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https://api.github.com/repos/huggingface/transformers/issues/11338 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11338/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11338/comments | https://api.github.com/repos/huggingface/transformers/issues/11338/events | https://github.com/huggingface/transformers/issues/11338 | 862,842,133 | MDU6SXNzdWU4NjI4NDIxMzM= | 11,338 | tf generate compatible with tf.function | {
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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)... | 1,618 | 1,622 | 1,622 | NONE | null | because the tf generate function is not compatible with tf.function，so i can not use this function in tf server
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"> Thanks for working on it!\r\n> \r\n> It is very specific to S2T and Wav2Vec2 but I don't think that's too much of an issue, we can adapt later.\r\n> \r\n> Could you add this pipeline to:\r\n> \r\n> * the documentation\r\n\r\nYes !\r\n> \r\n> * the main init\r\n\r\nYes\r\n\r\n> \r\n> * the `pipeline` ... | 1,618 | 1,619 | 1,619 | CONTRIBUTOR | null | # What does this PR do?
- Because we added everything to enable this pipeline, we probably
should add it to `transformers`.
- This PR tries to limit the scope and focuses only on the pipeline part
(what should go in, and out).
- The tests are very specific for S2T and Wav2vec2 to make sure both
architectures are suppo... | {
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https://api.github.com/repos/huggingface/transformers/issues/11336 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11336/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11336/comments | https://api.github.com/repos/huggingface/transformers/issues/11336/events | https://github.com/huggingface/transformers/issues/11336 | 862,746,183 | MDU6SXNzdWU4NjI3NDYxODM= | 11,336 | M2M-100 SentencePiece model produces tokens that are missing on the fixed dictionary | {
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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)... | 1,618 | 1,622 | 1,622 | NONE | null | ## 🐛 Bug
The SentencePiece model for [M2M-100](https://huggingface.co/transformers/model_doc/m2m_100.html) (https://dl.fbaipublicfiles.com/m2m_100/spm.128k.model) generates several tokens that are missing on the fixed dictionary (https://dl.fbaipublicfiles.com/m2m_100/data_dict.128k.txt)
### To Reproduce
Step... | {
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https://api.github.com/repos/huggingface/transformers/issues/11335 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11335/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11335/comments | https://api.github.com/repos/huggingface/transformers/issues/11335/events | https://github.com/huggingface/transformers/pull/11335 | 862,733,676 | MDExOlB1bGxSZXF1ZXN0NjE5MjU1NDYz | 11,335 | [GPTNeo] create local attention mask ones | {
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This PR refactors GPT Neo such that the causal attention mask for the local attention layer is only computed once per batch in the `GPTNeoModel` class and then shared between the layers instead of re-computing it in each layer.
I've verified that all slow tests are passing.
#### Benchma... | {
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https://api.github.com/repos/huggingface/transformers/issues/11334 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11334/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11334/comments | https://api.github.com/repos/huggingface/transformers/issues/11334/events | https://github.com/huggingface/transformers/issues/11334 | 862,654,817 | MDU6SXNzdWU4NjI2NTQ4MTc= | 11,334 | Bug in GPT2ForSequenceClassification | {
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"Ah, indeed, I think the identifier is incorrect. It needs to be updated to `microsoft/DialogRPT-updown`. Do you want to open a PR to fix this?\r\n\r\nThe issue you mention regarding the random weights is because the `gpt2` checkpoint doesn't have a sequence classification head. This is not the case for the checkpo... | 1,618 | 1,622 | 1,622 | CONTRIBUTOR | null | ## Environment info
google collab
##Problem
When I run the example code provided on huggingface site for GPT2ForSequenceClassification, an error is raised sayin that 'microsoft/dialogrpt' is not a checkpoint. See the bug bellow:
![bug1](https://user-images.githubusercontent.com/48957493/115378658-10619700-a1d1-11... | {
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https://api.github.com/repos/huggingface/transformers/issues/11333 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11333/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11333/comments | https://api.github.com/repos/huggingface/transformers/issues/11333/events | https://github.com/huggingface/transformers/issues/11333 | 862,637,347 | MDU6SXNzdWU4NjI2MzczNDc= | 11,333 | Potential bug: Tokens with punctuation are re-tokenized although I've set `is_split_into_words=True` | {
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"The `is_split_into_words` should be set to skip pre-tokenization (splitting on whitespace), not tokenization. This flag should be set to `True` if you have split your text into individual words, and you're now looking to have each word split into tokens and converted to IDs.\r\n\r\nThis seems to be unclear from th... | 1,618 | 1,619 | 1,619 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 4.5.1
- Platform: Linux-4.19.112+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.10
- PyTorch version (GPU?): 1.8.1+cu101 (False)
- Tensorflow version (GPU?): 2.4.1 (False)
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No
###... | {
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https://api.github.com/repos/huggingface/transformers/issues/11332 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11332/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11332/comments | https://api.github.com/repos/huggingface/transformers/issues/11332/events | https://github.com/huggingface/transformers/issues/11332 | 862,557,425 | MDU6SXNzdWU4NjI1NTc0MjU= | 11,332 | batch_encode_plus set a sort parameter | {
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"Sorted by length?\r\nHow this helps you?",
"> Sorted by length?\r\n> How this helps you?\r\n\r\nfor next lstm layer",
"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 issue... | 1,618 | 1,622 | 1,622 | NONE | null | # 🚀 Feature request
<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
When use `tokenizer.batch_encode_plus`, I hope get the sorted results, so hope have the sort parameter.
Such as: `tokenizer.batch_encode_plus(..., sorted=True... | {
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https://api.github.com/repos/huggingface/transformers/issues/11331 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11331/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11331/comments | https://api.github.com/repos/huggingface/transformers/issues/11331/events | https://github.com/huggingface/transformers/pull/11331 | 862,546,878 | MDExOlB1bGxSZXF1ZXN0NjE5MTAwMzM5 | 11,331 | [Generate] Remove outdated code | {
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"Merging (cc @LysandreJik, @sgugger)"
] | 1,618 | 1,618 | 1,618 | MEMBER | null | # What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this w... | {
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https://api.github.com/repos/huggingface/transformers/issues/11330 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11330/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11330/comments | https://api.github.com/repos/huggingface/transformers/issues/11330/events | https://github.com/huggingface/transformers/pull/11330 | 862,476,688 | MDExOlB1bGxSZXF1ZXN0NjE5MDQyMTA5 | 11,330 | Correcting comments in T5Stack to reflect correct tuple order | {
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"Hi, @talkhaldi thanks for correcting the other comment!\r\n\r\nThere is one code quality check failing, could run `make style && make quality` and push the code again?",
"Hi!\r\n\r\nThanks for your comment! The command you mentioned was requiring a lot of dependencies, some of which conflicted with the venv I w... | 1,618 | 1,622 | 1,622 | CONTRIBUTOR | null | # What does this PR do?
In order to match the actual order (line 513 and 516, and as accessed in 968), I've changed the order mentioned in comments L962 and L966-967.
## Before submitting
- [ x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
## Who can review?... | {
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https://api.github.com/repos/huggingface/transformers/issues/11329 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11329/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11329/comments | https://api.github.com/repos/huggingface/transformers/issues/11329/events | https://github.com/huggingface/transformers/pull/11329 | 862,358,721 | MDExOlB1bGxSZXF1ZXN0NjE4OTQ1NDgx | 11,329 | Honor contributors to models | {
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"Hi, thanks for this update!\r\nI guess my huggingface username is [`camembert`](https://huggingface.co/camembert) ...?",
"> # What does this PR do?\r\n> This PR mentions by HF username the person who added a given model in each doc file, and updates the template so this keeps being consistently done.\r\n> \r\n> ... | 1,618 | 1,619 | 1,619 | COLLABORATOR | null | # What does this PR do?
This PR mentions by HF username the person who added a given model in each doc file, and updates the template so this keeps being consistently done.
A few persons are missing, tagging there below. If you are one of the persons tagged, it would be great if you could create a HF account and ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11328 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11328/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11328/comments | https://api.github.com/repos/huggingface/transformers/issues/11328/events | https://github.com/huggingface/transformers/pull/11328 | 862,238,321 | MDExOlB1bGxSZXF1ZXN0NjE4ODMzNzIy | 11,328 | Trainer push to hub | {
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"Side note, the torchhub test uses the master branch to check which dependency to install (see [here](https://github.com/huggingface/transformers/blob/c0328a6c263494fff527fac7288faa627e3267e0/.github/workflows/github-torch-hub.yml#L36)), which means it can't pass until this PR is merged. Unless I missed something!"... | 1,618 | 1,619 | 1,619 | COLLABORATOR | null | # What does this PR do?
