface/transformers/issues/10878 | 839,325,292 | MDU6SXNzdWU4MzkzMjUyOTI= | 10,878 | RuntimeError: while running run_common_voice.py (XLSR wav2vec finetuning week) | {
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"I am experiencing the same error. I have been all the day working around without solving it. I have tried trough Docker Cuda versions 9.2, 10.0 and 10.1 and different versions of pytorch including 1.3, 1.5 and 1.6. I have tried with different combinations of GTX1080 and RTX2080\r\n\r\nAdding \"--ddp_find_unused_pa... | 1,616 | 1,619 | 1,619 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.5.0.dev0 (I tried running it on 4.4.0 as well, gave the same error)
- Platform: Ubuntu (running on a virtual... | {
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https://api.github.com/repos/huggingface/transformers/issues/10877 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10877/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10877/comments | https://api.github.com/repos/huggingface/transformers/issues/10877/events | https://github.com/huggingface/transformers/issues/10877 | 839,293,419 | MDU6SXNzdWU4MzkyOTM0MTk= | 10,877 | `XLMRobertaTokenizer` `encode_plus` api producing `<unk>` for a valid token | {
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"Hi, thanks for opening an issue! Seen with @n1to, and this comes from the Unigram-based tokenizers: Unigram's tokenize cuts the string into tokens, and then converts them to IDs. Unknown tokens are detected during the token to IDs conversion, rather than when the string is cut into tokens.\r\n\r\nThis is different... | 1,616 | 1,619 | 1,617 | NONE | null | ## Environment info
- `transformers` version: 4.5.0.dev0 (latest master)
- Platform: Windows-10-10.0.19041-SP0
- Python version: 3.7.10
- PyTorch version (GPU?): not installed (NA)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No
... | {
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https://api.github.com/repos/huggingface/transformers/issues/10876 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10876/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10876/comments | https://api.github.com/repos/huggingface/transformers/issues/10876/events | https://github.com/huggingface/transformers/pull/10876 | 839,211,286 | MDExOlB1bGxSZXF1ZXN0NTk5MjYyMzc0 | 10,876 | Add new notebook links in the docs | {
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"Oh actually, an additional comment: the title of the summarization notebook is currently \"Text classification on GLUE\" (and same for the translation)",
"Fixed the titles and the sentence, so merging. Thanks for the review!"
] | 1,616 | 1,616 | 1,616 | COLLABORATOR | null | # What does this PR do?
This PR adds links to the three missing tasks in the notebooks page: multiple choice, translation and summarization. | {
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https://api.github.com/repos/huggingface/transformers/issues/10875 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10875/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10875/comments | https://api.github.com/repos/huggingface/transformers/issues/10875/events | https://github.com/huggingface/transformers/pull/10875 | 839,187,923 | MDExOlB1bGxSZXF1ZXN0NTk5MjQyNTk1 | 10,875 | Fix test_trainer_distributed | {
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#10861 introduced a change in the way metrics are prefixed byt default in `Trainer.predict`, which in turn made `tests/test_trainer_distributed.py` fail. This PR fixes that.
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https://api.github.com/repos/huggingface/transformers/issues/10874 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10874/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10874/comments | https://api.github.com/repos/huggingface/transformers/issues/10874/events | https://github.com/huggingface/transformers/issues/10874 | 839,082,427 | MDU6SXNzdWU4MzkwODI0Mjc= | 10,874 | transformers.models.auto.tokenization_auto | {
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"Could you reproduce this in a colab so that we can take a look? Thanks!",
"I reworked my code so I didn't get the error anymore I'm honestly not sure how it got fixed",
"I think it maybe because I didn't restart the runtime\r\n",
"This issue has been automatically marked as stale because it has not had recen... | 1,616 | 1,619 | 1,619 | NONE | null | I installed the version transformers 3.5.1 to get the version in GitHub using !pip3 install transformers==3.5.1 and !pip3 install transformers but then when I try to install SentenceTransofrmer using : from sentence_transformers import SentenceTransformer I get ModuleNotFoundError: No module named 'transformers.models.... | {
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"Wav2Vec2 Pre-Training is more important.",
"I would also like to be able to pre-train a Wav2Vec2 model using my own raw audio files in a self-supervised way. It would be even better if I could use a pre-trained model as a starting point. Is there any way to do this currently?",
"@czonios Yes, you can fine-tune... | 1,616 | 1,623 | 1,623 | NONE | null | Dear 🤗-team,
I'd like to do pre-training with your implementation of Wav2Vec2 and/or XLRS-Wav2Vec2. I was wondering if there are any plans to add such scripts (or even a demo) to the repository?
