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https://api.github.com/repos/huggingface/transformers/issues/12946 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12946/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12946/comments | https://api.github.com/repos/huggingface/transformers/issues/12946/events | https://github.com/huggingface/transformers/issues/12946 | 956,500,360 | MDU6SXNzdWU5NTY1MDAzNjA= | 12,946 | ImportError: cannot import name 'BigBirdTokenizer' from 'transformers' | {
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"The sentencepiece library was missing. ",
"`BigBirdTokenizer` requires a sentencepiece installation, but you should have had that error instead of an import error. This is because the `BigBirdTokenizer` was misplaced in the init, the PR linked above fixes it.",
"I sadly only got the import error, nothing else.... | 1,627 | 1,646 | 1,627 | 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: 4.9.1
- Platform: windows
- Python version: 3.9
- PyTorch version (GPU?): 1.9 (CPU)
- Tensorflow version (G... | {
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"This has been solved in v4.9, you should upgrade to the latest version of Transformers.",
"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 [cont... | 1,627 | 1,630 | 1,630 | 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: 4.8.2
- Platform: Linux-5.4.0-1051-aws-x86_64-with-glibc2.10
- Python version: 3.8.5
- PyTorch version (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)... | 1,627 | 1,630 | 1,630 | 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: 4.9.0
- Platform: Linux-5.8.0-63-generic-x86_64-with-debian-bullseye-sid
- Python version: 3.7.10
- PyTorch ... | {
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https://api.github.com/repos/huggingface/transformers/issues/12943 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12943/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12943/comments | https://api.github.com/repos/huggingface/transformers/issues/12943/events | https://github.com/huggingface/transformers/pull/12943 | 956,065,225 | MDExOlB1bGxSZXF1ZXN0Njk5NzIxNjY0 | 12,943 | Moving fill-mask pipeline to new testing scheme | {
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"@LysandreJik I think it' s ready for 2nd review to check that everything you raised is fixed. I'll go on to the next pipeline after that."
] | 1,627 | 1,628 | 1,628 | CONTRIBUTOR | null | # What does this PR do?
Changes the testing of fill-mask so we can test all supported architectures.
Turns out quite a bit are NOT testable (because reference tokenizers do not include
mask token, reformer is a bit tricky to handle too).
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https://api.github.com/repos/huggingface/transformers/issues/12942 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12942/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12942/comments | https://api.github.com/repos/huggingface/transformers/issues/12942/events | https://github.com/huggingface/transformers/issues/12942 | 955,976,366 | MDU6SXNzdWU5NTU5NzYzNjY= | 12,942 | trainer is not reproducible | {
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"The average training loss is indeed not saved and thus you will have a different one restarting from a checkpoint. It's also not a useful metric in most cases, which is why we don't bother. You will notice however that your eval BLEU is exactly the same, so the training yielded the same model at the end.",
"This... | 1,627 | 1,630 | 1,630 | 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: 4.9.1
- Platform: linux
- Python version: 3.7
- PyTorch version (GPU?): 1.9
- Tensorflow version (GPU?): -... | {
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"Was it just a fluke or is the issue still happening? On Colab I have no problem downloading that model.",
"@sgugger Hi it is still happening now. Not just me, many people I know of. I can access the config file from browser, but not through the code. Thanks",
"Still not okay online, but I managed to do it loca... | 1,627 | 1,681 | 1,630 | NONE | null | ## Environment info
It happens in local machine, Colab, and my colleagues also.
- `transformers` version:
- Platform: Window, Colab
- Python version: 3.7
- PyTorch version (GPU?): 1.8.1 (GPU yes)
- Tensorflow version (GPU?):
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: No
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https://api.github.com/repos/huggingface/transformers/issues/12940 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12940/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12940/comments | https://api.github.com/repos/huggingface/transformers/issues/12940/events | https://github.com/huggingface/transformers/issues/12940 | 955,950,852 | MDU6SXNzdWU5NTU5NTA4NTI= | 12,940 | Starting today, I get an error downloading pre-trained models | {
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"Hi @jason-weddington, are you calling those URLs from any particular workload or infrastructure?\r\n\r\nThe only reason I can see where you would get a 403 on this URL is if your usage triggers our infra's firewall. Would you mind contacting us at `expert-acceleration at huggingface.co` so we can take a look?",
... | 1,627 | 1,627 | 1,627 | NONE | null | ## Environment info
Copy-and-paste the text below in your GitHub issue and FILL OUT the two last points.
- `transformers` version: 2.1.1
- Platform: Linux-5.8.0-63-generic-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyTorch version (GPU?): 1.9.0+cu111 (True)
- Tensorflow version (GPU?): not installed (NA)
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https://api.github.com/repos/huggingface/transformers/issues/12939 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12939/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12939/comments | https://api.github.com/repos/huggingface/transformers/issues/12939/events | https://github.com/huggingface/transformers/pull/12939 | 955,946,165 | MDExOlB1bGxSZXF1ZXN0Njk5NjIxMDE3 | 12,939 | Fix from_pretrained with corrupted state_dict | {
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"The test caught something weird with `sshleifer/tiny-distilbert-base-uncased-finetuned-sst-2-english` (another plus for this PR in my opinion!)\r\n\r\nThis model is used in the benchmark tests and in the zero shot pipeline but that model is beyond salvation: its weights have the names of BERT (in the keys) when it... | 1,627 | 1,628 | 1,628 | COLLABORATOR | null | # What does this PR do?
As we discovered in #12843, when a state dictionary contains keys for the body of the model that are not prefixed *and* keys for the head, the body is loaded but the head is ignored with no warning.
This PR fixes that by keeping track of the expected key that do not contain the prefix and ... | {
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https://api.github.com/repos/huggingface/transformers/issues/12938 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12938/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12938/comments | https://api.github.com/repos/huggingface/transformers/issues/12938/events | https://github.com/huggingface/transformers/pull/12938 | 955,878,521 | MDExOlB1bGxSZXF1ZXN0Njk5NTYzNjU4 | 12,938 | Add CpmTokenizerFast | {
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"> I don't think the fast tokenizer as it's written works for now, as the fast tokenizer do not call the `_tokenize` method.\n\nOops! It looks the old pull request isn't right. I'll take a closer look",
"@sgugger I've updated and tested it. It works fine - only needs to wait for the `tokenizer.json` to be uploade... | 1,627 | 1,627 | 1,627 | CONTRIBUTOR | null | # What does this PR do?
Add a fast version of `CpmTokenizer`
Fixes #12837 | {
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https://api.github.com/repos/huggingface/transformers/issues/12937 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12937/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12937/comments | https://api.github.com/repos/huggingface/transformers/issues/12937/events | https://github.com/huggingface/transformers/issues/12937 | 955,717,183 | MDU6SXNzdWU5NTU3MTcxODM= | 12,937 | Not able use TF Dataset on TPU when created via generator in Summarization example | {
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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)... | 1,627 | 1,633 | 1,633 | 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: 4.9.1
- Platform: Kaggle/Colab
- Python version: 3.7.10
- Tensorflow version (GPU?): 2.4.1 / 2.5.1
### Wh... | {
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https://api.github.com/repos/huggingface/transformers/issues/12936 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12936/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12936/comments | https://api.github.com/repos/huggingface/transformers/issues/12936/events | https://github.com/huggingface/transformers/issues/12936 | 955,493,727 | MDU6SXNzdWU5NTU0OTM3Mjc= | 12,936 | `PretrainedTokenizer.return_special_tokens` returns incorrect mask | {
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"Indeed, we have an error in the way the special tokens mask is computed here. See here for the slow tokenizer: https://github.com/huggingface/transformers/blob/3f44a66cb617c72efeef0c0b4201cbe2945d8edf/src/transformers/models/bert/tokenization_bert.py#L297-L299\r\n\r\nThis seems to also be the case for the fast tok... | 1,627 | 1,675 | 1,641 | CONTRIBUTOR | 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: 4.9.1
- Platform: ubuntu
- Python version: 3.8
- PyTorch version (GPU?): 1.9
- Tensorflow version (GPU?):
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https://api.github.com/repos/huggingface/transformers/issues/12935 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12935/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12935/comments | https://api.github.com/repos/huggingface/transformers/issues/12935/events | https://github.com/huggingface/transformers/issues/12935 | 955,444,383 | MDU6SXNzdWU5NTU0NDQzODM= | 12,935 | Better error message? `CUDA error: CUBLAS_STATUS_ALLOC_FAILED` | {
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"That's something we can't solve I suppose, unfortunately. If you have a CUDA error like that, it's always advised to run your code on CPU as it provides a much more informative error message.",
"@NielsRogge \r\nThanks for the answer.\r\n\r\n> it's always advised to run your code on CPU as it provides a much more... | 1,627 | 1,627 | 1,627 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 4.9.1
- Platform: Linux-5.4.104+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.11
- PyTorch version (GPU?): 1.9.0+cu102 (True)
- Tensorflow version (GPU?): 2.5.0 (True)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib... | {
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https://api.github.com/repos/huggingface/transformers/issues/12934 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12934/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12934/comments | https://api.github.com/repos/huggingface/transformers/issues/12934/events | https://github.com/huggingface/transformers/issues/12934 | 955,354,233 | MDU6SXNzdWU5NTUzNTQyMzM= | 12,934 | [Wav2vec Pretrain] KeyError: ‘attention_mask’ | {
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"I've assigned Patrick, but looking at the docs of Wav2Vec2, is says:\r\n\r\n> Wav2Vec2 models that have set config.feat_extract_norm == \"group\", such as wav2vec2-base, have not been trained using attention_mask. For such models, input_values should simply be padded with 0 and no attention_mask should be passed.\... | 1,627 | 1,673 | 1,627 | 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: 4.9.1
- Platform: Google Colab
- Python version: 3.7 & 3.8
- PyTorch version (GPU?): 1.8
- Tensorflow versi... | {
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https://api.github.com/repos/huggingface/transformers/issues/12933 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12933/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12933/comments | https://api.github.com/repos/huggingface/transformers/issues/12933/events | https://github.com/huggingface/transformers/pull/12933 | 955,259,242 | MDExOlB1bGxSZXF1ZXN0Njk5MDM2MzQ2 | 12,933 | ONNX v2 raises an Exception when using PyTorch < 1.8.0 | {
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"@sgugger failing tests seem unrelated to this PR, let you check 👍🏻 "
] | 1,627 | 1,627 | 1,627 | MEMBER | null | {
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https://api.github.com/repos/huggingface/transformers/issues/12932 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12932/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12932/comments | https://api.github.com/repos/huggingface/transformers/issues/12932/events | https://github.com/huggingface/transformers/issues/12932 | 955,150,972 | MDU6SXNzdWU5NTUxNTA5NzI= | 12,932 | Error when trying `push_to_hub` for a fine-tuned model on Colab | {
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"Just tried on a fresh colab and could upload a model without any problem (as long as there is no \"/\" in the model ID). Do you already have a model with the same username maybe?\r\n\r\nNote that you are missing the step `! git config --global user.email \"your_email\"` in the preparation.\r\n\r\nAre you certain y... | 1,627 | 1,627 | 1,627 | 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: 4.9.1
- Platform: Colab
### Who can help
@sgugger
## To reproduce
Steps to reproduce the behavior. T... | {
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https://api.github.com/repos/huggingface/transformers/issues/12931 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12931/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12931/comments | https://api.github.com/repos/huggingface/transformers/issues/12931/events | https://github.com/huggingface/transformers/issues/12931 | 955,035,021 | MDU6SXNzdWU5NTUwMzUwMjE= | 12,931 | How to fuse copy mechnism into the GenerationMixin？ | {
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"Pinging @patrickvonplaten and @patil-suraj ",
"Hey @Hannibal046,\r\n\r\nCould you clarify a bit what you mean by \"copy-mechanism\" ?\r\nMaybe a code example of what you want to do?",
"Hello,I also find others to talk about the `copy mechanism`. in this [link](https://discuss.huggingface.co/t/copying-mechanism... | 1,627 | 1,630 | 1,630 | NONE | null | Hello， is there any way to directly fuse copy mechanism into beamsearch? since the beam_search function receive model_output.logit rather than probabily of vocab?