This PR begins the work to completely integrate the `Trainer` API with the [model hub](https://huggingface.co/models). It introduces a new mixin `PushToHubMixin` that implements the `push_to_hub` method. That mixin is then subclassed in all objects have a `save_pretrained` method: config, tok... | {
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https://api.github.com/repos/huggingface/transformers/issues/11327 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11327/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11327/comments | https://api.github.com/repos/huggingface/transformers/issues/11327/events | https://github.com/huggingface/transformers/issues/11327 | 861,988,941 | MDU6SXNzdWU4NjE5ODg5NDE= | 11,327 | run_ner.py example MobileBERT FP16 returns nan loss | {
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"It looks like mobileBERT was pretrained on TPUs using bfloat16, which then often result in NaNs when using FP16 for further fine-tuning (see #11076 or #10956). You'll be best off training in FP32 or use another model compatible with FP16.",
"Makes sense! That's interesting that affects the training on GPUs! I wi... | 1,618 | 1,618 | 1,618 | 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: 4.5.1
- Platform: Linux-5.8.0-44-generic-x86_64-with-glibc2.10
- Python version: 3.8.8
- PyTorch version (GP... | {
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https://api.github.com/repos/huggingface/transformers/issues/11326 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11326/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11326/comments | https://api.github.com/repos/huggingface/transformers/issues/11326/events | https://github.com/huggingface/transformers/issues/11326 | 861,954,468 | MDU6SXNzdWU4NjE5NTQ0Njg= | 11,326 | Parameter missing from state_dict of optimizer when loading from checkpoint | {
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"Could you upgrade to the latest version of Transformers and see if the problem persists? I have tried to reproduce but it all works fine on my side.",
"I have the same issue.",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be address... | 1,618 | 1,628 | 1,622 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: `'4.2.0dev0'`
- Platform: Debian
- Python version: `Python 3.6.10 |Anaconda, Inc.| (default, May 8 2020, 02:... | {
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https://api.github.com/repos/huggingface/transformers/issues/11325 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11325/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11325/comments | https://api.github.com/repos/huggingface/transformers/issues/11325/events | https://github.com/huggingface/transformers/pull/11325 | 861,899,431 | MDExOlB1bGxSZXF1ZXN0NjE4NTE3ODc4 | 11,325 | Enable added tokens | {
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"@sgugger, please merge if you're happy with the updated PR :)"
] | 1,618 | 1,620 | 1,620 | MEMBER | null | Currently, the only way to manage adding `AddedToken`s to a tokenizer is via the `tokenizer.add_special_tokens` or `tokenizer.add_tokens` methods; it should also be enabled from the initialization.
Previously this was impossible:
```py
special_tokens = [AddedToken('<special>')]
GPT2Tokenizer.from_pretrained('... | {
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https://api.github.com/repos/huggingface/transformers/issues/11324 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11324/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11324/comments | https://api.github.com/repos/huggingface/transformers/issues/11324/events | https://github.com/huggingface/transformers/pull/11324 | 861,867,132 | MDExOlB1bGxSZXF1ZXN0NjE4NDg4MTAy | 11,324 | [Trainer] Add a progress bar for batches skipped | {
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As suggested in #11284, this PR adds a progress bar for the batches skipped when resuming training from a checkpoint as well as a comment telling the user how to deactivate that behavior if they find it too long. | {
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https://api.github.com/repos/huggingface/transformers/issues/11323 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11323/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11323/comments | https://api.github.com/repos/huggingface/transformers/issues/11323/events | https://github.com/huggingface/transformers/issues/11323 | 861,744,931 | MDU6SXNzdWU4NjE3NDQ5MzE= | 11,323 | Bug in trainer: substantially different results from restarting from a checkpoint and without | {
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"You will only have perfectly reproducible results using checkpointing if the only randomness comes from the shuffling in your data (this is enforced by the CI). The way this is programmed inside the Trainer is to go through each epoch before the current one (which triggers the random shuffling) and then each batch... | 1,618 | 1,620 | 1,620 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.5.5
- Platform: linux
- Python version: 3.7
- PyTorch version (GPU?): 1.8
- Tensorflow version (GPU?): - ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11322 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11322/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11322/comments | https://api.github.com/repos/huggingface/transformers/issues/11322/events | https://github.com/huggingface/transformers/pull/11322 | 861,598,638 | MDExOlB1bGxSZXF1ZXN0NjE4MjQxOTQ5 | 11,322 | [Trainer] fix the placement on device with fp16_full_eval | {
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"We probably need to re-think the \"placement on device\" logic. And to do it explicitly in each stage and in `__init__` only in those special cases where it's absolutely required."
] | 1,618 | 1,618 | 1,618 | CONTRIBUTOR | null | * `do_train` isn't a reliable arg - it is not required to run `train), so for now add a workaround for the `fp16_full_eval` case to place the model on device if `train()` was called w/o `do_train=True` being passed to the Trainer args.
* while at it fix the `deepspeed` case, now that it's used in eval too, it should n... | {
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https://api.github.com/repos/huggingface/transformers/issues/11321 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11321/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11321/comments | https://api.github.com/repos/huggingface/transformers/issues/11321/events | https://github.com/huggingface/transformers/issues/11321 | 861,535,259 | MDU6SXNzdWU4NjE1MzUyNTk= | 11,321 | EncoderDecoderModel's decoder gets unexpected use_cache argument | {
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"Hi @biggoron \r\n\r\n`BertForMaskedLM` can't be used as a decoder, it's intended for masked LM. The `BertLMHeadModel` model should be used if you wan to use bert as a decoder. Also the right way to initialize the bert as decoder is as follows\r\n\r\n```python\r\ndec_config = BertConfig.from_pretrained(\"bert-base-... | 1,618 | 1,619 | 1,619 | NONE | null | ## Environment info
- `transformers` version: 4.5.1
- Platform: Linux-4.15.0-123-generic-x86_64-with-glibc2.10
- Python version: 3.8.8
- PyTorch version (GPU?): 1.8.1 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No
### W... | {
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https://api.github.com/repos/huggingface/transformers/issues/11320 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11320/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11320/comments | https://api.github.com/repos/huggingface/transformers/issues/11320/events | https://github.com/huggingface/transformers/issues/11320 | 861,493,251 | MDU6SXNzdWU4NjE0OTMyNTE= | 11,320 | Irregular VRAM usage with gpt-neo inference with sequences longer than 250 tokens | {
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"After asking about this on the EleutherAI discord, it was pointed out to me that 256 tokens corresponds to the local attention span of the model. Looking at the plot above, the first allocation peaks appear after about 256 tokens. After about 512 tokens, another shorter set of spikes occur, with more and shorter s... | 1,618 | 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: 4.5.1 / HEAD
- Platform: Linux/Colab Pro
- Python version: 3.7
- PyTorch version (GPU?): 1.8.1 (CUDA 11.0)
... | {
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https://api.github.com/repos/huggingface/transformers/issues/11319 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11319/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11319/comments | https://api.github.com/repos/huggingface/transformers/issues/11319/events | https://github.com/huggingface/transformers/issues/11319 | 861,461,850 | MDU6SXNzdWU4NjE0NjE4NTA= | 11,319 | Error in loading model tokenizer ('Helsinki-NLP/opus-mt-en-fr' actually loads 'Helsinki-NLP/opus-mt-en-de') | {
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"You should upgrade to the last version of transformers, which fully relies on the repository of a pretrained model instead of using special files like here.",
"Thanks!"
] | 1,618 | 1,620 | 1,620 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 4.3.3
- Platform: Windows-10-10.0.19041-SP0
- Python version: 3.7.1
- PyTorch version (GPU?): 1.7.0 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: not at this stage in the code
- Using distributed or parallel set-up in script?: no
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https://api.github.com/repos/huggingface/transformers/issues/11318 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11318/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11318/comments | https://api.github.com/repos/huggingface/transformers/issues/11318/events | https://github.com/huggingface/transformers/pull/11318 | 861,384,555 | MDExOlB1bGxSZXF1ZXN0NjE4MDU1ODAx | 11,318 | Load checkpoint without re-creating the model | {
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This PR avoids recreating the model when loading a checkpoint in the Trainer. As mentioned in #11294, the current loading messes up the model a user passed when some weights are frozen, which will yield to unexpected OOM errors.
A test is also added checking the frozen parameters are kept fr... | {
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https://api.github.com/repos/huggingface/transformers/issues/11317 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11317/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11317/comments | https://api.github.com/repos/huggingface/transformers/issues/11317/events | https://github.com/huggingface/transformers/issues/11317 | 861,277,476 | MDU6SXNzdWU4NjEyNzc0NzY= | 11,317 | large memory usage when resuming training from a checkpoint | {
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"Similar issue to https://github.com/huggingface/transformers/issues/11294",
"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 guide... | 1,618 | 1,622 | 1,622 | 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: 4.4.5
- Platform: linux
- Python version: 3.7
- PyTorch version (GPU?): 1.8
- Tensorflow version (GPU?): -... | {
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https://api.github.com/repos/huggingface/transformers/issues/11316 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11316/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11316/comments | https://api.github.com/repos/huggingface/transformers/issues/11316/events | https://github.com/huggingface/transformers/pull/11316 | 861,255,232 | MDExOlB1bGxSZXF1ZXN0NjE3OTQ5NjU1 | 11,316 | Added BERT pretraining example running on Graphcore IPUs to research projects | {
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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)... | 1,618 | 1,624 | 1,624 | CONTRIBUTOR | null | # What does this PR do?
Adds BERT pretraining example running on Graphcore IPUs to research projects
## Before submitting
- This was discussed in the HuggingFace/Graphcore meeting
## Who can review?
@LysandreJik
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"This code seems to be using `simpletransformers`, sadly we won't dive into that. You could use the `run_translation.py` script [here](https://github.com/huggingface/transformers/tree/master/examples/seq2seq) which supports multi-gpu training. See this [doc](https://github.com/huggingface/transformers/tree/master/e... | 1,618 | 1,622 | 1,622 | NONE | null | ## Environment info
- `transformers` version: 4.5.1
- Platform: Linux-5.4.0-1041-azure-x86_64-with-debian-buster-sid
- Python version: 3.7.9
- PyTorch version (GPU?): 1.8.1+cu102 (True)
- Tensorflow version (GPU?): 2.4.1 (False)
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: Yes
... | {
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https://api.github.com/repos/huggingface/transformers/issues/11314 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11314/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11314/comments | https://api.github.com/repos/huggingface/transformers/issues/11314/events | https://github.com/huggingface/transformers/pull/11314 | 861,130,981 | MDExOlB1bGxSZXF1ZXN0NjE3ODQ3NjU5 | 11,314 | Removed `max_length` from being mandatory within `generate`. | {
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"All tests pass, the max_length was actually a bug hidden by `while cur_len < max_length` that was still in there.\r\nThe bart tests (at least) caught it automatically and enabled me to change it to the correct comparison ! ",
"> All tests pass, the max_length was actually a bug hidden by `while cur_len < max_le... | 1,618 | 1,618 | 1,618 | CONTRIBUTOR | null | # What does this PR do?