PS: I already did pre-training in NVIDIA NeMo, but I'm having problems with porting my checkpoints. Being able to do e... | {
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https://api.github.com/repos/huggingface/transformers/issues/10872 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10872/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10872/comments | https://api.github.com/repos/huggingface/transformers/issues/10872/events | https://github.com/huggingface/transformers/issues/10872 | 838,971,320 | MDU6SXNzdWU4Mzg5NzEzMjA= | 10,872 | Training GPT2 does not use GPU | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,616 | 1,619 | 1,619 | NONE | null | Im using [run_clm.py](https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_clm.py) to train GPT2. When using the [example from the documetnation](https://github.com/huggingface/transformers/tree/master/examples/language-modeling) it works fine and uses the GPU. But when I start it on m... | {
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https://api.github.com/repos/huggingface/transformers/issues/10871 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10871/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10871/comments | https://api.github.com/repos/huggingface/transformers/issues/10871/events | https://github.com/huggingface/transformers/issues/10871 | 838,969,705 | MDU6SXNzdWU4Mzg5Njk3MDU= | 10,871 | not created config.json in Wav2Vec2ForCTC for ASR | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,616 | 1,619 | 1,619 | NONE | null | After saving the trained file I can to read the model. Here gives the error
/content/gdrive/MyDrive/wav2vec2-large-xlsr-hindi' is the correct path to a directory containing a config.json file
Here is my reading model
model = Wav2Vec2ForCTC.from_pretrained("/content/gdrive/MyDrive/wav2vec2-large-xlsr-hindi").to("c... | {
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https://api.github.com/repos/huggingface/transformers/issues/10870 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10870/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10870/comments | https://api.github.com/repos/huggingface/transformers/issues/10870/events | https://github.com/huggingface/transformers/pull/10870 | 838,944,405 | MDExOlB1bGxSZXF1ZXN0NTk5MDM5Mjg2 | 10,870 | Sm trainer smp init fix | {
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"LGTM! I ran one training job successfully with these changes. ",
"I tested it with `pytorch1.7.1`\r\n`564829616587.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:1.7.1-transformers4.4.0-py36-gpu-cu110-ubuntu18.04` \r\nand `pytorch1.6` \r\n`763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-py... | 1,616 | 1,616 | 1,616 | MEMBER | null | # What does this PR do?
Fixes `SageMakerTrainer` `smp.init` for `smp 1.3`. It also removes the `is_smdistributed_available` for are more robust `is_sagemaker_model_parallel_available`.
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,616 | 1,622 | 1,622 | NONE | null | ## Environment info
- `transformers` version: 4.1.1
- Platform: Linux-4.15.0-45-generic-x86_64-with-debian-10.2
- Python version: 3.7.3
- PyTorch version (GPU?): 1.7.1 (True)
- Tensorflow version (GPU?): 2.4.1 (False)
- Using GPU in script?: yes
- Using distributed or parallel set-up in script?: no
### Who ca... | {
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https://api.github.com/repos/huggingface/transformers/issues/10868 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10868/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10868/comments | https://api.github.com/repos/huggingface/transformers/issues/10868/events | https://github.com/huggingface/transformers/pull/10868 | 838,875,652 | MDExOlB1bGxSZXF1ZXN0NTk4OTgxNjY5 | 10,868 | [Examples] Added predict stage and Updated Example Template | {
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* Adds Predict stage in `run_xlni.py` text-classification example
* Updated Example Template for Predict Stage
Fixes #10482
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor g... | {
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Adds the Documentation page for "Run training on Amazon SageMaker". | {
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"Hey @flozi00,\r\n\r\nCould you make the code quality test pass -> then I think we can merge this one :-)"
] | 1,616 | 1,619 | 1,619 | CONTRIBUTOR | null | # What does this PR do?