https://github.com/huggingface/transformers/blob/72aee83ced5f31302c5e331d896412737287f976/src/transformers/generation_utils.py#L1801 | {
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https://api.github.com/repos/huggingface/transformers/issues/12930 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12930/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12930/comments | https://api.github.com/repos/huggingface/transformers/issues/12930/events | https://github.com/huggingface/transformers/pull/12930 | 954,934,587 | MDExOlB1bGxSZXF1ZXN0Njk4NzU2MzU1 | 12,930 | Print defaults when using --help for scripts | {
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"This is indeed a great addition!"
] | 1,627 | 1,628 | 1,627 | COLLABORATOR | null | # What does this PR do?
This PR uses the solution suggested in #12924 to automatically print the defaults of each argument when using `--help` for the script for instance, using `--help` on any of the examples would yield:
```
--push_to_hub [PUSH_TO_HUB]
Whether or not to upload the trai... | {
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https://api.github.com/repos/huggingface/transformers/issues/12929 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12929/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12929/comments | https://api.github.com/repos/huggingface/transformers/issues/12929/events | https://github.com/huggingface/transformers/pull/12929 | 954,857,447 | MDExOlB1bGxSZXF1ZXN0Njk4Njg4Nzc1 | 12,929 | Add option to set max_len in run_ner | {
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This PR adds an option to the set the maximum sequence length in `run_ner`. Pointed out in #12817, this script does not have that option (but the TF version and `run_ner_no_trainer` both have). | {
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https://api.github.com/repos/huggingface/transformers/issues/12928 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12928/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12928/comments | https://api.github.com/repos/huggingface/transformers/issues/12928/events | https://github.com/huggingface/transformers/pull/12928 | 954,847,552 | MDExOlB1bGxSZXF1ZXN0Njk4NjgwMzQ2 | 12,928 | Fix QA examples for roberta tokenizer | {
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https://github.com/huggingface/datasets/pull/2586 has changed the SQUAD dataset and doesn't clean anymore the whitespace in questions. This in turn makes the tokenization fail for tokenizers that don't remove whitespace (like RoBERTa): some questions begin with loooots of spaces and so the tr... | {
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https://api.github.com/repos/huggingface/transformers/issues/12927 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12927/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12927/comments | https://api.github.com/repos/huggingface/transformers/issues/12927/events | https://github.com/huggingface/transformers/pull/12927 | 954,820,673 | MDExOlB1bGxSZXF1ZXN0Njk4NjU3MTUx | 12,927 | Add missing @classmethod decorators | {
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"Fun fact: the poor guy @classmethod will be pinged consistently if you add this handle to the commit message 😂\r\n\r\nI'm removing `@` from it!"
] | 1,627 | 1,627 | 1,627 | CONTRIBUTOR | null | `_BaseAutoModelClass` was missing `@classmethod` decorators on the `from_config(...)` and `from_pretrained(...)` methods. | {
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https://api.github.com/repos/huggingface/transformers/issues/12926 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12926/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12926/comments | https://api.github.com/repos/huggingface/transformers/issues/12926/events | https://github.com/huggingface/transformers/issues/12926 | 954,608,901 | MDU6SXNzdWU5NTQ2MDg5MDE= | 12,926 | Misleading warning when using DPRContextEncoderTokenizer | {
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"Yes you are not using it, but it's the tokenizer that was registered with the checkpoint `'facebook/dpr-ctx_encoder-single-nq-base'` so the library is warning you there is a mismatch (which may be okay in this instance).",
"Thanks, but `facebook/dpr-ctx_encoder-single-nq-base` encoder should be registered as a c... | 1,627 | 1,651 | 1,630 | CONTRIBUTOR | 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: `4.9.1`
- Platform: Ubuntu
- Python version: 3.8.10
- PyTorch version (GPU?): 1.9.0
- Using GPU in script?:... | {
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https://api.github.com/repos/huggingface/transformers/issues/12925 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12925/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12925/comments | https://api.github.com/repos/huggingface/transformers/issues/12925/events | https://github.com/huggingface/transformers/issues/12925 | 954,383,822 | MDU6SXNzdWU5NTQzODM4MjI= | 12,925 | How to reproduce XLNet correctly And What is the config for finetuning XLNet? | {
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"Hi,\r\n\r\nFor training related questions, please refer to the [forum](https://discuss.huggingface.co/). We like to keep Github issues for bugs/feature requests.\r\n\r\nThanks!"
] | 1,627 | 1,627 | 1,627 | NONE | null | I fintune a XLNet for English text classification. But it seems that I did something wrong about it because xlnet-base is worse than bert-base in my case. I set every 1/3 epoch report validation accuracy. At the beginning Bert-base is about 0.50 while XLNet-base is only 0.24. The config I use for xlnet is listed as fol... | {
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https://api.github.com/repos/huggingface/transformers/issues/12924 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12924/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12924/comments | https://api.github.com/repos/huggingface/transformers/issues/12924/events | https://github.com/huggingface/transformers/issues/12924 | 954,364,858 | MDU6SXNzdWU5NTQzNjQ4NTg= | 12,924 | Feature request: Show command line argument defaults | {
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"This is a very reasonable request and thanks for suggesting an easy way to do it! I added that in the PR linked above.",
"Wow, thank you so much for the support and quick turnaround, I really appreciate it!! 🎉 "
] | 1,627 | 1,627 | 1,627 | CONTRIBUTOR | null | # 🚀 Feature request
When running with `--help`, show the default values for command line arguments.
## Motivation
There are dozens of command line arguments. When I'm trying to figure out how to run a script, I often want to know what value is being used when I don't specify it. But running with `--help` does... | {
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https://api.github.com/repos/huggingface/transformers/issues/12923 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12923/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12923/comments | https://api.github.com/repos/huggingface/transformers/issues/12923/events | https://github.com/huggingface/transformers/issues/12923 | 954,340,185 | MDU6SXNzdWU5NTQzNDAxODU= | 12,923 | Transformers onnx export error | {
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"Hi @ZHANG-GuiGui, \r\n\r\nThanks for reporting the issue, I'm looking at it 🧐 ",
"Hi, I'm also having this issue. \r\n\r\n`!python -m transformers.onnx --model=MyModel onnx/MyModelName/`\r\n\r\nExtracting a GPT-2 model.",
"Hi @ZHANG-GuiGui, @johnpaulbin, \r\n\r\nThis is indeed unsupported on PyTorch < 1.8.0.\... | 1,627 | 1,627 | 1,627 | 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: Linux Ubuntu20.04
- Python version: 3.8
- PyTorch version (GPU?): Pytorch1.7.1 Cuda11.0
- Tenso... | {
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https://api.github.com/repos/huggingface/transformers/issues/12922 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12922/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12922/comments | https://api.github.com/repos/huggingface/transformers/issues/12922/events | https://github.com/huggingface/transformers/issues/12922 | 954,257,086 | MDU6SXNzdWU5NTQyNTcwODY= | 12,922 | GPT2 Layers | {
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"It finetunes all the layers. You can set the `require_grads` attribute of the model layers you don't want to train to `False` before sending the model to the `Trainer` if you want to change that behavior.",
"thank you!"