- Moving on to fully using `StoppingCriteria` for `greedy` and `sample`
modes.
- `max_length` still used for `beam_search` and `group_beam_search`
(Follow up PR)
- Fixes a bug with MaxLengthStoppingCriteria (we should stop as soon a
we hit the max_length, the comparison needs to be or equal, th... | {
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https://api.github.com/repos/huggingface/transformers/issues/11313 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11313/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11313/comments | https://api.github.com/repos/huggingface/transformers/issues/11313/events | https://github.com/huggingface/transformers/pull/11313 | 861,129,822 | MDExOlB1bGxSZXF1ZXN0NjE3ODQ2Njk2 | 11,313 | [WIP] Add PiT | {
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Adds `PoolingTransformer` for image classification. https://github.com/naver-ai/pit
Todos:
- [ ] Fix tests
- [ ] Add doc
- [ ] port and push all `PiT` checkpoints | {
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"The I-BERT framework allows for easy fine-tuning in PyTorch to find the optimal parameters. Once those are found, the model can be deployed in a setup using int-8 capable operations such as TensorRT.\r\n\r\n@kssteven418 will be able to explain better than me.",
"Yes, the current I-BERT implementation (both in HF... | 1,618 | 1,623 | 1,623 | NONE | null | ## Environment info
- `transformers` version: 4.5.1
- Platform: Linux-5.8.0-49-generic-x86_64-with-glibc2.10
- Python version: 3.8.5
- PyTorch version (GPU?): 1.7.1 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: DDP (pytorch-l... | {
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https://api.github.com/repos/huggingface/transformers/issues/11311 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11311/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11311/comments | https://api.github.com/repos/huggingface/transformers/issues/11311/events | https://github.com/huggingface/transformers/pull/11311 | 861,050,711 | MDExOlB1bGxSZXF1ZXN0NjE3NzgyNDE3 | 11,311 | Update hf_argparser.py | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,618 | 1,622 | 1,622 | CONTRIBUTOR | null | Dictionary type should be annotated with `Dict`.
# What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/11310 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11310/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11310/comments | https://api.github.com/repos/huggingface/transformers/issues/11310/events | https://github.com/huggingface/transformers/issues/11310 | 861,017,697 | MDU6SXNzdWU4NjEwMTc2OTc= | 11,310 | [Benchmark] GPT2LMHeadModel (gpt2-medium) forward pass inference became 9% slower compared to 2.8.0 release | {
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"@patil-suraj Can you please check if this speed decrease of GPT2LMHeadModel model call is not caused by your PR #11225?",
"Hi @LSinev \r\n\r\nThank you for posting the detailed issue. I will take a look.",
"This issue has been automatically marked as stale because it has not had recent activity. If you think t... | 1,618 | 1,622 | 1,622 | CONTRIBUTOR | null | # 🖥 Benchmarking `GPT2LMHeadModel`
## Benchmark
GPT2LMHeadModel model call (and model.generate() too)
## Set-up
gpu: gtx 1080
pytorch 1.4.0
transformers 2.8.0, 3.5.1, 4.5.1 releases and latest master branch
Code to reproduce
```python
import timeit
import numpy as np
import torch
from transformer... | {
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https://api.github.com/repos/huggingface/transformers/issues/11309 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11309/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11309/comments | https://api.github.com/repos/huggingface/transformers/issues/11309/events | https://github.com/huggingface/transformers/pull/11309 | 861,007,075 | MDExOlB1bGxSZXF1ZXN0NjE3NzQ3Njky | 11,309 | Vit deit fixes | {
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"The notebook looks amazing!\r\n\r\nOut of curiosity, have you tried using `Trainer` to fine-tune `ViT`?",
"Added a notebook that uses the Trainer. Includes a nice confusion matrix at the end :) "
] | 1,618 | 1,620 | 1,620 | CONTRIBUTOR | null | # What does this PR do?
* Some small documentation improvements of ViT + DeiT.
* Adds a cats image to the `fixtures/test_samples` folder, which is used in the integration tests of both ViT and DeiT.
* Adds a community notebook, illustrating how to fine-tune the Vision Transformer on CIFAR-10.
(there's somethin... | {
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https://api.github.com/repos/huggingface/transformers/issues/11308 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11308/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11308/comments | https://api.github.com/repos/huggingface/transformers/issues/11308/events | https://github.com/huggingface/transformers/issues/11308 | 860,966,059 | MDU6SXNzdWU4NjA5NjYwNTk= | 11,308 | RAG with RAY implementation: Ray workers memory slowly increase over time. | {
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"I think I solved the memory leakage issue. In my case, I simply wanted to update the index parameters in **self.retriever object**. So I used **def set_index function**. But I observe for some reason ray works completely cannot flush out the old index and its related objects.\r\n\r\nSo now when I want to update... | 1,618 | 1,618 | 1,618 | CONTRIBUTOR | null | I fine-tune the RAG with RAY workers from 50 000 steps. When I checked the MEM% with the top command, I can see the memory consumption keep growing slowly. Usually, it should use around 20GB. After 50000 steps it raises up to 24 GB.
This could eventually lead to crash the system with OOM error. I did a background c... | {
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https://api.github.com/repos/huggingface/transformers/issues/11307 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11307/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11307/comments | https://api.github.com/repos/huggingface/transformers/issues/11307/events | https://github.com/huggingface/transformers/issues/11307 | 860,870,722 | MDU6SXNzdWU4NjA4NzA3MjI= | 11,307 | Getting time offsets of beginning and end of each word in Wav2Vec2 | {
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"@patrickvonplaten @patil-suraj @sgugger ",
"This sounds like a nice feature, but I sadly won't have time to work on it - let's see if someone in the community could be interested :-)",
"There is something like this which may help : https://github.com/lumaku/espnet/blob/espnet2_ctc_segmentation/espnet2/bin/asr_... | 1,618 | 1,687 | null | CONTRIBUTOR | null | # 🚀 Feature request
Hello I was thinking it would be of great help if I can get the time offsets of start and end of each word .
## Motivation
I was going through Google Speech to text documentation and found this [feature](https://cloud.google.com/speech-to-text/docs/async-time-offsets) and thought will be re... | {
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https://api.github.com/repos/huggingface/transformers/issues/11306 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11306/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11306/comments | https://api.github.com/repos/huggingface/transformers/issues/11306/events | https://github.com/huggingface/transformers/pull/11306 | 860,771,997 | MDExOlB1bGxSZXF1ZXN0NjE3NTYwOTMw | 11,306 | Wav2Vec2 Pretraining | {
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"I will take a deeper look tomorrow and comment here - looks great already :-)",
"Looks great to me so far @anton-l - I see no breaking changes, the modularization looks good to me and the parameter naming is fine as well -> don't think `self.quantizer.quantizer` is too awkward => we also have `self.self.self_att... | 1,618 | 1,623 | 1,623 | MEMBER | null | # What does this PR do?
Fixes #11246
This adds `Wav2Vec2ForPreTraining` which allows to pre-train Wav2Vec 2.0 on unlabeled audio with a self-supervised Vector Quantization task.
## Before submitting
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/master/CONTRIBU... | {
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https://api.github.com/repos/huggingface/transformers/issues/11305 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11305/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11305/comments | https://api.github.com/repos/huggingface/transformers/issues/11305/events | https://github.com/huggingface/transformers/issues/11305 | 860,626,279 | MDU6SXNzdWU4NjA2MjYyNzk= | 11,305 | invalid multinomial distribution (with replacement=False, not enough non-negative category to sample) | {
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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)... | 1,618 | 1,657 | 1,622 | CONTRIBUTOR | null | When using "sshleifer/distilbart-cnn-6-6" & do_sample the below code errors out, meanwhile the same code works for "sshleifer/distilbart-xsum-6-6". Am I missing something really obvious here? Thanks for any help!