This PR stores the resampled commoinvoice on disk to speedup multiple runs.
Furthermore it adds data augmentation to double the dataset size
<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with t... | {
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https://api.github.com/repos/huggingface/transformers/issues/10865 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10865/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10865/comments | https://api.github.com/repos/huggingface/transformers/issues/10865/events | https://github.com/huggingface/transformers/pull/10865 | 838,730,017 | MDExOlB1bGxSZXF1ZXN0NTk4ODYwMDYy | 10,865 | Update the example template for a no Trainer option | {
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Expand the template of new examples with a new option to build an example like the new [run_glue_no_trainer.py](https://github.com/huggingface/transformers/blob/master/examples/text-classification/run_glue_no_trainer.py). | {
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"Hello! I would guess something is wrongly setup in your local environment; especially it it works in colab! Are you sure you're using the `python` from the same environment as your `pip3`?",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs t... | 1,616 | 1,619 | 1,619 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.4.2
- Platform: MACOS
- Python version: Python 3.6.13
- PyTorch version (GPU?): 1.8.0 (cpu)
- Tensorflow ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10863 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10863/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10863/comments | https://api.github.com/repos/huggingface/transformers/issues/10863/events | https://github.com/huggingface/transformers/pull/10863 | 838,603,070 | MDExOlB1bGxSZXF1ZXN0NTk4NzU2ODE4 | 10,863 | Fix p_mask cls token masking in question-answering pipeline | {
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It fixes a really small bug described in detail in the issue - it only adds a condition to the if statement responsible for unmasking the `cls_token_id` in the `p_mask` used in the question answering pipeline.
Fixes #10810
## Who can review?
Anyone in the community is free to review the... | {
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https://api.github.com/repos/huggingface/transformers/issues/10862 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10862/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10862/comments | https://api.github.com/repos/huggingface/transformers/issues/10862/events | https://github.com/huggingface/transformers/pull/10862 | 838,480,609 | MDExOlB1bGxSZXF1ZXN0NTk4NjU1ODA3 | 10,862 | Fixed confusing order of args in generate() docstring | {
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<!--
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/10861 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10861/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10861/comments | https://api.github.com/repos/huggingface/transformers/issues/10861/events | https://github.com/huggingface/transformers/pull/10861 | 838,348,266 | MDExOlB1bGxSZXF1ZXN0NTk4NTQzMjUw | 10,861 | [trainer] Fixes Typo in Predict Method of Trainer | {
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Fixes typo in Predict Method of Trainer. This will enable saving files with the correct prefix `test` in Predict stage. Earlier it was saving it with the `eval` prefix for both predict and evaluate stage.
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismi... | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,616 | 1,619 | 1,619 | CONTRIBUTOR | null | (Sorry I can not visit the forum.)
Any one know where to get them?
Thank you and thank you.
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@LysandreJik, @sgugger | {
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https://api.github.com/repos/huggingface/transformers/issues/10858 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10858/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10858/comments | https://api.github.com/repos/huggingface/transformers/issues/10858/events | https://github.com/huggingface/transformers/issues/10858 | 838,268,704 | MDU6SXNzdWU4MzgyNjg3MDQ= | 10,858 | If run trainer._maybe_log_save_evaluate() twice continuously, it will appear “ZeroDivisionError: float division by zero” | {
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"@niuzaisheng The function starting with '_' is a hint that this is an internal function and is not for external use. Is there any particular reason you are using this and not any alternatives?",
"Looking into the function `_maybe_log_save_evaluate` should ideally not contain line 1225 `self._globalstep_last_logg... | 1,616 | 1,616 | 1,616 | NONE | null | ## Environment info
- `transformers` version: 4.3.3
- Platform: Linux-4.15.0-139-generic-x86_64-with-debian-buster-sid
- Python version: 3.7.0
- PyTorch version (GPU?): 1.8.0+cu111 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: Irrelevant
- Using distributed or parallel set-up i... | {
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https://api.github.com/repos/huggingface/transformers/issues/10857 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10857/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10857/comments | https://api.github.com/repos/huggingface/transformers/issues/10857/events | https://github.com/huggingface/transformers/pull/10857 | 838,124,305 | MDExOlB1bGxSZXF1ZXN0NTk4MzU0MTA2 | 10,857 | Make convert_to_onnx runable as script again | {
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When rewroking the inits, `convert_graph_to_onnx.py` got its import replaced by relative imports which broke the fact it can be run as a script. This PR fixes that. | {
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https://api.github.com/repos/huggingface/transformers/issues/10856 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10856/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10856/comments | https://api.github.com/repos/huggingface/transformers/issues/10856/events | https://github.com/huggingface/transformers/pull/10856 | 838,005,439 | MDExOlB1bGxSZXF1ZXN0NTk4MjU0NjY2 | 10,856 | Use DataCollatorForSeq2Seq in run_summarization in all cases | {
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"Thanks a lot!"