] | 1,627 | 1,627 | 1,627 | NONE | null | When the trainer API is used to finetune gpt-2, does it finetune all the layers or just some? Is there a way to control which layers it finetunes?
gpt2: @patrickvonplaten, @LysandreJik
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https://api.github.com/repos/huggingface/transformers/issues/12921 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12921/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12921/comments | https://api.github.com/repos/huggingface/transformers/issues/12921/events | https://github.com/huggingface/transformers/issues/12921 | 954,249,139 | MDU6SXNzdWU5NTQyNDkxMzk= | 12,921 | LEDForSequenceClassification and LEDForQuestionAnswering example codes don't work. | {
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"Actually we should probs just remove those examples since there is no fine-tuned model anyways...@jacklxc would you like to make a PR? :-)",
"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\nP... | 1,627 | 1,630 | 1,630 | NONE | null | ## Environment info
Tried on both transformers=4.2.0 and the latest transformer package.
### Who can help
@patrickvonplaten
Models:
LED
## Information
LEDForSequenceClassification and LEDForQuestionAnswering example code doesn't work. Please fix these bugs. LEDForConditionalGeneration works though. [he... | {
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https://api.github.com/repos/huggingface/transformers/issues/12920 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12920/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12920/comments | https://api.github.com/repos/huggingface/transformers/issues/12920/events | https://github.com/huggingface/transformers/issues/12920 | 954,148,049 | MDU6SXNzdWU5NTQxNDgwNDk= | 12,920 | Add callback method for substeps during gradient accumulation. | {
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"We can definitely accept a PR with this new method, as it seems there is a clear use case for it."
] | 1,627 | 1,627 | 1,627 | CONTRIBUTOR | null | # 🚀 Feature request
Add a callback method which is called between `on_step_begin` and `on_step_end` i.e. during gradient accumulation steps.
Something like `on_substep` which is called after each gradient accumulation step.
## Motivation
Some training techniques require custom code to be run after each subst... | {
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https://api.github.com/repos/huggingface/transformers/issues/12919 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12919/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12919/comments | https://api.github.com/repos/huggingface/transformers/issues/12919/events | https://github.com/huggingface/transformers/pull/12919 | 954,078,917 | MDExOlB1bGxSZXF1ZXN0Njk4MDI3MzI5 | 12,919 | Fix typo in the example of MobileBertForPreTraining | {
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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/12918 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12918/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12918/comments | https://api.github.com/repos/huggingface/transformers/issues/12918/events | https://github.com/huggingface/transformers/pull/12918 | 954,051,197 | MDExOlB1bGxSZXF1ZXN0Njk4MDA0MTUy | 12,918 | Fix StoppingCriteria ABC signature | {
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"My pleasure! I have a handful of other PRs open with small fixes like this. I'm knocking them out as I encounter them."
] | 1,627 | 1,627 | 1,627 | CONTRIBUTOR | null | Change `score` -> `scores` because the argument is not positional-only, so you need consistently named parameters for the subclasses. The subclasses appear to favor `scores` over `score`. | {
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https://api.github.com/repos/huggingface/transformers/issues/12917 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12917/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12917/comments | https://api.github.com/repos/huggingface/transformers/issues/12917/events | https://github.com/huggingface/transformers/issues/12917 | 954,018,029 | MDU6SXNzdWU5NTQwMTgwMjk= | 12,917 | Tokenizer from tokenizers library cannot be used in Trainer | {
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"You can just do\r\n```\r\nfrom transformers import PreTrainedTokenizerFast\r\n\r\ntokenizer = PreTrainedTokenizerFast(tokenizer_object=your_tokenizer)\r\n```",
"> You can just do\n> \n> ```\n> \n> from transformers import PreTrainedTokenizerFast\n> \n> \n> \n> tokenizer = PreTrainedTokenizerFast(tokenizer_object... | 1,627 | 1,627 | 1,627 | CONTRIBUTOR | null | Hi,
I am trying to train my own model with `Trainer` with a pre-trained `SentencePieceBPETokenizer` from **tokenizers** library. However, it is missing several attributes as well as methods (e.g., `pad`), which makes it incompatible with `transformers.Trainer`. Is there an easy way to convert it to `PretrainedTokeni... | {
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https://api.github.com/repos/huggingface/transformers/issues/12916 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12916/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12916/comments | https://api.github.com/repos/huggingface/transformers/issues/12916/events | https://github.com/huggingface/transformers/issues/12916 | 954,015,908 | MDU6SXNzdWU5NTQwMTU5MDg= | 12,916 | fill-mask pipeline with tables (TapasForMaskedLM) fails DataFrame type assertion | {
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"Hi,\r\n\r\nTAPAS is not supported by the `FillMaskPipeline`, only by the `TableQuestionAnsweringPipeline`. \r\n\r\n`TapasForMaskedLM` was defined, but I did not include the weights of language modeling head when converting the checkpoints (I only loaded the weights of `TapasModel`, `TapasForQuestionAnswering` and ... | 1,627 | 1,630 | 1,630 | 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: macOS
- Python version: 3.9.2
- PyTorch version (GPU?): 1.8.9 (N/A)
- Tensorflow version ... | {
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https://api.github.com/repos/huggingface/transformers/issues/12915 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12915/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12915/comments | https://api.github.com/repos/huggingface/transformers/issues/12915/events | https://github.com/huggingface/transformers/issues/12915 | 953,961,467 | MDU6SXNzdWU5NTM5NjE0Njc= | 12,915 | saved checkpoint for best model and last model needs to be different | {
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"As you can see [here](https://github.com/huggingface/transformers/blob/d3c3e722d69627d6334d7ef8faaced7df3103174/src/transformers/trainer.py#L1982) we have special code to deal with that situation exactly, and I just checked locally and always have two checkpoints (the best model and the oldest) with `save_total_li... | 1,627 | 1,627 | 1,627 | 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: 4.8.2
- Platform: linux
- Python version: 2.7
- PyTorch version (GPU?): 1.9
- Tensorflow version (GPU?): - ... | {
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https://api.github.com/repos/huggingface/transformers/issues/12914 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12914/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12914/comments | https://api.github.com/repos/huggingface/transformers/issues/12914/events | https://github.com/huggingface/transformers/pull/12914 | 953,915,393 | MDExOlB1bGxSZXF1ZXN0Njk3ODg5MDk2 | 12,914 | [FLAX] Minor fixes in CLM example | {
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this PR fixes some minor issues that I've seen when training a new GPT-2 model from scratch:
* It uses the correct method for retrieving the vocab size from tokenizer instance
* Fixes train and validation assignment of dataset instance when using train or validation files | {
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https://api.github.com/repos/huggingface/transformers/issues/12913 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12913/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12913/comments | https://api.github.com/repos/huggingface/transformers/issues/12913/events | https://github.com/huggingface/transformers/pull/12913 | 953,902,401 | MDExOlB1bGxSZXF1ZXN0Njk3ODc3NzYy | 12,913 | Add truncation_side option to tokenizers | {
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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)... | 1,627 | 1,642 | 1,642 | CONTRIBUTOR | null | # What does this PR do?
As requested by #12909, it would be handy if one could also decide on whether to truncate sequences from the left instead of from the right.
As we already have a `padding_side` (which can be either left/right), it makes sense to also add a `truncation_side` (which by default is set to `"r... | {
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https://api.github.com/repos/huggingface/transformers/issues/12912 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12912/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12912/comments | https://api.github.com/repos/huggingface/transformers/issues/12912/events | https://github.com/huggingface/transformers/issues/12912 | 953,885,348 | MDU6SXNzdWU5NTM4ODUzNDg= | 12,912 | memory crash with large dataset | {
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"on the task manager I see that the dedicated GPU memory usage is constant at 24GB while the shared GPU memory usage is at zero. CPU is at 20% and RAM fills entirely up to 160GB. I cannot share the data (proprietary) but maybe there is something obvious that I am missing here in terms of `pipeline` and processing t... | 1,627 | 1,630 | 1,630 | NONE | null | Hello,
I am using the basic `sentiment-classification` pipeline based on https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english/tree/main.
I was able to predict the sentiment of several hundreds of sentences but ran into trouble when I tried to predict the sentiment of about 9M short sentences sto... | {
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https://api.github.com/repos/huggingface/transformers/issues/12911 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12911/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12911/comments | https://api.github.com/repos/huggingface/transformers/issues/12911/events | https://github.com/huggingface/transformers/pull/12911 | 953,854,013 | MDExOlB1bGxSZXF1ZXN0Njk3ODM1NzA2 | 12,911 | GPT-Neo ONNX export | {
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"@sgugger @LysandreJik What do you think would be the best way to approach this exporting features for downstream task? I think we have the two possible ways:\r\n\r\n- One config per task `XOnnxConfigForY` => Follow the general \"duplication\" pattern in transformers\r\n- One config with task as parameter encapsula... | 1,627 | 1,628 | 1,628 | MEMBER | null | # What does this PR do?
This PR enables the export of GPT-Neo to ONNX by extending the new module transformers.onnx.