Tranformers: 4.5.1
````
from transformers import (
AutoModelForSeq2SeqLM,
AutoTokenizer
... | {
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https://api.github.com/repos/huggingface/transformers/issues/11304 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11304/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11304/comments | https://api.github.com/repos/huggingface/transformers/issues/11304/events | https://github.com/huggingface/transformers/issues/11304 | 860,608,405 | MDU6SXNzdWU4NjA2MDg0MDU= | 11,304 | env about run longformer model downloaded from https://github.com/allenai/longformer | {
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"I created an env that cannot be copied",
"Please do not create duplicates.\r\nDuplicate of #11301 ",
"sorry, i close it now"
] | 1,618 | 1,618 | 1,618 | NONE | null | 1. just use `conda install transformers`，the transformers version is 4.4.2, can't run
1.1. error:
```bash
can't import pipline
# then use tokenizer and model to get my feature vector，ERROR：
RuntimeError: Error(s) in loading state_dict for BartModel:
siz... | {
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https://api.github.com/repos/huggingface/transformers/issues/11303 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11303/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11303/comments | https://api.github.com/repos/huggingface/transformers/issues/11303/events | https://github.com/huggingface/transformers/issues/11303 | 860,586,136 | MDU6SXNzdWU4NjA1ODYxMzY= | 11,303 | small bug in RAG model | {
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"This indeed looks like a typo! Thanks for your issue :-)\r\n\r\nThe kwargs should not be trimmed by `\"question_question_encoder\"`, but by `\"question_encoder\"`.\r\n\r\nWould you like to open a PR to fix it? Otherwise I can do it as well :-)",
"This issue has been automatically marked as stale because it has n... | 1,618 | 1,622 | 1,622 | 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: 4.5.1
- Platform: Linux-5.4.0-66-generic-x86_64-with-glibc2.27
- Python version: 3.8.3
- PyTorch version (GP... | {
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https://api.github.com/repos/huggingface/transformers/issues/11302 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11302/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11302/comments | https://api.github.com/repos/huggingface/transformers/issues/11302/events | https://github.com/huggingface/transformers/issues/11302 | 860,582,468 | MDU6SXNzdWU4NjA1ODI0Njg= | 11,302 | Problems with webbased editing of model cards | {
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"The probem only seems to happen on some models. This model here works ok: https://huggingface.co/T-Systems-onsite/cross-en-de-roberta-sentence-transformer",
"Tagging @Pierrci for visibility",
"Hi @PhilipMay, thank you for reporting this, we just deployed a fix for that, let us know if you still encounter the p... | 1,618 | 1,620 | 1,620 | CONTRIBUTOR | null | When I open a model in hugging face model repository - like here: https://huggingface.co/german-nlp-group/electra-base-german-uncased
And then click "Edit model card" the text in the webbased editor contains `\r` characters. When the webbased editor is now used to save the modelcard these characters are saved and sh... | {
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https://api.github.com/repos/huggingface/transformers/issues/11301 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11301/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11301/comments | https://api.github.com/repos/huggingface/transformers/issues/11301/events | https://github.com/huggingface/transformers/issues/11301 | 860,553,318 | MDU6SXNzdWU4NjA1NTMzMTg= | 11,301 | Longformer model with weight(model.encoder.embed_positions.weight) error | {
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"What code are you running that leads to that error?",
"# God, someone finally replied to me，thanks！\r\n## code\r\n```python\r\nfrom transformers import AutoModel, AutoTokenizer, pipeline\r\nimport torch\r\n\r\nmodel_name = 'pre-model/' + 'longformer-encdec-base-16384'\r\ntokenizer = AutoTokenizer.from_pretrained... | 1,618 | 1,622 | 1,622 | NONE | null | ```bash
RuntimeError: Error(s) in loading state_dict for BartModel:
size mismatch for model.encoder.embed_positions.weight: copying a param with shape torch.Size([16386, 768]) from checkpoint, the shape in current model is torch.Size([1026, 768]).
```
I use longformer model called longformer-encdec-base-16384 wh... | {
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https://api.github.com/repos/huggingface/transformers/issues/11300 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11300/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11300/comments | https://api.github.com/repos/huggingface/transformers/issues/11300/events | https://github.com/huggingface/transformers/pull/11300 | 860,524,909 | MDExOlB1bGxSZXF1ZXN0NjE3Mzg3ODU3 | 11,300 | EncoderDecoderConfigs should not create new objects | {
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"@patrickvonplaten @patil-suraj : Could please help me with the failed test? The error message is not that expressive:\r\n\r\n> Run cat reports/tests_templates_failures_short.txt\r\n> cat reports/tests_templates_failures_short.txt\r\n> shell: /usr/bin/bash -e {0}\r\n> env:\r\n> pythonLocation: /opt/hosted... | 1,618 | 1,619 | 1,619 | CONTRIBUTOR | null | # What does this PR do?
1. Removes the creation of separate config objects (pre PR 3:encoderdecoderConfig, encoderConfig, decoderConfig) and uses the existing ones (encoderConfig and decoderConfig now part of the encoderdecoderConfig)
2. Overwrite `resize_token_embeddings` from the parent class because it is not w... | {
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https://api.github.com/repos/huggingface/transformers/issues/11299 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11299/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11299/comments | https://api.github.com/repos/huggingface/transformers/issues/11299/events | https://github.com/huggingface/transformers/pull/11299 | 860,519,905 | MDExOlB1bGxSZXF1ZXN0NjE3Mzg0MzI1 | 11,299 | Pr2keep encoder decoder synced | {
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Fixes #11285 + adds an implementation for the `resize_token_embeddings method` (currently the parent class implementation is used which throws an error).
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [X] Did... | {
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https://api.github.com/repos/huggingface/transformers/issues/11297 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11297/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11297/comments | https://api.github.com/repos/huggingface/transformers/issues/11297/events | https://github.com/huggingface/transformers/pull/11297 | 860,475,207 | MDExOlB1bGxSZXF1ZXN0NjE3MzU1MTAw | 11,297 | Fixing bug in generation | {
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"Circle CI is unrelated - merging! Thanks a lot @nicola-decao "
] | 1,618 | 1,619 | 1,619 | CONTRIBUTOR | null | When passing `inputs_embeds` and not `input_ids=None` the generation function fails because `input_ids` is created but the function but it should not.
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [X] Did you read the [contributor guid... | {
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https://api.github.com/repos/huggingface/transformers/issues/11296 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11296/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11296/comments | https://api.github.com/repos/huggingface/transformers/issues/11296/events | https://github.com/huggingface/transformers/issues/11296 | 860,472,136 | MDU6SXNzdWU4NjA0NzIxMzY= | 11,296 | Cannot save GPT2 model with signature | {
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"Tbh, I've never really worked with `get_concrete_function()`, etc.... @Rocketknight1 - do you have an idea by any chance?",
"> Tbh, I've never really worked with `get_concrete_function()`, etc.... @Rocketknight1 - do you have an idea by any chance?\n\nI just realized I should tag the authors of the post I read a... | 1,618 | 1,619 | 1,619 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.5.0
- Platform: Windows-10-10.0.19041-SP0
- Python version: 3.7.4
- PyTorch version (GPU?): 1.8.1+cu111 (T... | {
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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)... | 1,618 | 1,638 | 1,622 | CONTRIBUTOR | null | # What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this w... | {
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https://api.github.com/repos/huggingface/transformers/issues/11294 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11294/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11294/comments | https://api.github.com/repos/huggingface/transformers/issues/11294/events | https://github.com/huggingface/transformers/issues/11294 | 860,379,431 | MDU6SXNzdWU4NjAzNzk0MzE= | 11,294 | serious bug with trainer.py when restarting the training from a checkpoint | {
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"You can also consider the modification in finetune_trainer.py\r\n\r\nhttps://github.com/huggingface/transformers/blob/1c06240e1b3477728129bb58e7b6c7734bb5074e/examples/legacy/seq2seq/finetune_trainer.py#L233\r\n\r\nIf you freeze some parameters as done in the line above, those would not be there when you load the ... | 1,618 | 1,618 | 1,618 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.5.1
- Platform: Linux
- Python version: 3.8
- PyTorch version (GPU?): 1.8
- Tensorflow version (GPU?): - ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11293 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11293/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11293/comments | https://api.github.com/repos/huggingface/transformers/issues/11293/events | https://github.com/huggingface/transformers/issues/11293 | 860,357,154 | MDU6SXNzdWU4NjAzNTcxNTQ= | 11,293 | OSError: Unable to load weights from pytorch checkpoint file | {
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"> Attempted to read a PyTorch file with version 3, but the maximum supported version for reading is 2. Your PyTorch installation may be too old. \r\n",
"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 t... | 1,618 | 1,622 | 1,622 | NONE | null | I got this error with MT5 model. Can anyone help?
```
(base) notooth@Debian:~$ python
Python 3.8.8 (default, Apr 13 2021, 19:58:26)
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> from transformers import MT5Model, T5Tokenizer
>>> model = M... | {
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https://api.github.com/repos/huggingface/transformers/issues/11292 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11292/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11292/comments | https://api.github.com/repos/huggingface/transformers/issues/11292/events | https://github.com/huggingface/transformers/pull/11292 | 860,341,074 | MDExOlB1bGxSZXF1ZXN0NjE3MjYwMDk1 | 11,292 | move device statements outside if statements | {
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<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this w... | {
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https://api.github.com/repos/huggingface/transformers/issues/11290 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11290/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11290/comments | https://api.github.com/repos/huggingface/transformers/issues/11290/events | https://github.com/huggingface/transformers/issues/11290 | 860,204,615 | MDU6SXNzdWU4NjAyMDQ2MTU= | 11,290 | Python crashes when loading Bert model from pretrained | {
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"Is it possible you're running out of RAM (not necessarily GPU RAM)?",
"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]... | 1,618 | 1,622 | 1,622 | NONE | null | Hello all, I am here because I am encountering a outmost obscure problem. Right when I begin by creating my model I encounter that my gpu usage spikes and then my python code crashes. This only happens when I try to use any of the models 'from_pretrained' only, I haven't had issues with neither Tensorflow nor PyTourch... | {
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https://api.github.com/repos/huggingface/transformers/issues/11289 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11289/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11289/comments | https://api.github.com/repos/huggingface/transformers/issues/11289/events | https://github.com/huggingface/transformers/issues/11289 | 860,201,404 | MDU6SXNzdWU4NjAyMDE0MDQ= | 11,289 | google/pegasus-cnn_dailymail generates blank file | {
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"Hi @chz816 \r\n\r\nI can reproduce the issue. This is because pegasus doesn't really work with `fp16`since its trained with `bfloat16`, so in most cases, it overflows and returns `nan` logits. The model works as expected in `fp32`, so if you run the above command without the `--fp16` arg, it should give the expec... | 1,618 | 1,619 | 1,619 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.2.0 and 4.5.1
- Platform: linux
- Python version: 3.6
- PyTorch version (GPU?): 1.7.1
- Tensorflow versio... | {
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https://api.github.com/repos/huggingface/transformers/issues/11288 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11288/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11288/comments | https://api.github.com/repos/huggingface/transformers/issues/11288/events | https://github.com/huggingface/transformers/issues/11288 | 860,172,377 | MDU6SXNzdWU4NjAxNzIzNzc= | 11,288 | Question about T5-11b model weights | {
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https://api.github.com/repos/huggingface/transformers/issues/11287 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11287/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11287/comments | https://api.github.com/repos/huggingface/transformers/issues/11287/events | https://github.com/huggingface/transformers/issues/11287 | 860,076,552 | MDU6SXNzdWU4NjAwNzY1NTI= | 11,287 | Zero-shot pipeline feature extraction | {
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"The ",
"> The\r\n\r\nYes?",
"Answering my question: pipeline returns the model as well. You just have to use it directly to extract the hidden states."