] | 1,616 | 1,616 | 1,616 | CONTRIBUTOR | null | # What does this PR do?
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"Hi @sergej-d \r\n\r\nThe `run_translation.py` script now supports fine-tuning `M2M100` (see #11170), for this model you should now also pass the `--forced_bos_token` argument which is usually similar to the the `--target_lang` ",
"This issue has been automatically marked as stale because it has not had recent ac... | 1,616 | 1,621 | 1,621 | NONE | null | - `transformers` version: 4.5.0.dev0
- Python version: 3.8
- PyTorch version (GPU?): 1.7.1+cu110
- Using GPU in script?: Yes, RTX 3090
- Using distributed or parallel set-up in script?: No
I am trying to finetune m2m:
python3 run_translation.py \
--model_name_or_path=facebook/m2m100_418M \
--do_trai... | {
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https://api.github.com/repos/huggingface/transformers/issues/10854 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10854/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10854/comments | https://api.github.com/repos/huggingface/transformers/issues/10854/events | https://github.com/huggingface/transformers/pull/10854 | 837,794,114 | MDExOlB1bGxSZXF1ZXN0NTk4MDc1NjQw | 10,854 | Run summarization always use data collator for seq2 seq | {
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https://api.github.com/repos/huggingface/transformers/issues/10853 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10853/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10853/comments | https://api.github.com/repos/huggingface/transformers/issues/10853/events | https://github.com/huggingface/transformers/issues/10853 | 837,692,755 | MDU6SXNzdWU4Mzc2OTI3NTU= | 10,853 | Error building extension 'fused_adam' | {
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"Could you paste the whole stacktrace you're having? Also it seems you're running on a colab, would it be possible to share that colab so we can take a look? Thank you!\r\nPinging @stas00 ",
"1. As @LysandreJik suggested always report the full backtrace\r\n2. deepspeed requires a pytorch matching cuda version ins... | 1,616 | 1,616 | 1,616 | NONE | null | Hi,
I recently updated `transformers` to `4.4.2` for `DebertaV2` and while training DebertaV2 with DeepSpeed, got an error regarding `deepspeed` version. So I upgraded to latest deepspeed (0.3.13) and started training and getting this error -
**RuntimeError: Error building extension 'fused_adam'**
Here is the... | {
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https://api.github.com/repos/huggingface/transformers/issues/10852 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10852/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10852/comments | https://api.github.com/repos/huggingface/transformers/issues/10852/events | https://github.com/huggingface/transformers/issues/10852 | 837,656,414 | MDU6SXNzdWU4Mzc2NTY0MTQ= | 10,852 | Longformer training : CUDA error: device-side assert triggered | {
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"Seems like my issue. Maybe can help: https://github.com/huggingface/transformers/issues/10832",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the... | 1,616 | 1,686 | 1,619 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version:
- Platform:
- Python version: 3.7
- PyTorch version (GPU?):
- Tensorflow version (GPU?):
- Using GPU in s... | {
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https://api.github.com/repos/huggingface/transformers/issues/10851 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10851/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10851/comments | https://api.github.com/repos/huggingface/transformers/issues/10851/events | https://github.com/huggingface/transformers/issues/10851 | 837,633,317 | MDU6SXNzdWU4Mzc2MzMzMTc= | 10,851 | Small inconsistency in tokenization_utils for special tokens retrieval | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,616 | 1,619 | 1,619 | NONE | null | Hi there,
This is just a minor issue I have spotted.