It also provides a possible way of implementing the export for specific tasks: the task can be specified when instantiating an OnnxConfig. It is a nice approach because it makes factoring most of t... | {
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https://api.github.com/repos/huggingface/transformers/issues/12910 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12910/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12910/comments | https://api.github.com/repos/huggingface/transformers/issues/12910/events | https://github.com/huggingface/transformers/pull/12910 | 953,831,862 | MDExOlB1bGxSZXF1ZXN0Njk3ODE2Njkw | 12,910 | fix distiller.py | {
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<!--
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https://api.github.com/repos/huggingface/transformers/issues/12909 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12909/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12909/comments | https://api.github.com/repos/huggingface/transformers/issues/12909/events | https://github.com/huggingface/transformers/issues/12909 | 953,761,529 | MDU6SXNzdWU5NTM3NjE1Mjk= | 12,909 | Truncating the prefix of a sequence rather than the suffix | {
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"There's a `TruncationStrategy` called `\"only_first\"` that implements this. See [this](https://github.com/huggingface/transformers/blob/ba15fe7995a02357ecea6e7024918f6915564c36/src/transformers/tokenization_utils_base.py#L125) for all possible truncation strategies. ",
"@NielsRogge Perhaps I miss something, but... | 1,627 | 1,632 | null | CONTRIBUTOR | null | # 🚀 Feature request
Hi, tokenizers get `truncation` as an argument. When set to `True` the tokenizer will truncate the suffix of a sequence so it does not surpass the specified `max_length`. I'd like to have a functionality that truncates the prefix of the sequence, so the model will see the suffix of the sequence.... | {
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https://api.github.com/repos/huggingface/transformers/issues/12908 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12908/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12908/comments | https://api.github.com/repos/huggingface/transformers/issues/12908/events | https://github.com/huggingface/transformers/issues/12908 | 953,740,056 | MDU6SXNzdWU5NTM3NDAwNTY= | 12,908 | Training Transformer XL from scratch for CLM | {
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"Transformer XL is not compatible with the Trainer API, and won't work with any of the example scripts. You should use another model, or a modified version of the `run_clm_no_trainer` script.",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs... | 1,627 | 1,630 | 1,630 | NONE | null | I am training Transformer XL using the **run_clm.py** script. I was able to train GPT2, XLNet, CTRL etc without any issue. But with Transformer XL, I get the error
```
File "../lib/python3.8/site-packages/transformers/trainer.py", line 1272, in train
tr_loss += self.training_step(model, inputs)
File "../l... | {
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https://api.github.com/repos/huggingface/transformers/issues/12907 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12907/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12907/comments | https://api.github.com/repos/huggingface/transformers/issues/12907/events | https://github.com/huggingface/transformers/issues/12907 | 953,669,139 | MDU6SXNzdWU5NTM2NjkxMzk= | 12,907 | Can't set attention_probs_dropout_prob in LEDConfig | {
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"The reason you're getting this error is because `attention_probs_dropout_prob` is (as of now) only defined as a getter, not as a setter, as you can see [here](https://github.com/huggingface/transformers/blob/ba15fe7995a02357ecea6e7024918f6915564c36/src/transformers/models/led/configuration_led.py#L173-L175). The r... | 1,627 | 1,630 | 1,630 | NONE | null | ## Environment info
- `transformers` version: 4.9.0
- Python version: 3.8.10
- PyTorch version (GPU?): 1.9.0
### Who can help
@patrickvonplaten @beltagy
## Information
Loading LEDForConditionalGeneration throws an error on line 314 of configuration_utils.py:
```
"Can't set attention_probs_dropout_... | {
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https://api.github.com/repos/huggingface/transformers/issues/12906 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12906/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12906/comments | https://api.github.com/repos/huggingface/transformers/issues/12906/events | https://github.com/huggingface/transformers/issues/12906 | 953,646,795 | MDU6SXNzdWU5NTM2NDY3OTU= | 12,906 | AttributeError in BERT-Tokenizer | {
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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)... | 1,627 | 1,630 | 1,630 | NONE | null | Hi, I use `transformers` as part of the `xrenner`-Pipeline. I run into the following problem with the BERT-tokenization:
```
Traceback (most recent call last):
File "/Users/lucienbaumgartner/phd/projects/done/tc_methods_paper/src/animacy-classification/test.py", line 63, in <module>
sgml_result = xrenner.an... | {
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https://api.github.com/repos/huggingface/transformers/issues/12905 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12905/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12905/comments | https://api.github.com/repos/huggingface/transformers/issues/12905/events | https://github.com/huggingface/transformers/issues/12905 | 953,623,407 | MDU6SXNzdWU5NTM2MjM0MDc= | 12,905 | The Unsupervised denoising training example in T5's doc | {
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"I just ran it in a Colab notebook and got no issues.\r\n\r\nHere's the notebook: https://colab.research.google.com/drive/1Fq420RZwq2coLjb0TJmAx5Q20uz3JJHj?usp=sharing",
"> I just ran it in a Colab notebook and got no issues.\r\n> \r\n> Here's the notebook: https://colab.research.google.com/drive/1Fq420RZwq2coLjb... | 1,627 | 1,627 | 1,627 | NONE | null | When I am running that example, it will print a lot of "seq_length: 7" like this:
seq_length: 7
position_bias: torch.Size([1, 8, 7, 7])
mask: torch.Size([1, 1, 1, 7])
seq_length: 7
seq_length: 7
seq_length: 7
seq_length: 7
seq_length: 7
seq_length: 7
position_bias: torch.Size([1, 8, 7, 7])
mask: torch.Size([... | {
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https://api.github.com/repos/huggingface/transformers/issues/12904 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12904/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12904/comments | https://api.github.com/repos/huggingface/transformers/issues/12904/events | https://github.com/huggingface/transformers/issues/12904 | 953,600,304 | MDU6SXNzdWU5NTM2MDAzMDQ= | 12,904 | transformers.__spec__ returning None. Causing downstream import errors | {
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"`__spec__` is used by the Python import system internally, I am not reading anywhere that it should be defined manually by the package creators. If you have more resources about this I'm happy to look into what we could add, but a quick Google search yields nothing.",
"> `__spec__` is used by the Python import s... | 1,627 | 1,642 | 1,627 | 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: Tried on 4.6.1(current default kaggle version)/4.8.1/4.8.2 and 4.9.1
- Platform: Colab/Kaggle/ My Local Runtim... | {
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https://api.github.com/repos/huggingface/transformers/issues/12903 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12903/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12903/comments | https://api.github.com/repos/huggingface/transformers/issues/12903/events | https://github.com/huggingface/transformers/issues/12903 | 953,595,056 | MDU6SXNzdWU5NTM1OTUwNTY= | 12,903 | ValueError: Outputs values doesn't match between reference model and ONNX exported model | {
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"python -m transformers.onnx --model=facebook/bart-large /home/sysadmin/downlaod/onnx_models/bart-large\r\n\r\nHello, the doc says bart has been supported by transformers.onnx. But this error occers while I run it.\r\n\r\nPytorch version: 1.9.0\r\ntransformers version: 4.9.1\r\nplatform: centos 7\r\npython version:... | 1,627 | 1,659 | 1,630 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
python -m transformers.onnx --model=facebook/bart-large /home/sysadmin/downlaod/onnx_models/bart-large
- `transformers` version: 4.9.1
- Platform: CENTOS 8
- Python version: python 3.7
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https://api.github.com/repos/huggingface/transformers/issues/12902 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12902/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12902/comments | https://api.github.com/repos/huggingface/transformers/issues/12902/events | https://github.com/huggingface/transformers/issues/12902 | 953,584,317 | MDU6SXNzdWU5NTM1ODQzMTc= | 12,902 | pipeline does not load a (local) model | {
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"As the error specifies, there's a problem with the path you are providing. Make sure the path can be parsed correctly.",
"thanks @NielsRogge, actually I was able to make it work indirectly: first load the model on another computer, then use `save_pretrained`, transfer the saved folder to the offline computer and... | 1,627 | 1,630 | 1,630 | NONE | null | Hello the great `huggingface` team!
I am using a computer behind a firewall so I cannot download files from python. I am simply trying to load a sentiment-analysis pipeline so I downloaded all the files available here https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english/tree/main in a local folder ... | {
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https://api.github.com/repos/huggingface/transformers/issues/12901 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12901/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12901/comments | https://api.github.com/repos/huggingface/transformers/issues/12901/events | https://github.com/huggingface/transformers/pull/12901 | 953,454,027 | MDExOlB1bGxSZXF1ZXN0Njk3NDkzMjI2 | 12,901 | Update generation_logits_process.py | {
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https://api.github.com/repos/huggingface/transformers/issues/12900 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12900/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12900/comments | https://api.github.com/repos/huggingface/transformers/issues/12900/events | https://github.com/huggingface/transformers/pull/12900 | 953,424,664 | MDExOlB1bGxSZXF1ZXN0Njk3NDY4ODMz | 12,900 | Update generation_logits_process.py | {
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https://api.github.com/repos/huggingface/transformers/issues/12899 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12899/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12899/comments | https://api.github.com/repos/huggingface/transformers/issues/12899/events | https://github.com/huggingface/transformers/pull/12899 | 953,417,012 | MDExOlB1bGxSZXF1ZXN0Njk3NDYyNTUw | 12,899 | `Seq2SeqTrainer` set max_length and num_beams only when non None | {
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This PR slightly modifies the logic of setting `self._max_length` and `self._num_beams` in `Seq2SeqTrainer`'s `evaluate()` and `predict()` methods, i.e., the two variables will be set only when they are provided non `None` values.