] | 1,618 | 1,618 | 1,618 | NONE | null | Is it possible to extract the hidden states representation from the zero-shot pipeline? I have these two tasks: feature extraction and zero-shot classification. But I don't want to load the same model twice, since it is a major burden on GPU memory. Any suggestions to how I can do both tasks without having to load it t... | {
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https://api.github.com/repos/huggingface/transformers/issues/11286 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11286/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11286/comments | https://api.github.com/repos/huggingface/transformers/issues/11286/events | https://github.com/huggingface/transformers/pull/11286 | 859,985,842 | MDExOlB1bGxSZXF1ZXN0NjE2OTcyNjc0 | 11,286 | Trainer support for IterableDataset for evaluation and predict | {
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This PR rewrites the entirety of the evaluation loop to add support for `IterableDataset`. The main problem with the current training loop is that, in distributed settings, it expects the indices of the evaluation set to come like this:
- `[0, 1, 2, 3, 4, 5, 6, 7, ...., 99]` for process 0
-... | {
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https://api.github.com/repos/huggingface/transformers/issues/11285 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11285/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11285/comments | https://api.github.com/repos/huggingface/transformers/issues/11285/events | https://github.com/huggingface/transformers/issues/11285 | 859,916,821 | MDU6SXNzdWU4NTk5MTY4MjE= | 11,285 | `resize_token_embeddings` not taken into account in `save_pretrained` for `EncoderDecoderModel` | {
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"This is caused by the EncoderDecoderConfig which initializes independent objects ([link](https://github.com/huggingface/transformers/blob/d9c62047a8d75e18d2849d345ab3394875a712ef/src/transformers/models/encoder_decoder/configuration_encoder_decoder.py#L84)) instead of utilizing the already existing ones.\r\n\r\nYo... | 1,618 | 1,619 | 1,619 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 4.5.0
- Platform: Darwin-17.7.0-x86_64-i386-64bit
- Python version: 3.7.2
- PyTorch version (GPU?): 1.4.0 (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: no
- Using distributed or parallel set-up in script?: no
### Who can help
@pa... | {
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https://api.github.com/repos/huggingface/transformers/issues/11284 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11284/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11284/comments | https://api.github.com/repos/huggingface/transformers/issues/11284/events | https://github.com/huggingface/transformers/issues/11284 | 859,914,569 | MDU6SXNzdWU4NTk5MTQ1Njk= | 11,284 | Loading from checkpoint seems to hang indefinitely for Roberta | {
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"The script is not hanging, it is skipping the first 660,000 batches since you are resuming training from there which takes a lot of time. If you don't mind continuing training with the same data, you can use the option `ignore_data_skip=True` in your training arguments.",
"@eh-93 Do you remember how much time it... | 1,618 | 1,676 | 1,622 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.5.0
- Platform: Linux-5.8.0-48-generic-x86_64-with-glibc2.29
- Python version: 3.8.7
- PyTorch version (GP... | {
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https://api.github.com/repos/huggingface/transformers/issues/11283 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11283/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11283/comments | https://api.github.com/repos/huggingface/transformers/issues/11283/events | https://github.com/huggingface/transformers/issues/11283 | 859,879,552 | MDU6SXNzdWU4NTk4Nzk1NTI= | 11,283 | Beam search decoding and language model integration for Wav2Vec2ForCTC models | {
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"Hey @tanujjain, \r\n\r\nWe are very interested in adding beam search for Wav2Vec2 + LM support in general, but sadly don't find the time to do so at the moment. We would be really happy about a contribution if you want to give it a try.\r\n\r\nAs a start we could add the logic to `examples/research_projects/wav2ve... | 1,618 | 1,636 | 1,625 | NONE | null | 1. AFAIK, `Wav2Vec2ForCTCTokenizer.decode` method only provides greedy decoding. Is there a Beamsearch implementation for CTC available yet?
2. Also, as it is a common norm in ASR modelling, language models are also generally added on top of the acoustic model. It would also be nice to have a possibility of appending... | {
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https://api.github.com/repos/huggingface/transformers/issues/11282 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11282/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11282/comments | https://api.github.com/repos/huggingface/transformers/issues/11282/events | https://github.com/huggingface/transformers/issues/11282 | 859,853,549 | MDU6SXNzdWU4NTk4NTM1NDk= | 11,282 | tf.function and half precision fails with Roberta models | {
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"Thanks for sharing this issue!\r\n\r\nThe issue here indeed comes from 1.0 that is not from the same dtype than `extended_attention_mask`. A better fix would be to align this line such as the other models by replacing it with:\r\n```\r\nextended_attention_mask = tf.cast(extended_attention_mask, dtype=embedding_out... | 1,618 | 1,621 | 1,621 | NONE | null | ## Environment info
- `transformers` version: 4.5.1
- Platform: Linux-5.4.0-71-generic-x86_64-with-glibc2.29
- Python version: 3.8.5
- PyTorch version (GPU?): 1.7.1 (False)
- Tensorflow version (GPU?): 2.4.1 (False)
- Using GPU in script?: No (but also fails with GPU)
- Using distributed or parallel set-up in ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11281 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11281/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11281/comments | https://api.github.com/repos/huggingface/transformers/issues/11281/events | https://github.com/huggingface/transformers/issues/11281 | 859,831,794 | MDU6SXNzdWU4NTk4MzE3OTQ= | 11,281 | Adding and consequently removing tokens leads to incorrect number of input embeddings | {
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"Hey @doubleplusnice,\r\n\r\nI can't really reproduce the bug. \r\n\r\nWhen running your code the output I get is:\r\n\r\n```\r\nSetting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\r\n/home/patrick/python_bin/transformers/generation_utils.py:963: UserWarning: `max_length` is deprecated in this f... | 1,618 | 1,622 | 1,622 | NONE | null | ## Environment info
- `transformers` version: 4.2.2
- Platform: Windows-10-10.0.19041-SP0
- Python version: 3.7.9
- PyTorch version (GPU?): 1.7.1+cpu (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No
### Who can help
Mod... | {
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https://api.github.com/repos/huggingface/transformers/issues/11280 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11280/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11280/comments | https://api.github.com/repos/huggingface/transformers/issues/11280/events | https://github.com/huggingface/transformers/issues/11280 | 859,800,647 | MDU6SXNzdWU4NTk4MDA2NDc= | 11,280 | failed to import BertModel | {
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"I don't know what your transformers version is, but from your error message, you should install `sentencepiece`: `pip install sentencepiece` or `conda install sentencepiece` with the appropriate channel (probably `conda-forge`)",
"Thank u very much, I have solved this problem. Your work is really remarkable.&nbs... | 1,618 | 1,618 | 1,618 | NONE | null | # 📚 Migration
## Information
The version of my torch is 1.6.0. When I want to import BertModel from transformers, it raised an error: ModuleNotFoundError: No module named '_sentencepiece'
I firstly activate my envs and used 'conda install transformers'.
Please help me, how can I address this problem? | {
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https://api.github.com/repos/huggingface/transformers/issues/11279 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11279/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11279/comments | https://api.github.com/repos/huggingface/transformers/issues/11279/events | https://github.com/huggingface/transformers/issues/11279 | 859,779,938 | MDU6SXNzdWU4NTk3Nzk5Mzg= | 11,279 | fp16 compatibility | {
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"Please fill in the issue template for us to help you. You seem to be on an older transformers version, this was fixed in recent versions.",
"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\nPl... | 1,618 | 1,621 | 1,621 | NONE | null | 我使用的是RTX3090，cuda11.0，系统是ubuntu 18.04
现在遇到问题如下，希望请教一下解决方法
^MEpoch: 0%| | 0/2 [00:00<?, ?it/s]
^MIteration: 0%| | 0/10860 [00:00<?, ?it/s]^[[A^MIteration: 0%| | 0/10860 [00:03<?, ?it/s]
^MEpoch: 0%| | 0/2 [00:03<?, ?it/s]
Selected optimization level O1: Insert automatic ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11278 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11278/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11278/comments | https://api.github.com/repos/huggingface/transformers/issues/11278/events | https://github.com/huggingface/transformers/issues/11278 | 859,752,846 | MDU6SXNzdWU4NTk3NTI4NDY= | 11,278 | [Benchmark] | {
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## Benchmark
Which part of `transformers` did you benchmark?