When a special token (cls_token, sep_token, etc.) is accessed in an instantiated Tokenizer, this is the piece of code executed to retrieve the property:
```python
@property
def eos_token(self) -> str:
"""
:obj:`str`: End of sentence... | {
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https://api.github.com/repos/huggingface/transformers/issues/10850 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10850/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10850/comments | https://api.github.com/repos/huggingface/transformers/issues/10850/events | https://github.com/huggingface/transformers/issues/10850 | 837,548,277 | MDU6SXNzdWU4Mzc1NDgyNzc= | 10,850 | How to train encoder decoder for explicit negation generation | {
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"Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.\r\nCould you ask your question on the [forum](https://discusss.huggingface.co) instead?\r\n\r\nThanks!"
] | 1,616 | 1,617 | 1,617 | NONE | null | Hi
I am trying to generate negations out of non-negated sentences.
I used a simple “I have tea” => “I don’t have tea” formatted dataset for training an XLMR encoder-decoder model using the example provided in the collab.
```
# set special tokens
roberta_shared.config.decoder_start_token_id = tokenizer.bos_toke... | {
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https://api.github.com/repos/huggingface/transformers/issues/10849 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10849/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10849/comments | https://api.github.com/repos/huggingface/transformers/issues/10849/events | https://github.com/huggingface/transformers/pull/10849 | 837,512,926 | MDExOlB1bGxSZXF1ZXN0NTk3ODM3MzMx | 10,849 | Fix: typo in FINE_TUNE_XLSR_WAV2VEC2.md | {
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# What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/10848 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10848/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10848/comments | https://api.github.com/repos/huggingface/transformers/issues/10848/events | https://github.com/huggingface/transformers/pull/10848 | 837,467,742 | MDExOlB1bGxSZXF1ZXN0NTk3Nzk5MTM4 | 10,848 | GPT Neo | {
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"@sdtblck @leogao2 this is the Neo PR, reviews/comments appreciated !",
"I tried running this with the 2.7B checkpoint and got \r\n```\r\n(base) stellabiderman@Stellas-MacBook-Pro research % python transformers/src/transformers/models/gpt_neo/convert_gpt_neo_mesh_tf_to_pytorch.py --tf_checkpoint_path GPT3_2.7B/ch... | 1,616 | 1,617 | 1,617 | MEMBER | null | # What does this PR do?
This PR adds the [GPT Neo model](https://github.com/EleutherAI/gpt-neo).
The model architecture is very similar to GPT2 except it local attention in alternate layers
- `LocalAttention` module implements the local attention. The implementation is not as clean as it should be and will be cl... | {
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https://api.github.com/repos/huggingface/transformers/issues/10847 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10847/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10847/comments | https://api.github.com/repos/huggingface/transformers/issues/10847/events | https://github.com/huggingface/transformers/pull/10847 | 837,440,327 | MDExOlB1bGxSZXF1ZXN0NTk3Nzc1OTA2 | 10,847 | fix code quality issues | {
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"Hi @LysandreJik :wave: Please review this PR",
"Hi @withshubh, as said before in https://github.com/huggingface/transformers/pull/8950#issuecomment-781222459, we would like to stay with our current tooling for now. Thank you."
] | 1,616 | 1,617 | 1,617 | NONE | null | ### Description
Hi :wave: I sent PR #8950 which has changes in a lot of files so sending this PR with fixes in few files so that it can be easily reviewed.