This is to address a potentially inconsistent evaluation co... | {
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https://api.github.com/repos/huggingface/transformers/issues/12898 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12898/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12898/comments | https://api.github.com/repos/huggingface/transformers/issues/12898/events | https://github.com/huggingface/transformers/issues/12898 | 953,408,473 | MDU6SXNzdWU5NTM0MDg0NzM= | 12,898 | Tensorflow Mixed Precision Training | {
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"One-hot encoding the labels for a language model will get you OOM super fast since the vocab size is often large, so that's not an option. I think casting the prediction before the loss back to float32 is probably the safest option?",
"Ah, good point, I assumed since logits were of the same dimensionality, it wo... | 1,627 | 1,630 | 1,630 | NONE | null | ## Environment info
- `transformers` version: 4.5.1
- Platform: Linux-5.4.0-74-generic-x86_64-with-glibc2.27
- Python version: 3.8.8
- PyTorch version (GPU?): 1.8.1+cu111 (True)
- Tensorflow version (GPU?): 2.6.0-dev20210604 (True)
- Using GPU in script?: yes
- Using distributed or parallel set-up in script?: ... | {
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https://api.github.com/repos/huggingface/transformers/issues/12897 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12897/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12897/comments | https://api.github.com/repos/huggingface/transformers/issues/12897/events | https://github.com/huggingface/transformers/pull/12897 | 953,393,012 | MDExOlB1bGxSZXF1ZXN0Njk3NDQyNDU2 | 12,897 | Correct validation_split_percentage argument from int (ex:5) to float (0.05) | {
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"Please make sure to run `make style` on your branch to fix the formatting issues.",
"Thanks for fixing!",
"Thanks for kind help with the formatting "
] | 1,627 | 1,627 | 1,627 | CONTRIBUTOR | null |
# What does this PR do?
This PR is for fixing a bug in the run_clm.py and run_mlm.py examples in the tensorflow section. I have merely divided the value by 100 on the train_test_split test_size argument. This will make it work as intended now.
## Before submitting
- [ ] This PR fixes a typo or improves the... | {
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https://api.github.com/repos/huggingface/transformers/issues/12895 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12895/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12895/comments | https://api.github.com/repos/huggingface/transformers/issues/12895/events | https://github.com/huggingface/transformers/pull/12895 | 953,291,207 | MDExOlB1bGxSZXF1ZXN0Njk3MzU1MTI1 | 12,895 | Fix push_to_hub for TPUs | {
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This PR fixes the `push_to_hub` method for TPUs, which hangs forever right now because there is a reandezvous point in code that is only reached by the main process. | {
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"Pinging @n1t0 and @SaulLu for advice",
"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... | 1,627 | 1,630 | 1,630 | NONE | null | The way `add_token` is implemented results is problematic tokenization when added tokens are substring of each other. Example:
```
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("google/mt5-large")
tokenizer.add_tokens(['my_token_1', 'my_token_12', 'my_token_123'])
tokenizer.t... | {
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"Thanks, @willfrey! I'm reading the PEP 561 as I was unaware of this file, but I'm not sure I'm getting everything. Is this file necessary for downstream type checkers (such as `mypy`) to understand the types from `transformers`?\r\n\r\nIf that is so, is there no need for any additions, such as a mention in our set... | 1,627 | 1,629 | 1,628 | CONTRIBUTOR | null | # What does this PR do?
This creates a [py.typed as per PEP 561](https://www.python.org/dev/peps/pep-0561/#packaging-type-information) that should be distributed to mark that the package includes (inline) type annotations.
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"Hi,\r\n\r\nGoogle hasn't released any pre-training code yet. As stated on their [README](https://github.com/google-research/language/tree/master/language/canine#pre-training-code-coming-later):\r\n\r\n> Pre-training Code (Coming later)\r\nWe've prioritized releasing the pre-trained checkpoints, modeling code, and ... | 1,627 | 1,630 | 1,630 | NONE | null | # 🚀 Feature request
Thanks for the integration of the Canine model. I am interested in pre-training the model from scratch and I was wondering if you have a timeline for the release of a pre-training script using autoregressive character loss.
Thank you in advance.
@NielsRogge | {
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https://api.github.com/repos/huggingface/transformers/issues/12890 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12890/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12890/comments | https://api.github.com/repos/huggingface/transformers/issues/12890/events | https://github.com/huggingface/transformers/issues/12890 | 952,972,307 | MDU6SXNzdWU5NTI5NzIzMDc= | 12,890 | Multi-GPU fails | {
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"I am unable to reproduce the problem (also you seem to have made changes to the `run_clm` script since it does not accept those arguments: `--method range --source fi.json --from_scratch`) but in general, PyTorch discourages the use of DataParallel for multiGPU, so you should try to see if using DistributedDataPar... | 1,627 | 1,630 | 1,630 | NONE | null | ## Environment info
- transformers version: 4.6.1
- Platform: Linux-4.19.0-17-cloud-amd64-x86_64-with-glibc2.10
- Python version: 3.8.10
- PyTorch version (GPU?): 1.8.1+cu111
- Tensorflow version (GPU?): not installed
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: Data Parallel
... | {
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https://api.github.com/repos/huggingface/transformers/issues/12889 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12889/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12889/comments | https://api.github.com/repos/huggingface/transformers/issues/12889/events | https://github.com/huggingface/transformers/pull/12889 | 952,931,955 | MDExOlB1bGxSZXF1ZXN0Njk3MDUyNzg2 | 12,889 | Fix documentation of BigBird tokenizer | {
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The tokens mentioned in the docstrings don't match the signature, this PR fixes that.
Fixes #12873 | {
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https://api.github.com/repos/huggingface/transformers/issues/12888 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12888/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12888/comments | https://api.github.com/repos/huggingface/transformers/issues/12888/events | https://github.com/huggingface/transformers/pull/12888 | 952,929,406 | MDExOlB1bGxSZXF1ZXN0Njk3MDUwNjM4 | 12,888 | Add accelerate to examples requirements | {
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As mentioned in #12849, the `requirements.txt` for most PyTorch examples does not contain `accelerate`, so the `run_xxx_no_trainer.py` example cannot be executed. This PR fixes that.
Fixes #12489 | {
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https://api.github.com/repos/huggingface/transformers/issues/12887 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12887/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12887/comments | https://api.github.com/repos/huggingface/transformers/issues/12887/events | https://github.com/huggingface/transformers/issues/12887 | 952,753,136 | MDU6SXNzdWU5NTI3NTMxMzY= | 12,887 | Add config option to skip 1-D position embeddings in LayoutLM | {
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"I'm not sure whether we should add such an option, because models like BERT, RoBERTa, ... basically all Transformer models within this repository don't have this option. Either we add that option to all, either we don't in my opinion. \r\n\r\nAbsolute position embeddings are almost always beneficial, so not sure i... | 1,627 | 1,629 | 1,629 | CONTRIBUTOR | null | # 🚀 Feature request
Add an option in LayoutLM config to not use 1-D position embeddings. The config currently allows us to choose between "absolute", "relative_key", and "relative_key_query". Can we add another option like "none" to not use 1-D positional embeddings?
## Motivation
The input to LayoutLM consists o... | {
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https://api.github.com/repos/huggingface/transformers/issues/12886 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12886/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12886/comments | https://api.github.com/repos/huggingface/transformers/issues/12886/events | https://github.com/huggingface/transformers/pull/12886 | 952,658,230 | MDExOlB1bGxSZXF1ZXN0Njk2ODE5NTA4 | 12,886 | Object detection pipeline | {
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"@LysandreJik ofc as a personal matter I would rather this would be merged after the large refactor, but tbh this should be handled like any other PR, the first to be ready should be approved.\r\n\r\nMoving this code to the new PR should be just as easy as the other ones (the code is currently rather well separated... | 1,627 | 1,647 | 1,631 | CONTRIBUTOR | null | # What does this PR do?
* Object detection pipeline
* Give an image or list of images, outputs obj det annotations in form:
```python
[
[
{'score': 0.9..., 'label': 'remote', 'box': [{'x': 66, 'y': 118}, ...},
],
...
]
```
* See [colab](https://colab.research.google.com/github/NielsRogge/... | {
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https://api.github.com/repos/huggingface/transformers/issues/12885 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12885/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12885/comments | https://api.github.com/repos/huggingface/transformers/issues/12885/events | https://github.com/huggingface/transformers/issues/12885 | 952,647,429 | MDU6SXNzdWU5NTI2NDc0Mjk= | 12,885 | an unexpected keyword argument 'output_signature' | {
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"update tensorflow to 2.5 solve this.",
"Use tf >= v2.4.0 to solve this issue. This was in the release notes."
] | 1,627 | 1,649 | 1,627 | 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:4.9.0
- Platform:linux
- Python version:3.6
- PyTorch version (GPU?):1.7
- Tensorflow version (GPU?):2.3,gpu... | {
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https://api.github.com/repos/huggingface/transformers/issues/12884 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12884/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12884/comments | https://api.github.com/repos/huggingface/transformers/issues/12884/events | https://github.com/huggingface/transformers/issues/12884 | 952,578,997 | MDU6SXNzdWU5NTI1Nzg5OTc= | 12,884 | Super slow ByT5 Tokenizer | {
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"Pinging @patrickvonplaten ",
"See his (@patrickvonplaten ) answer here: https://github.com/huggingface/transformers/pull/11971#issuecomment-889797262",
"pinging @Narsil",
"Hi, don't think rust is necessary here.\r\n\r\nUsing raw bytes should be just as fast in python (if not faster because no overhead).\r\n... | 1,627 | 1,629 | 1,629 | CONTRIBUTOR | null | Hi,
The ByT5 Tokenizer seems to be super slow compared to others (T5).