## Set-up
What did you run your benchmarks on? Please include details, such as: CPU, GPU? If using multiple GPUs, which parallelization did you use?
## Results
Put your results here! | {
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https://api.github.com/repos/huggingface/transformers/issues/11277 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11277/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11277/comments | https://api.github.com/repos/huggingface/transformers/issues/11277/events | https://github.com/huggingface/transformers/issues/11277 | 859,735,432 | MDU6SXNzdWU4NTk3MzU0MzI= | 11,277 | We should make an eco freindly phone and it should be affordable for everyone | {
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"Seems out of scope."
] | 1,618 | 1,618 | 1,618 | NONE | null | {
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https://api.github.com/repos/huggingface/transformers/issues/11276 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11276/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11276/comments | https://api.github.com/repos/huggingface/transformers/issues/11276/events | https://github.com/huggingface/transformers/issues/11276 | 859,696,327 | MDU6SXNzdWU4NTk2OTYzMjc= | 11,276 | Running gpt-neo 2.7B with less than 13GB of system memory like Colab | {
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A way to conserve regular system memory while loading large models. On systems without much system memory, the process crashes because it tries to load both the weight checkpoint and the model into system memory. In the case of gpt-neo 2.7B, this is even worse because the checkpoint is offered o... | {
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https://api.github.com/repos/huggingface/transformers/issues/11275 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11275/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11275/comments | https://api.github.com/repos/huggingface/transformers/issues/11275/events | https://github.com/huggingface/transformers/pull/11275 | 859,483,838 | MDExOlB1bGxSZXF1ZXN0NjE2NTU3NjM3 | 11,275 | modify double considering special tokens in `language_modeling.py` | {
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in `class TextDatasetForNextSentencePrediction`, double considering `self.tokenizer.num_special_tokens_to_add(pair=True)`
so, i remove `self.block_size`, and add parameter for `def create_examples_from_document` like `class LineByLineWithSOPTextDataset` do
Fixes # (issue) double con... | {
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https://api.github.com/repos/huggingface/transformers/issues/11274 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11274/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11274/comments | https://api.github.com/repos/huggingface/transformers/issues/11274/events | https://github.com/huggingface/transformers/pull/11274 | 859,400,794 | MDExOlB1bGxSZXF1ZXN0NjE2NDg4ODA5 | 11,274 | [debug utils] activation/weights underflow/overflow detector | {
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"> I haven't commented on each print statement, but they should use the logger maybe? \r\n\r\nI started with it first and then replaced with print, because we need all the horizontal space and the really busy long pre-amble is just getting in the way, IMHO. I also don't see what useful information it'd contribute b... | 1,618 | 1,619 | 1,619 | CONTRIBUTOR | null | This PR came to be out of the overflow issue we have been dealing with in t5/mt5/gpt-neo due to bf16 pretrained models. This PR:
* adds a new file `debug_utils.py`
* adds new helper debug class `DebugUnderOverflow` and function `detect_overflow` for doing the same for any tensor variable (useful for detailed debug)... | {
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https://api.github.com/repos/huggingface/transformers/issues/11273 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11273/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11273/comments | https://api.github.com/repos/huggingface/transformers/issues/11273/events | https://github.com/huggingface/transformers/pull/11273 | 859,391,145 | MDExOlB1bGxSZXF1ZXN0NjE2NDgxMDA2 | 11,273 | update dependency_versions_table | {
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https://api.github.com/repos/huggingface/transformers/issues/11272 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11272/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11272/comments | https://api.github.com/repos/huggingface/transformers/issues/11272/events | https://github.com/huggingface/transformers/issues/11272 | 859,343,781 | MDU6SXNzdWU4NTkzNDM3ODE= | 11,272 | squad_convert_example_to_features is broken | {
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"Please use `squad_convert_example_to_features_init(yourtokenizer)` to set the tokenizer."
] | 1,618 | 1,618 | 1,618 | NONE | null | ## Environment info
- `transformers` version: 4.2.2
- Platform: Linux-4.15.0-132-generic-x86_64-with-glibc2.10
- Python version: 3.8.5
- PyTorch version (GPU?): 1.7.1+cu101 (True)
- Tensorflow version (GPU?): No
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No
### Who can help
... | {
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https://api.github.com/repos/huggingface/transformers/issues/11271 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11271/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11271/comments | https://api.github.com/repos/huggingface/transformers/issues/11271/events | https://github.com/huggingface/transformers/issues/11271 | 859,315,034 | MDU6SXNzdWU4NTkzMTUwMzQ= | 11,271 | gpt-neo 2.7 crashes, 1.3 runs fine | {
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"I would guess that's a memory issue indeed! That should be the only difference between the two checkpoints.",
"Oof makes sense. I'll check back if that doesn't fix it. Thanks!",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addr... | 1,618 | 1,621 | 1,621 | NONE | null | Loading the generator crashes Python
```
python3
Python 3.8.5 (default, Jan 27 2021, 15:41:15)
[GCC 9.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> from transformers import pipeline
>>> generator = pipeline('text-generation', model='EleutherAI/gpt-neo-2.7B', device=0... | {
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https://api.github.com/repos/huggingface/transformers/issues/11270 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11270/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11270/comments | https://api.github.com/repos/huggingface/transformers/issues/11270/events | https://github.com/huggingface/transformers/pull/11270 | 859,281,467 | MDExOlB1bGxSZXF1ZXN0NjE2Mzg4NjQ1 | 11,270 | Workflow fixes | {
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"That's one advantage of using the docker images! We control the exact CUDA and torch versions by controlling the images directly, so it won't break until we manually update it, at which point we should remember to be extra careful about this dependency."
] | 1,618 | 1,618 | 1,618 | MEMBER | null | Fixes some workflow issues:
- Installs torch scatter in the CI with the appropriate pre-compiled version
- Removes DeepSpeed and Fairscale from the non-cuda-extension workflows
- Adds the forgotten reports for cuda-extension workflows
- Adds the result of the cuda-extension workflows to be sent to Slack
Also it ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11268 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11268/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11268/comments | https://api.github.com/repos/huggingface/transformers/issues/11268/events | https://github.com/huggingface/transformers/issues/11268 | 858,905,324 | MDU6SXNzdWU4NTg5MDUzMjQ= | 11,268 | DataCollatorForSOP marked as deprecated but DataCollatorForLanguageModeling does not offer the same functionality | {
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"The `sentence_order_label` will be left as is and collated if your dataset provides them. This is tested [here](https://github.com/huggingface/transformers/blob/2550b41aa2ec34f05ddfd3ec5875ddb32ad78d58/tests/test_data_collator.py#L268) which is adapted from the old test of `DataCollatorForSOP`.",
"Oh, now I see ... | 1,618 | 1,618 | 1,618 | NONE | null | The `DataCollatorForSOP` is marked as deprecated and it is recommended to use the `DataCollatorForLanguageModeling` instead. [Link to the data_collator.py](https://github.com/huggingface/transformers/blob/4bae96ec2bee265f938fc262201538819419089a/src/transformers/data/data_collator.py)
As far as I can tell, the label... | {
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https://api.github.com/repos/huggingface/transformers/issues/11267 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11267/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11267/comments | https://api.github.com/repos/huggingface/transformers/issues/11267/events | https://github.com/huggingface/transformers/issues/11267 | 858,891,748 | MDU6SXNzdWU4NTg4OTE3NDg= | 11,267 | inf/nan in generate (beam_sample) with small temperature values | {
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"Hi @elsanns \r\n\r\nGreat catch, thanks for the detailed explanation!\r\n\r\nYour observation is right and I can re-produce this error.\r\n\r\nRe, your question\r\n> should one just implement their own logits_warper handling float overflow?\r\n\r\nActually there's an `InfNanRemoveLogitsProcessor ` (#10769) which ... | 1,618 | 1,644 | 1,644 | CONTRIBUTOR | null | ## Environment info
- transformers` version: transformers version: '4.6.0.dev0'
- Platform: Linux
- Python version: 3.6.9
- PyTorch version (GPU?): '1.8.0' (yes)
## Information
The `generate` function (`beam_sample`) throws error when passing small temperature values.
## To reproduce
```
from transform... | {
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https://api.github.com/repos/huggingface/transformers/issues/11266 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11266/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11266/comments | https://api.github.com/repos/huggingface/transformers/issues/11266/events | https://github.com/huggingface/transformers/issues/11266 | 858,785,033 | MDU6SXNzdWU4NTg3ODUwMzM= | 11,266 | chunk of words for input token | {
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"Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.\r\nCould you ask your question on the [forum](https://discusss.huggingface.co) instead?\r\n\r\nThanks!",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this sti... | 1,618 | 1,621 | 1,621 | NONE | null | Hi I have some questions about using pretrained bert.
Can I put a chunk of words into one input token? For example, split "hi my name is Linda and today i will~" as "hi my name is Linda" and "and today i will" and make each split as one embedding vector (i.e using average word2vec) and treat each split vector as one... | {
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https://api.github.com/repos/huggingface/transformers/issues/11265 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11265/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11265/comments | https://api.github.com/repos/huggingface/transformers/issues/11265/events | https://github.com/huggingface/transformers/issues/11265 | 858,756,641 | MDU6SXNzdWU4NTg3NTY2NDE= | 11,265 | TensorFlow "predict" returns empty output with MirroredStrategy | {
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"Tested on latest release and still present.",
"Pinging our TensorFlow expert, @Rocketknight1 ",
"I've managed to reproduce this but I'm very confused about the cause, especially because I'm pretty sure I've used model.predict with MirroredStrategy in our codebase before.\r\n\r\nI've tested your code snippet wi... | 1,618 | 1,631 | 1,631 | NONE | null | I'm trying to use the `predict` method of the Keras TensorFlow API but it returns an empty output despite the input is being processed. Calling the model seems to work.