You can have a look at the various issues that were caught in the codebase [here](https://deepsource.io/gh/withshubh/transformers/issues/?category=recommended... | {
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https://api.github.com/repos/huggingface/transformers/issues/10846 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10846/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10846/comments | https://api.github.com/repos/huggingface/transformers/issues/10846/events | https://github.com/huggingface/transformers/pull/10846 | 837,416,229 | MDExOlB1bGxSZXF1ZXN0NTk3NzU1Mzc4 | 10,846 | [Wav2Vec2] Small tab fix | {
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<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this w... | {
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https://api.github.com/repos/huggingface/transformers/issues/10845 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10845/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10845/comments | https://api.github.com/repos/huggingface/transformers/issues/10845/events | https://github.com/huggingface/transformers/issues/10845 | 837,396,118 | MDU6SXNzdWU4MzczOTYxMTg= | 10,845 | Option to change loss function for fine tuning | {
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"You can change the loss function to anything you want. Here's an example:\r\n\r\n```\r\nfrom transformers import BertModel\r\nfrom transformers.modeling_outputs import SequenceClassifierOutput\r\nimport torch.nn as nn\r\n\r\nclass FancyBertModelWithCustomLossFunction(nn.Module):\r\n def __init__(self):\r\n ... | 1,616 | 1,616 | 1,616 | NONE | null | # 🚀 Feature request
## Motivation
I was working in a multi class text classification problem for which I was using `DistilBertForSequenceClassification` and I found out that there is no way for me to change the loss function from CrossEntropyLoss.
## Your contribution
I can submit a PR, if this feature re... | {
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https://api.github.com/repos/huggingface/transformers/issues/10844 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10844/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10844/comments | https://api.github.com/repos/huggingface/transformers/issues/10844/events | https://github.com/huggingface/transformers/issues/10844 | 837,364,574 | MDU6SXNzdWU4MzczNjQ1NzQ= | 10,844 | Add GPT-Neo | {
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Please add GPT-Neo
## Model description
> GPT-Neo is the code name for a series of transformer-based language models loosely styled around the GPT architecture that Eleuther AI plans to train and open source. Eleuther AI's primary goal is to replicate a GPT-3 sized model and open source... | {
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https://api.github.com/repos/huggingface/transformers/issues/10843 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10843/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10843/comments | https://api.github.com/repos/huggingface/transformers/issues/10843/events | https://github.com/huggingface/transformers/issues/10843 | 837,324,819 | MDU6SXNzdWU4MzczMjQ4MTk= | 10,843 | Is there a `DataCollator` cat mask n-gram words for LM? | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,616 | 1,619 | 1,619 | NONE | null | # 📚 Migration
## Information
I want a mask n-gram words when pre-train bert model? but I can't find a DataCollator from the lib
https://github.com/huggingface/transformers/blob/master/src/transformers/data/data_collator.py
I want to build it by myself, but I don't know how to build my own DataCollator, who ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10842 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10842/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10842/comments | https://api.github.com/repos/huggingface/transformers/issues/10842/events | https://github.com/huggingface/transformers/issues/10842 | 837,272,360 | MDU6SXNzdWU4MzcyNzIzNjA= | 10,842 | How to fine-tune RAG on MS-MARCO dataset? | {
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"Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.\r\nCould you ask your question on the [forum](https://discusss.huggingface.co) instead?\r\n\r\nThanks!"
] | 1,616 | 1,616 | 1,616 | NONE | null | {
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https://api.github.com/repos/huggingface/transformers/issues/10841 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10841/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10841/comments | https://api.github.com/repos/huggingface/transformers/issues/10841/events | https://github.com/huggingface/transformers/issues/10841 | 837,267,087 | MDU6SXNzdWU4MzcyNjcwODc= | 10,841 | issue of run_mlm.py | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,616 | 1,619 | 1,619 | NONE | null | hello guys, I try to finetune bert in my own dataset (line by line txt, language:Chinese), follow the guid code of run_mlm.py example.