See colab link below for example code.
T5-small tokenizer:
By-T5-small tokenizer:
![grafik](https://user-images.githubuser... | {
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https://api.github.com/repos/huggingface/transformers/issues/12883 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12883/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12883/comments | https://api.github.com/repos/huggingface/transformers/issues/12883/events | https://github.com/huggingface/transformers/issues/12883 | 952,423,712 | MDU6SXNzdWU5NTI0MjM3MTI= | 12,883 | Distributed TPU training with run_mlm duplicate data | {
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"Dataset streaming has not been tested on any of the examples, so I'm not sure it works, especially for distributed training on TPUs.",
"I am working on this feature for several days. Especially, I am trying to implement Iterable Dataset which reads preprocessed data from Cloud. Is the problem about streaming or ... | 1,627 | 1,630 | 1,630 | 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: 4.10.0 (currently master)
- Platform: TPU VM3.8 -- Ubuntu 20.04.2 LTS
- Python version: 3.8.10
- PyTorch ve... | {
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https://api.github.com/repos/huggingface/transformers/issues/12882 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12882/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12882/comments | https://api.github.com/repos/huggingface/transformers/issues/12882/events | https://github.com/huggingface/transformers/issues/12882 | 952,404,531 | MDU6SXNzdWU5NTI0MDQ1MzE= | 12,882 | loss sudden increase | {
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"Hi,\r\n\r\nWe like to keep Github issues for bugs/feature requests. For training related questions, please see the [forum](https://discuss.huggingface.co/). Also, make sure to make it possible for people to reproduce your issue, by providing code or a colab notebook.\r\n\r\nThanks!\r\n\r\n"
] | 1,627 | 1,627 | 1,627 | NONE | null | 
I tried this a few times | {
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https://api.github.com/repos/huggingface/transformers/issues/12881 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12881/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12881/comments | https://api.github.com/repos/huggingface/transformers/issues/12881/events | https://github.com/huggingface/transformers/issues/12881 | 952,361,907 | MDU6SXNzdWU5NTIzNjE5MDc= | 12,881 | Tensorflow GPT-2 model incapable of freezing layers | {
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"Hi, I think this is going to be quite difficult in Keras given the way our models are implemented, as I believe Keras only supports freezing weights on Layer objects, and we haven't implemented the individual pieces of GPT2 as Keras Layers.\r\n\r\nIf you'd like to only train specific pieces of your model, I'd reco... | 1,627 | 1,659 | 1,630 | CONTRIBUTOR | null | I am trying to finetune gpt-2 by freezing some layers according to [this article](https://arxiv.org/pdf/2103.05247.pdf). Freezing the specified layers doesn't change the number of trainable parameters, even though accessing the .trainable attribute of the weights of the model shows that they are False.
```python
from... | {
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https://api.github.com/repos/huggingface/transformers/issues/12880 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12880/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12880/comments | https://api.github.com/repos/huggingface/transformers/issues/12880/events | https://github.com/huggingface/transformers/issues/12880 | 952,321,567 | MDU6SXNzdWU5NTIzMjE1Njc= | 12,880 | RoBERTa: Truncation error: Sequence to truncate too short to respect the provided max_length | {
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"After further analysis, I could see that RoBERTa tokenizer is not able to handle a question in SQuAD 2.0 dataset at index \"107709\" due to lot of blank spaces at the start of the question and it's length is 25651 character. \r\nWhile other tokenizers are able to handle this.\r\n\r\n\r\n```python\r\nprint(\"questi... | 1,627 | 1,695 | 1,627 | NONE | null | ## Environment info
- `transformers` version: 4.9.0
- Platform: Linux-5.4.104+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.11
- PyTorch version (GPU?): 1.9.0+cu102 (False)
- Tensorflow version (GPU?): 2.5.0 (False)
- Flax version (CPU?/GPU?/TPU?): TPU
- Jax version: not installed
- JaxLib version: n... | {
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https://api.github.com/repos/huggingface/transformers/issues/12879 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12879/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12879/comments | https://api.github.com/repos/huggingface/transformers/issues/12879/events | https://github.com/huggingface/transformers/issues/12879 | 952,318,553 | MDU6SXNzdWU5NTIzMTg1NTM= | 12,879 | Feature Request: Add support for --do_train/eval/predict arguments in the TF examples script for token classification | {
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"Hi, you can use the `--train_file` and `--validation_file` arguments to pass custom data to the model! Are you specifically interested in doing predictions too?",
"Yes! It is the predictions I think would be awesome to have the option to do! 🥇 ",
"This issue has been automatically marked as stale because it h... | 1,627 | 1,633 | 1,633 | NONE | null | It would be truly awesome if the TensorFlow example of token classification could mimic the capabilities of the PyTorch implementation, by providing additional argument-functionality, including `--do_train`, `--do_eval` and `--do_predict`.
Furthermore, giving the user the opportunity to provide a custom dataset thr... | {
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https://api.github.com/repos/huggingface/transformers/issues/12878 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12878/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12878/comments | https://api.github.com/repos/huggingface/transformers/issues/12878/events | https://github.com/huggingface/transformers/issues/12878 | 952,276,917 | MDU6SXNzdWU5NTIyNzY5MTc= | 12,878 | Trainer accumulates logits | {
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"@sgugger ",
"No, metrics usually can't be computed on a batch-per-batch basis as it usually gives the wrong result when the metric is not a mean (like precision, recall or F1 score).\r\n\r\nFor metrics in language modeling, you should use your own manual evaluation loop after training.",
"Fair enough, but if I... | 1,627 | 1,700 | 1,627 | CONTRIBUTOR | null | Hi,
I am using `transformers.Trainer` to pre-train a model with MLM. From line 2213 in `trainer.py` I can see the logits obtained on the evaluation step are accumulated:
`preds_host = logits if preds_host is None else nested_concat(preds_host, logits, padding_index=-100)`
This makes it impossible to use a reaso... | {
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https://api.github.com/repos/huggingface/transformers/issues/12877 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12877/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12877/comments | https://api.github.com/repos/huggingface/transformers/issues/12877/events | https://github.com/huggingface/transformers/issues/12877 | 952,213,866 | MDU6SXNzdWU5NTIyMTM4NjY= | 12,877 | run_mlm.py errors when running validation only | {
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"I'm not sure what you mean, could you check you have the latest version of the script? There is a test of whether the `train_file` is None or not at the line you mention, and then the `validation_file` is used instead if the `train_file` has not been set.",
"@sgugger You're right, it was fixed in this commit htt... | 1,627 | 1,627 | 1,627 | NONE | null | If you run `mlm_train.py' for validation only (i.e. --do_eval but don't pass -do_train) the script only runs if you still pass --train_file
This is due to the inference of the train file being used to determine the file type (i.e. text)
https://github.com/huggingface/transformers/blob/9ff672fc4d84db3b077e03ea22e2... | {
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https://api.github.com/repos/huggingface/transformers/issues/12876 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12876/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12876/comments | https://api.github.com/repos/huggingface/transformers/issues/12876/events | https://github.com/huggingface/transformers/issues/12876 | 952,146,479 | MDU6SXNzdWU5NTIxNDY0Nzk= | 12,876 | New transformers.onnx CLI does not support ONNX quantization | {
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"Hi @minimaxir, \r\n\r\nThanks for reporting this.\r\n\r\nWith the new \"configuration based\" capabilities we are taking a very different approach from the initial `convert_graph_to_onnx.py` which was relying on heuristics to match dynamic axes and was exporting them in the wrong order quite often.\r\n\r\nThe new ... | 1,627 | 1,633 | 1,627 | NONE | null | # 🚀 Feature request
New transformers.onnx CLI introduced in 4.9.0 does not support ONNX quantization, which is a notable missing feature from the `convert_graph_to_onnx.py` script.
Semi-related: the [source quantize() function](https://github.com/microsoft/onnxruntime/blob/79097ef5535cc5ac18fc8e9010c99de08df2134... | {
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https://api.github.com/repos/huggingface/transformers/issues/12875 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12875/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12875/comments | https://api.github.com/repos/huggingface/transformers/issues/12875/events | https://github.com/huggingface/transformers/issues/12875 | 952,145,752 | MDU6SXNzdWU5NTIxNDU3NTI= | 12,875 | Model card updated/deleted | {
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"Hey @tuner007,\r\n\r\nThanks a lot for your issue! I'm very sorry that this has happened - this was a bug from my side :-/ I corrected it and your model should work as before now :-)",
"> Hey @tuner007,\r\n> \r\n> Thanks a lot for your issue! I'm very sorry that this has happened - this was a bug from my side :-... | 1,627 | 1,627 | 1,627 | CONTRIBUTOR | null | Hi,
I can check that the Model "tuner007/t5_abs_qa" has been removed from model hub...Is there anything i need to update ?