EDIT: the predict method works correctly if the model is loaded with single GPu strategy.
## Environment info
<!-- You can run the command `tran... | {
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https://api.github.com/repos/huggingface/transformers/issues/11264 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11264/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11264/comments | https://api.github.com/repos/huggingface/transformers/issues/11264/events | https://github.com/huggingface/transformers/issues/11264 | 858,735,802 | MDU6SXNzdWU4NTg3MzU4MDI= | 11,264 | Multi-Workers distributed training | {
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"Hi, here are a few resources to get you started:\r\n- [Examples](https://github.com/huggingface/transformers/tree/master/examples)\r\n- [Docs on distributed training](https://huggingface.co/transformers/examples.html#distributed-training-and-mixed-precision)",
"> Hi, here are a few resources to get you started:\... | 1,618 | 1,619 | 1,619 | NONE | null | Hi, does transformers support multi-workers distributed training for bert fine-tuning? | {
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https://api.github.com/repos/huggingface/transformers/issues/11263 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11263/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11263/comments | https://api.github.com/repos/huggingface/transformers/issues/11263/events | https://github.com/huggingface/transformers/issues/11263 | 858,595,826 | MDU6SXNzdWU4NTg1OTU4MjY= | 11,263 | TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect | {
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"Hi, please provide all the information required in the template so that we may help you. Thanks!",
"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 ... | 1,618 | 1,621 | 1,621 | NONE | null | Probably due to assertion, traceback is lost and I cannot debug the code.
C:\Users\m00596504\.virtualenvs\porn_tr\lib\site-packages\transformers\modeling_utils.py:1759: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so th... | {
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https://api.github.com/repos/huggingface/transformers/issues/11262 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11262/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11262/comments | https://api.github.com/repos/huggingface/transformers/issues/11262/events | https://github.com/huggingface/transformers/issues/11262 | 858,529,625 | MDU6SXNzdWU4NTg1Mjk2MjU= | 11,262 | Failed to import transformers | {
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"I think this is the same issue as https://github.com/huggingface/tokenizers/issues/585",
"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 [contr... | 1,618 | 1,704 | 1,624 | NONE | null | I got this error when importing transformers. Please help.
My system is Debian 10, Anaconda3.
```
$ python
Python 3.8.5 (default, Sep 4 2020, 07:30:14)
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> from transformers import pipeline
Traceback ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11261 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11261/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11261/comments | https://api.github.com/repos/huggingface/transformers/issues/11261/events | https://github.com/huggingface/transformers/issues/11261 | 858,510,743 | MDU6SXNzdWU4NTg1MTA3NDM= | 11,261 | --sharded_ddp "zero_dp_3 offload" fails with AssertionError | {
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"As replied on the forums, you should rather use `--deepspeed` for Zero-offload. We will investigate this bug, but there is another one for the gradient scaler that will block you either way.",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs... | 1,618 | 1,621 | 1,621 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.5.1
- Platform: Linux-5.4.0-1043-aws-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.9
- PyTorch ver... | {
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https://api.github.com/repos/huggingface/transformers/issues/11260 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11260/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11260/comments | https://api.github.com/repos/huggingface/transformers/issues/11260/events | https://github.com/huggingface/transformers/issues/11260 | 858,420,355 | MDU6SXNzdWU4NTg0MjAzNTU= | 11,260 | About pre-trained model : facebook/wav2vec2-large-xlsr-53 & facebook/wav2vec2-base | {
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"The xlsr model has no vocab, you need to build the processor yourself",
"https://huggingface.co/blog/fine-tune-xlsr-wav2vec2\r\nYou could check out this blogpost, there is it explained very well",
"@flozi00 Thank you very much! Processor is built. \r\n\r\nActually, I want to visualize the output of hidden laye... | 1,618 | 1,621 | 1,621 | NONE | null | Hi,
I am trying to load the pre-trained 'no fine-tuning' model of wav2vec2 to exact some features . The models, 'wav2vec2-base' and 'wav2vec2-large-xlsr-53', are not fine-tuned. Why are these files not exactly the same?
https://huggingface.co/facebook/wav2vec2-base/tree/main
https://huggingface.co/facebook/wav2... | {
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https://api.github.com/repos/huggingface/transformers/issues/11259 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11259/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11259/comments | https://api.github.com/repos/huggingface/transformers/issues/11259/events | https://github.com/huggingface/transformers/issues/11259 | 858,395,431 | MDU6SXNzdWU4NTgzOTU0MzE= | 11,259 | [Benchmark] | {
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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)... | 1,618 | 1,621 | 1,621 | NONE | null | # 🖥 Benchmarking `transformers`
## Benchmark
Which part of `transformers` did you benchmark?
## Set-up
What did you run your benchmarks on? Please include details, such as: CPU, GPU? If using multiple GPUs, which parallelization did you use?
## Results
Put your results here! | {
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https://api.github.com/repos/huggingface/transformers/issues/11258 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11258/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11258/comments | https://api.github.com/repos/huggingface/transformers/issues/11258/events | https://github.com/huggingface/transformers/pull/11258 | 858,271,915 | MDExOlB1bGxSZXF1ZXN0NjE1NTUzMzI5 | 11,258 | Support for set_epoch in IterableDataset | {
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I merged #11254 a bit too fast and forgot to actually call the `set_epoch` method in the main training loop at the beginning of each epoch.
Also, it looks like the Datasets library will deal internally with the RNG logic by having a `set_epoch` method, this PR allows support for that. | {
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"\n```",
"> # 🖥 Benchmarking `transformers`\n> \n> ## Benchmark\n> \n> Which part of `transformers` did you benchmark?\n> \n> ## Set-up\n> \n> What did you run your benchmarks on? Please include details, such as: CPU, GPU? If using multiple GPUs, which parallelization did you use?\n> \n> ## Results\n> \n> Put yo... | 1,618 | 1,618 | 1,618 | NONE | null | # 🖥 Benchmarking `transformers`
## Benchmark
Which part of `transformers` did you benchmark?
## Set-up
What did you run your benchmarks on? Please include details, such as: CPU, GPU? If using multiple GPUs, which parallelization did you use?
## Results
Put your results here! | {
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https://api.github.com/repos/huggingface/transformers/issues/11256 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11256/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11256/comments | https://api.github.com/repos/huggingface/transformers/issues/11256/events | https://github.com/huggingface/transformers/issues/11256 | 858,223,942 | MDU6SXNzdWU4NTgyMjM5NDI= | 11,256 | Getting KeyError: 'loss' when fine-tuning model on a pre-trained MLM | {
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"Hi @neel04. Regarding your code sample with simple reproducible data. I believe there are two errors here:\r\n- First, you've created your labels as a range from 1 to 20. You've set the model's `num_labels` to 20, but that, unfortunately, means it has a range of `[0, 19]`, therefore unable to satisfy the label 20.... | 1,618 | 1,621 | 1,621 | NONE | null | ## Environment info
- `transformers` version: 4.5.1
- Platform: Linux-4.19.112+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.10
- PyTorch version (GPU?): 1.8.1+cu101 (False)
- Tensorflow version (GPU?): 2.4.1 (False)
- Using GPU in script?: Depends - CPU for debugging
- Using distributed or parallel set... | {
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https://api.github.com/repos/huggingface/transformers/issues/11255 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11255/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11255/comments | https://api.github.com/repos/huggingface/transformers/issues/11255/events | https://github.com/huggingface/transformers/issues/11255 | 858,145,493 | MDU6SXNzdWU4NTgxNDU0OTM= | 11,255 | Big Bird generate() "local variable 'next_tokens' referenced before assignment" | {
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"cc @vasudevgupta7 ",
"@OscarGarciaF, i will need more details before i could see your issue. Are you using google/bigbird-roberta-base with EncoderDecoderModel for summarization? It would be great if you can share your code. ",
"@vasudevgupta7 I was using AutoModelForSeq2SeqLM (this is what you use for summari... | 1,618 | 1,668 | 1,621 | NONE | null | I am facing this problem when doing text summarization. I am using google/bigbird-roberta-base and I get the following error when calling model.generate(input, max_length = 4096, num_beams=4, early_stopping=True, length_penalty = 0.8):
```
Input length of input_ids is 4096, but ``max_length`` is set to 4096.This ca... | {
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https://api.github.com/repos/huggingface/transformers/issues/11254 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11254/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11254/comments | https://api.github.com/repos/huggingface/transformers/issues/11254/events | https://github.com/huggingface/transformers/pull/11254 | 858,144,735 | MDExOlB1bGxSZXF1ZXN0NjE1NDQ5MTI4 | 11,254 | Trainer iterable dataset | {
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This PR adds full support for `IterableDataset` training set in the main Trainer (just the training set, evaluation/prediction will require way more work). Up until now, the Trainer kind of support training dataset that are instances of `IterableDataset`, but in a distributed setting, the tra... | {
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https://api.github.com/repos/huggingface/transformers/issues/11253 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11253/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11253/comments | https://api.github.com/repos/huggingface/transformers/issues/11253/events | https://github.com/huggingface/transformers/pull/11253 | 858,142,240 | MDExOlB1bGxSZXF1ZXN0NjE1NDQ3MTI3 | 11,253 | New TF examples | {
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"I opened a new branch and PR at #11360 to avoid dealing with rebasing after the folder structure was changed around"
] | 1,618 | 1,651 | 1,619 | MEMBER | null | Opening a PR to get some feedback on the new TF example style before I write the rest.