The tokenizer is bert pretrained tokenizer (tokenizer=AutoTokenizer.from_pretrained('bert-base-chinese')), and model is bert-base-chinese ,as folllows:
config=BertConfig.from_pret... | {
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https://api.github.com/repos/huggingface/transformers/issues/10840 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10840/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10840/comments | https://api.github.com/repos/huggingface/transformers/issues/10840/events | https://github.com/huggingface/transformers/issues/10840 | 837,249,959 | MDU6SXNzdWU4MzcyNDk5NTk= | 10,840 | why My Albert pretrain loss can't decrease? | {
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"Hi! ALBERT is known to have issues converging in some cases as all layers are shared. See the following issues for similar issues and potential resolutions:\r\n\r\nhttps://github.com/huggingface/transformers/issues/5984\r\nhttps://github.com/huggingface/transformers/issues/4727\r\nhttps://github.com/huggingface/tr... | 1,616 | 1,619 | 1,619 | NONE | null | # 📚 Migration
## Information
<!-- Important information -->
Model i am using Albert
Language I am using the model on just digits(Desensitized Chinese)
The problem arises when using: Albert Trainer
## Details
The loss can decrease normal when I take this config to RoBerta, I use Albert replace RoBert... | {
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https://api.github.com/repos/huggingface/transformers/issues/10839 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10839/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10839/comments | https://api.github.com/repos/huggingface/transformers/issues/10839/events | https://github.com/huggingface/transformers/pull/10839 | 837,202,751 | MDExOlB1bGxSZXF1ZXN0NTk3NTc3NzUx | 10,839 | Fix on_step_begin and on_step_end Callback Sequencing | {
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Currently, the Trainer exhibits the following behavior (simplified):
```
for step, input in epoch_iterator:
if (step + 1) % self.args.gradient_accumulation_steps == 0:
callback_handler.on_step_begin()
...
if (step + 1) % self.args.gradient_accumulation... | {
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https://api.github.com/repos/huggingface/transformers/issues/10838 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10838/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10838/comments | https://api.github.com/repos/huggingface/transformers/issues/10838/events | https://github.com/huggingface/transformers/issues/10838 | 837,188,864 | MDU6SXNzdWU4MzcxODg4NjQ= | 10,838 | Can’t download the pre-trained pegasus-large model | {
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"Hey @xiaohy9,\r\n\r\nThanks for the issue! It should be resolved now. See: https://huggingface.co/google/pegasus-large/commit/4510ba69cc183d23e892e7728a40fdcf42e83079 . \r\n\r\nCould you try again? ",
"Yes, it works now. Thanks for the quick response!\r\nHowever, I saw some similar issue using pegasus-large as u... | 1,616 | 1,619 | 1,619 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.4.2
- Platform:
- Python version: 3.7.10
- PyTorch version (GPU?):
- Tensorflow version (GPU?): 2.4.1
-... | {
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https://api.github.com/repos/huggingface/transformers/issues/10837 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10837/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10837/comments | https://api.github.com/repos/huggingface/transformers/issues/10837/events | https://github.com/huggingface/transformers/issues/10837 | 837,187,665 | MDU6SXNzdWU4MzcxODc2NjU= | 10,837 | pegasus-xsum summarized a story of Eiffel Tower into one on the World Trade Center | {
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"Hey @xiaoda99,\r\n\r\nYou should **not** append a `summarize: ` prefix for Pegasus.\r\n\r\nRunning this code:\r\n\r\n```python\r\ntext1=\"The tower is 324 metres (1,063 ft) tall, about the same height as an 81-storey building, and the tallest structure in Paris. Its base is square, measuring 125 metres (410 ft) on... | 1,616 | 1,619 | 1,619 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.4.2
- Platform:
- Python version: 3.7.10
- PyTorch version (GPU?):
- Tensorflow version (GPU?): 2.4.1
-... | {
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https://api.github.com/repos/huggingface/transformers/issues/10836 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10836/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10836/comments | https://api.github.com/repos/huggingface/transformers/issues/10836/events | https://github.com/huggingface/transformers/issues/10836 | 837,170,205 | MDU6SXNzdWU4MzcxNzAyMDU= | 10,836 | Generating text with MBart Large 50 on GPU with Tensorflow is significantly slower than with Pytorch | {
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"It seems that the generation function is handled by the [`TFGenerationMixin`](https://github.com/huggingface/transformers/blob/696e8a43655a63b7312e036616f4abd2106e179e/src/transformers/generation_tf_utils.py#L48-L72) whereas in torch it is handled by [`GenerationMixin`](https://github.com/huggingface/transformers/... | 1,616 | 1,619 | 1,619 | CONTRIBUTOR | null | This applies to the [MBart Large MMT 50-language model](https://huggingface.co/facebook/mbart-large-50-many-to-many-mmt). Takes about 1m20s to process 10 batches of size 16 x 171 on pytorch, but 8min for tensorflow. Both are running on P100 through Kaggle.
- [Tensorflow notebook](https://www.kaggle.com/xhlulu/tf-mba... | {
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