@patrickvonplaten [Refer](https://huggingface.co/tuner007/t5_abs_qa/commit/faf30925ced0f25d0d5d321fb0ada04caaf5568d)
/thanks | {
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https://api.github.com/repos/huggingface/transformers/issues/12874 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12874/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12874/comments | https://api.github.com/repos/huggingface/transformers/issues/12874/events | https://github.com/huggingface/transformers/issues/12874 | 952,137,626 | MDU6SXNzdWU5NTIxMzc2MjY= | 12,874 | Finetuning GPT-2 on small datasets | {
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"I've finally found [this article](https://arxiv.org/pdf/2103.05247.pdf), and it seems promising. Going to try it out i'll say how it went.",
"For training-related questions, please refer to the [forum](https://discuss.huggingface.co/). We like to keep Github issues for bugs/feature requests.\r\n\r\nFor example, ... | 1,627 | 1,630 | 1,630 | CONTRIBUTOR | null | I have a relatively small dataset that i've scraped on my discord server. I wanted to make a gpt-2 chatbot with it, but the data is relatively small (3782031 characters counting the eos token). Training for a small number of epochs did nothing for any checkpoint related to gpt-2 (I tried distilbert, gpt-2, dialoGPT-sma... | {
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https://api.github.com/repos/huggingface/transformers/issues/12873 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12873/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12873/comments | https://api.github.com/repos/huggingface/transformers/issues/12873/events | https://github.com/huggingface/transformers/issues/12873 | 952,130,446 | MDU6SXNzdWU5NTIxMzA0NDY= | 12,873 | Possibly wrong API documentation for BigBirdTokenizerFast | {
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"Thanks for flagging, should be fixed by the PR mentioned above!"
] | 1,627 | 1,627 | 1,627 | NONE | null | - `transformers` version: v.4.9.0
### Who can help
Documentation: @sgugger
## Information
At this URL:
https://huggingface.co/transformers/model_doc/bigbird.html#transformers.BigBirdTokenizerFast
The doc says,
`bos_token (str, optional, defaults to "[CLS]")`
and
`eos_token (str, optional, default... | {
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https://api.github.com/repos/huggingface/transformers/issues/12872 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12872/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12872/comments | https://api.github.com/repos/huggingface/transformers/issues/12872/events | https://github.com/huggingface/transformers/issues/12872 | 952,103,278 | MDU6SXNzdWU5NTIxMDMyNzg= | 12,872 | Allow multilabel classification mode for widgets in the models repo | {
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"Hi @avidale, I'm closing this issue as I think it is an accidental duplicate of #12871.\r\nAlso, I've transferred #12871 to [huggingface_hub/#222](huggingface/huggingface.js#300) since thats where the widgets src is"
] | 1,627 | 1,700 | 1,627 | NONE | null | # 🚀 Feature request
1. Enable multilabel classification mode and regression mode for the widgets in the model repo.
2. Create the corresponding tags that can be read from the model card.
## Motivation
Models for sequence classification by default support three modes: binary/multiclass classification, multila... | {
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https://api.github.com/repos/huggingface/transformers/issues/12870 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12870/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12870/comments | https://api.github.com/repos/huggingface/transformers/issues/12870/events | https://github.com/huggingface/transformers/issues/12870 | 952,102,868 | MDU6SXNzdWU5NTIxMDI4Njg= | 12,870 | Bart Generation | {
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"Bart was trained to have EOS as it's start_token_id and we've noticed that forcing the first token to be BOS gives better results, see: https://github.com/huggingface/transformers/issues/3668",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still need... | 1,627 | 1,631 | 1,631 | 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: 4.9.0
- Platform:Linux
- Python version:3.7
- PyTorch version (GPU?):1.9.0
- Using GPU in script?:true
- U... | {
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https://api.github.com/repos/huggingface/transformers/issues/12869 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12869/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12869/comments | https://api.github.com/repos/huggingface/transformers/issues/12869/events | https://github.com/huggingface/transformers/issues/12869 | 952,019,037 | MDU6SXNzdWU5NTIwMTkwMzc= | 12,869 | I donnot want print trainer's logging info | {
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"You can use the argument `log_level` to adjust the level of the logger. If you set it to \"warning\", it won't print this.",
"thanks, it works"
] | 1,627 | 1,627 | 1,627 | NONE | null | torch 1.18.0，tf 1.14.0
every thing works well yesterday
i didn't do any thing, but today when i use predict of trainer, it print this infomation before the output
this situation didn't occur before
```
***** Running Prediction *****
Num examples = 1
Batch size = 256
```
now i want this info don'... | {
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https://api.github.com/repos/huggingface/transformers/issues/12868 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12868/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12868/comments | https://api.github.com/repos/huggingface/transformers/issues/12868/events | https://github.com/huggingface/transformers/issues/12868 | 952,015,912 | MDU6SXNzdWU5NTIwMTU5MTI= | 12,868 | MT5-base tokenizer can't decode to target language after decoding | {
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"follo... | [] | 1,627 | 1,628 | 1,628 | NONE | null | ## Environment info
- `transformers` version: 4.9.0
- Platform: Google Colab
- Python version: 3.8+
- PyTorch version (GPU?): 1.9.0+cu102
- Using GPU in script?: yes
- Using distributed or parallel set-up in script?: no
### Who can help
Models:
- blenderbot, bart, marian, pegasus, encoderdecoder, t... | {
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https://api.github.com/repos/huggingface/transformers/issues/12867 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12867/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12867/comments | https://api.github.com/repos/huggingface/transformers/issues/12867/events | https://github.com/huggingface/transformers/issues/12867 | 951,802,420 | MDU6SXNzdWU5NTE4MDI0MjA= | 12,867 | Possible bug in spm-based tokenizers | {
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"In fact, this seems to be a problem with other spm based tokenizers too. Other MBART checkpoints as well as MT5 and XLMR models have the same behavior but not multilingual BERT checkpoints. Not sure if this issue has been reported/ discussed before. Any hints are appreciated.",
"@patil-suraj - could you take a l... | 1,627 | 1,642 | 1,642 | CONTRIBUTOR | 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: latest (4.10.0.dev0)
- Python version: 3.8
- PyTorch version (GPU?): 1.9.0
- Using GPU in script?: no
- Usi... | {
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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)... | 1,627 | 1,630 | 1,630 | NONE | null | # 🚀 Feature request
I'd like to understand if it's possible to fine-tune MPnet model on domain specific corpus. I tried to run following script for MPNet and it seemed to be working (or at least on throwing any errors).
`python run_mlm.py --model_name_or_path microsoft/mpnet-base --dataset_name wikitext --do_train... | {
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https://api.github.com/repos/huggingface/transformers/issues/12865 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12865/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12865/comments | https://api.github.com/repos/huggingface/transformers/issues/12865/events | https://github.com/huggingface/transformers/pull/12865 | 951,726,940 | MDExOlB1bGxSZXF1ZXN0Njk2MDY1NDkx | 12,865 | Add TF multiple choice example | {
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https://api.github.com/repos/huggingface/transformers/issues/12864 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12864/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12864/comments | https://api.github.com/repos/huggingface/transformers/issues/12864/events | https://github.com/huggingface/transformers/issues/12864 | 951,680,451 | MDU6SXNzdWU5NTE2ODA0NTE= | 12,864 | [Speech2Text] Slow tests are failing on master | {
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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)... | 1,627 | 1,630 | 1,630 | MEMBER | null | Currently the following tests are failing on master:
```
FAILED tests/test_modeling_speech_to_text.py::Speech2TextModelIntegrationTests::test_generation_librispeech
FAILED tests/test_modeling_speech_to_text.py::Speech2TextModelIntegrationTests::test_generation_librispeech_batched
``` | {
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https://api.github.com/repos/huggingface/transformers/issues/12863 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12863/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12863/comments | https://api.github.com/repos/huggingface/transformers/issues/12863/events | https://github.com/huggingface/transformers/issues/12863 | 951,674,424 | MDU6SXNzdWU5NTE2NzQ0MjQ= | 12,863 | [Wav2Vec2] Slow pretraining tests are failing on CPU | {
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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)... | 1,627 | 1,630 | 1,630 | MEMBER | null | The following tests are failing on CPU currently:
```
tests/test_modeling_wav2vec2.py::Wav2Vec2ModelIntegrationTest::test_inference_integration
tests/test_modeling_wav2vec2.py::Wav2Vec2ModelIntegrationTest::test_loss_pretraining
```
-> check if they also fail on GPU. If not add a skip CPU decorator | {
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https://api.github.com/repos/huggingface/transformers/issues/12862 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12862/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12862/comments | https://api.github.com/repos/huggingface/transformers/issues/12862/events | https://github.com/huggingface/transformers/issues/12862 | 951,657,422 | MDU6SXNzdWU5NTE2NTc0MjI= | 12,862 | BatchFeature should cast to `np.float32` by default | {
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"follo... | [] | 1,627 | 1,629 | null | MEMBER | null | Currently the default dtype for Speech Feature Extractors is `numpy.float64` which leads to two problems:
1) It makes the data processing extremely expensive for the RAM. Many sound formats are stored in int16 (such as `.wav`) and are then transformed to float64 which unnecessarly increases RAM by a factor of 4. We ... | {
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https://api.github.com/repos/huggingface/transformers/issues/12861 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12861/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12861/comments | https://api.github.com/repos/huggingface/transformers/issues/12861/events | https://github.com/huggingface/transformers/issues/12861 | 951,656,739 | MDU6SXNzdWU5NTE2NTY3Mzk= | 12,861 | Asking for consent to publish `_LazyModule` as a standalone PyPI package on GitHub | {
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"Tagging @LysandreJik and @sgugger ",
"Thanks for asking! You can definitely package this class in a module as long as it's on the same license as in this repo (Apache 2.0) and you are willing to maintain it.",
"Here you go. A release will follow the next days:\r\nhttps://github.com/telekom/lazy-imports",
"Ma... | 1,627 | 1,627 | 1,627 | CONTRIBUTOR | null | Hi,
I very much like your `_LazyModule` implementation.