Don't merge it yet, I haven't even finalized the filenames! | {
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https://api.github.com/repos/huggingface/transformers/issues/11252 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11252/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11252/comments | https://api.github.com/repos/huggingface/transformers/issues/11252/events | https://github.com/huggingface/transformers/pull/11252 | 858,122,084 | MDExOlB1bGxSZXF1ZXN0NjE1NDI5MzY3 | 11,252 | Fix for the issue of device-id getting hardcoded for token_type_ids during Tracing [WIP] | {
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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)... | 1,618 | 1,624 | 1,624 | CONTRIBUTOR | null | # What does this PR do?
Using Torchscript Trace API to convert the HF models is creating an issue , where during the tracing some of the name/id of the device getting hardcoded for some of the tensors. As a result position_embedding or token_type_embedding fail when model is loaded for inference on another device, a... | {
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https://api.github.com/repos/huggingface/transformers/issues/11251 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11251/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11251/comments | https://api.github.com/repos/huggingface/transformers/issues/11251/events | https://github.com/huggingface/transformers/pull/11251 | 858,082,214 | MDExOlB1bGxSZXF1ZXN0NjE1Mzk2MTkw | 11,251 | Add batching in TokenClassificationPipeline | {
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"FYI there is also work done on this pipeline in https://github.com/huggingface/transformers/pull/10568 if you want to give it a look! It doesn't concern batching, however.",
"Thanks, let me check that out. ",
"Please review this @LysandreJik , @Narsil , @joshdevins",
"Closing this PR based on @Narsil's revi... | 1,618 | 1,620 | 1,620 | CONTRIBUTOR | null | # What does this PR do?
Currently, the NER pipeline in transformers iterates through the list of input sentences and processes them, sequentially.
This PR adds batching support in the pipeline to decrease latency and use GPU more efficiently.
Relevant Issue :- #11244
## Benchmark Report
### Without Batch... | {
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## Benchmark
Which part of `transformers` did you benchmark?
## Set-up
What did you run your benchmarks on? Please include details, such as: CPU, GPU? If using multiple GPUs, which parallelization did you use?
## Results
Put your results here! | {
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https://api.github.com/repos/huggingface/transformers/issues/11249 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11249/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11249/comments | https://api.github.com/repos/huggingface/transformers/issues/11249/events | https://github.com/huggingface/transformers/issues/11249 | 858,033,140 | MDU6SXNzdWU4NTgwMzMxNDA= | 11,249 | TypeError: can't pickle _thread.RLock objects hyperparameter_search raytune | {
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"I also have this issue (bump)",
"Pinging @richardliaw, @amogkam ",
"@maxzzze looks like a serialization error with the Trainer. We will take a look at this, but in the meantime can you downgrade your transformers version to 4.4. Also see https://github.com/ray-project/ray/issues/15439.",
"So it looks like th... | 1,618 | 1,677 | 1,623 | 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: v4.5.1
- Platform: Linux
- Python version: 3.7.8
- PyTorch version (GPU?): yes
- Tensorflow version (GPU?):... | {
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https://api.github.com/repos/huggingface/transformers/issues/11248 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11248/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11248/comments | https://api.github.com/repos/huggingface/transformers/issues/11248/events | https://github.com/huggingface/transformers/pull/11248 | 857,997,620 | MDExOlB1bGxSZXF1ZXN0NjE1MzI1MTgx | 11,248 | Fix #10128 | {
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Small bug fix in numpy_pad_and_concatenate, as reported in #10128
Fixes #10128 | {
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https://api.github.com/repos/huggingface/transformers/issues/11247 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11247/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11247/comments | https://api.github.com/repos/huggingface/transformers/issues/11247/events | https://github.com/huggingface/transformers/pull/11247 | 857,961,506 | MDExOlB1bGxSZXF1ZXN0NjE1Mjk0NzQ5 | 11,247 | Adding pipeline task aliases. | {
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Two tasks were sort of not aligned with the pipeline names.
`sentiment-analysis` -> `TextClassificationPipeline`
`ner` -> `TokenClassificationPipeline`
In order to make this change backward compatible, yet make the code more consistent, this PR
introduces a TASK_ALIASES dictionary, w... | {
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This is a feature request to add Wav2Vec2 Pretraining functionality to the transformers library. This is a "Good Second Issue" feature request, which means that interested contributors should have some experience with the transformers library and ideally also with training/fine-tuning Wav2Vec2.
... | {
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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)... | 1,618 | 1,635 | 1,621 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 3.5.1
- Platform: GPU
- Python version: python 3.6.9
- PyTorch version (GPU): torch==1.4.0
### Who can he... | {
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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)... | 1,618 | 1,621 | 1,621 | CONTRIBUTOR | null | # 🚀 Feature request
Currently, the NER pipeline in transformers iterates through the list of input sentences and processes them, sequentially.
It would we beneficial to add batching support in the pipeline to decrease latency and use GPU more efficiently.
## Motivation
Batching will help use the GPU more eff... | {
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https://api.github.com/repos/huggingface/transformers/issues/11243 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11243/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11243/comments | https://api.github.com/repos/huggingface/transformers/issues/11243/events | https://github.com/huggingface/transformers/issues/11243 | 857,783,481 | MDU6SXNzdWU4NTc3ODM0ODE= | 11,243 | Cant load tokenizer locally after downloading it | {
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"Hi, that's because the tokenizer first looks to see if the path specified is a local path. Since you're saving your model on a path with the same identifier as the hub checkpoint, when you're re-running the script both the model and tokenizer will look into that folder.\r\n\r\nThe tokenizer doesn't find anything i... | 1,618 | 1,674 | 1,619 | NONE | null | Hi!
I'm following the tutorial for this pretrained model https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment. It works the first time I run it (and download the tokenizer) but after that it will complain that I don't have any tokenizer on the path specified.
The code is the following
```python
from... | {
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https://api.github.com/repos/huggingface/transformers/issues/11242 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11242/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11242/comments | https://api.github.com/repos/huggingface/transformers/issues/11242/events | https://github.com/huggingface/transformers/issues/11242 | 857,753,540 | MDU6SXNzdWU4NTc3NTM1NDA= | 11,242 | position_ids generated from Roberta | {
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"See https://github.com/huggingface/transformers/issues/10736#issuecomment-800175342\r\n\r\nTip: if you search on this Github repo \"position ids roberta\", you get a lot of answers.\r\n"
] | 1,618 | 1,618 | 1,618 | CONTRIBUTOR | null | Hi,
Roberta created `position_ids` from `input_ids` using [this function](https://github.com/huggingface/transformers/blob/3d339ee6595b9e42925559ae21a0f6e77f032873/src/transformers/models/roberta/modeling_roberta.py#L1494).
When the max sequence length is 512, I expect the `position_ids` to be [0, 1, ..., 512].
Ho... | {
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"Could you provide a reproducible code example alongside the error that happened?",
"my code is:\r\n................................................................\r\n```py\r\ntokenizer = AutoTokenizer.from_pretrained(\"bert-base-uncased\",max_len=256)\r\nvocab=[]\r\nwith open('vocab30k.txt', mode='r',encoding=\... | 1,618 | 1,622 | 1,622 | NONE | null | Hi,
I want to fine-tune Bert on tweets and I want to add some new tokens. I tried following code but it may have problem because after adding tokens and during reading sentences and tokenizing, it has lag and couldn't pass it.
any idea please?
I tried this:
tokenizer.add_tokens(["NEW_TOKEN"])
model.resize_token... | {
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https://api.github.com/repos/huggingface/transformers/issues/11240 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11240/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11240/comments | https://api.github.com/repos/huggingface/transformers/issues/11240/events | https://github.com/huggingface/transformers/pull/11240 | 857,483,969 | MDExOlB1bGxSZXF1ZXN0NjE0ODk1MzIx | 11,240 | Close open files to suppress ResourceWarning | {
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<!--
Across the repo, we are opening a bunch of files and not closing them. This seems to cause issue when trying to programatically access them. This also raise ResourceWarning at a few places, for instance - transformers/convert_slow_tokenizer.py:308: ResourceWarni... | {
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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)... | 1,618 | 1,621 | 1,621 | NONE | null | # 📚 Migration
## Information
<!-- Important information -->
I am getting `NameError: name 'BertOnlyMLMHead' is not defined` error when I try to upgrade the transformers version used by [Oscar code](https://github.com/microsoft/Oscar) from pytorch-transformers to latest version of huggingface transformers.
Mo... | {
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https://api.github.com/repos/huggingface/transformers/issues/11238 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11238/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11238/comments | https://api.github.com/repos/huggingface/transformers/issues/11238/events | https://github.com/huggingface/transformers/pull/11238 | 857,402,739 | MDExOlB1bGxSZXF1ZXN0NjE0ODI5NjA5 | 11,238 | Fix dimention misspellings. | {
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Replaces dimention mispelling with the proper spelling dimension.
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob... | {
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"ok, it's all working in the Deepspeed team's test suite - yay! "
] | 1,618 | 1,618 | 1,618 | CONTRIBUTOR | null | Deepspeed devs, who will be running our deepspeed tests as part of their tests, discovered that we had an unbound number of nodes and gpus in the tests so it was firing on multiple nodes and many gpus, so wasn't quite ready for it. So fixing it. | {
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- starts a new "troubleshooting" document
- adds a note xref to `from_pretrained`
Surely we can start populating the new "troubleshooting" document - the idea her... | {
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