https://github.com/huggingface/transformers/blob/e218249b02465ec8b6029f201f2503b9e3b61feb/src/transformers/file_utils.py#L1945
I would like to reuse it on different other projects. That is why I ask for your consent to publish it as a
standalone PyPI pa... | {
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https://api.github.com/repos/huggingface/transformers/issues/12860 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12860/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12860/comments | https://api.github.com/repos/huggingface/transformers/issues/12860/events | https://github.com/huggingface/transformers/pull/12860 | 951,644,421 | MDExOlB1bGxSZXF1ZXN0Njk1OTk2MzQ0 | 12,860 | [tests] fix logging_steps requirements | {
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"Hello! Could you show me the command you used to install `transformers`? Thank you!",
"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 [contrib... | 1,627 | 1,659 | 1,630 | NONE | null | ## Environment info
- `transformers` version: 4.9.0
- Platform: Linux-4.15.0-151-generic-x86_64-with-glibc2.27
- Python version: 3.9.2
- PyTorch version (GPU?): 1.7.1+cu101 (False)
- Tensorflow version (GPU?): 2.5.0 (False)
- Flax version (CPU?/GPU?/TPU?): 0.3.4 (cpu)
- Jax version: 0.2.17
- JaxLib version: 0... | {
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"cc @LysandreJik @sgugger \r\n\r\nAlso see: https://github.com/gitpython-developers/GitPython/issues/1296"
] | 1,627 | 1,627 | 1,627 | MEMBER | null | # What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/12857 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12857/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12857/comments | https://api.github.com/repos/huggingface/transformers/issues/12857/events | https://github.com/huggingface/transformers/issues/12857 | 951,446,090 | MDU6SXNzdWU5NTE0NDYwOTA= | 12,857 | wav2vec pretrain and fine-tune with huge data | {
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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://discuss.huggingface.co) instead?\r\n\r\nThanks!",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this stil... | 1,627 | 1,629 | 1,629 | NONE | null | Hi,
Thanks for the great efforts for wav2vec!
is there good example to fine-tune and pretrain wav2vec with huge data?
it seems the official examples works fine with one GPU but not so good for multigpus.
Thanks. | {
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https://api.github.com/repos/huggingface/transformers/issues/12856 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12856/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12856/comments | https://api.github.com/repos/huggingface/transformers/issues/12856/events | https://github.com/huggingface/transformers/issues/12856 | 951,425,520 | MDU6SXNzdWU5NTE0MjU1MjA= | 12,856 | TypeError: '>' not supported between instances of 'NoneType' and 'int' | {
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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)... | 1,627 | 1,700 | 1,630 | 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:
- PyTorch version (GPU?):
- Tensorflow version (GPU?):
- Using GPU in script... | {
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https://api.github.com/repos/huggingface/transformers/issues/12855 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12855/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12855/comments | https://api.github.com/repos/huggingface/transformers/issues/12855/events | https://github.com/huggingface/transformers/pull/12855 | 951,345,649 | MDExOlB1bGxSZXF1ZXN0Njk1NzQ4NDE1 | 12,855 | fix typo in gradient_checkpointing arg | {
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"@JetRunner Thx for comment.\r\nI just update my branch and Now CI seems to be working fine!\r\n",
"Thanks!"
] | 1,627 | 1,627 | 1,627 | CONTRIBUTOR | null | help for `ModelArguments.gradient_checkpointing` should be
"If True, use gradient checkpointing to save memory
at the expense of slower backward pass."
not "Whether to freeze the feature extractor layers of the model."
(which is duplicated from `freeze_feature_extractor` arg)
# What does this PR do?
<!--
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https://api.github.com/repos/huggingface/transformers/issues/12854 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12854/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12854/comments | https://api.github.com/repos/huggingface/transformers/issues/12854/events | https://github.com/huggingface/transformers/issues/12854 | 951,299,896 | MDU6SXNzdWU5NTEyOTk4OTY= | 12,854 | How could I convert output tensor from transformer to text 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)... | 1,627 | 1,630 | 1,630 | NONE | null | # 🚀 Feature request
https://github.com/onnx/models/blob/master/text/machine_comprehension/gpt-2/dependencies/GPT2-export.py
I succeeded in extracting the output tensor value for the example input text using the above example. The link above imports your hugging face transformer, so I wonder how I can text gener... | {
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https://api.github.com/repos/huggingface/transformers/issues/12853 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12853/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12853/comments | https://api.github.com/repos/huggingface/transformers/issues/12853/events | https://github.com/huggingface/transformers/pull/12853 | 951,246,099 | MDExOlB1bGxSZXF1ZXN0Njk1NjY1NjA4 | 12,853 | Fix barrier for SM distributed | {
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#12351 introduced a new context manager for having the main process execute an instruction while other process have to wait. That context manager was missing special treatment for TPUs (added in #12464) and SageMaker distributed. This PR adds the latter.
Fixes #12847 | {
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https://api.github.com/repos/huggingface/transformers/issues/12852 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12852/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12852/comments | https://api.github.com/repos/huggingface/transformers/issues/12852/events | https://github.com/huggingface/transformers/issues/12852 | 951,227,585 | MDU6SXNzdWU5NTEyMjc1ODU= | 12,852 | How to ignore PAD tokens for NER | {
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"The `attention_mask` indicates if a token is padding or an actual token. The usual way to deal with padding in the LSTM is to pass lengths for each sequence, you can work this out by summing the attention_mask along the \"time\" access, ie something like\r\n\r\n```\r\nsequence_lengths = torch.sum(attention_mask, d... | 1,627 | 1,636 | 1,627 | NONE | null | Hi,
Thank you for such a great repo. I am trying to use the word/token embeddings from the pretrained transformers for NER. The following code is a snippet of my model. For simplicity I am using a Linear decoder as opposed to a CRF decoder.
```
model_bert = BertModel.from_pretrained(model_dir, config=config)
... | {
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https://api.github.com/repos/huggingface/transformers/issues/12851 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12851/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12851/comments | https://api.github.com/repos/huggingface/transformers/issues/12851/events | https://github.com/huggingface/transformers/issues/12851 | 951,144,847 | MDU6SXNzdWU5NTExNDQ4NDc= | 12,851 | Got `ONNXRuntimeError` when try to run BART in ONNX format | {
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"I can reproduce in latest `transformers` with latest onnx runtime. ",
"FYI this error seems to be linked to the dimension of the input; if you use a batch size 2 it should work.\r\n\r\nAs seen with @mfuntowicz offline, we'll be working on a fix in the coming weeks cc @michaelbenayoun ",
"@LysandreJik Thank you... | 1,626 | 1,652 | null | 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: 4.9.0
- Platform: Linux-5.4.104+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.11
- PyTorch version ... | {
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https://api.github.com/repos/huggingface/transformers/issues/12850 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12850/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12850/comments | https://api.github.com/repos/huggingface/transformers/issues/12850/events | https://github.com/huggingface/transformers/issues/12850 | 951,137,428 | MDU6SXNzdWU5NTExMzc0Mjg= | 12,850 | run_mlm_no_trainer.py requires --model_name_or_path | {
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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)... | 1,626 | 1,630 | 1,630 | NONE | null | The `examples/pytorch/language-modeling/run_mlm_no_trainer.py` script has
parser.add_argument(
"--model_name_or_path",
type=str,
help="Path to pretrained model or model identifier from huggingface.co/models.",
default=None,
required=True,
)
Despite there being... | {
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"Thanks for flagging, I added those to all examples in the PR mentioned above!",
"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 g... | 1,626 | 1,629 | 1,629 | NONE | null | I just installed Transformers 4.9.0 as I'm really excited to investigate the tokeniser free CANINE model.
I noticed that the `examples/pytorch/language-modeling/run_mlm_no_trainer.py` script requires the `accelerate` library but that doesn't appear to be included in `examples/pytorch/language-modeling/requirements.t... | {
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"first, any reason why you're not using the latest scripts? The legacy scripts are no longer being maintained and the up-to-date scripts had great many improvements. So if it's not too hard I highly recommend switching to those. Most likely you want\r\nhttps://github.com/huggingface/transformers/blob/master/example... | 1,626 | 1,630 | 1,630 | NONE | null | Hi @stas00
Splitting of from https://github.com/huggingface/transformers/issues/8771#issuecomment-884865133
There is a lot of great information in your post; thanks for being thorough!
I guess I dont understand what parameters I need to change within the deepspeed config file to properly offload into cpu memo... | {
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"@philschmid @sgugger ",
"From offline discussion, the issue seem to be the following:\r\n1. You can’t use torch.distributed and smdp at the same time. You might want to change torch.distributed.barrier to sm_dist.barrier\r\n2. You could do import either torch.distributed or smdistributed.dataparallel.torch.distr... | 1,626 | 1,627 | 1,627 | CONTRIBUTOR | 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: 4.9.0 - dev
- Platform: Sagemaker
- Python version:
- PyTorch version (GPU?): 1.8.1
- Tensorflow version (... | {
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https://api.github.com/repos/huggingface/transformers/issues/12846 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12846/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12846/comments | https://api.github.com/repos/huggingface/transformers/issues/12846/events | https://github.com/huggingface/transformers/pull/12846 | 950,944,940 | MDExOlB1bGxSZXF1ZXN0Njk1NDEyMjEz | 12,846 | T5: Create position related tensors directly on device instead of CPU | {
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The current implementation of the `compute_bias` function of the T5 model creates tensors on the CPU (`memory_position` and `context_position`) and then moves them to the corresponding device with `.to()`.
While this has minimal impact in single-gpu training, in multi-gpu large batch traini... | {
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