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"Duplicate of https://github.com/huggingface/transformers/issues/10285"
] | 1,614 | 1,614 | 1,614 | 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: 4.3.2
- Platform: linux
- Python version: 3.7
- PyTorch version (GPU?): 1.7
- Tensorflow version (GPU?): ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10331 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10331/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10331/comments | https://api.github.com/repos/huggingface/transformers/issues/10331/events | https://github.com/huggingface/transformers/pull/10331 | 813,535,532 | MDExOlB1bGxSZXF1ZXN0NTc3NjY4MDk2 | 10,331 | Add note to resize token embeddings matrix when adding new tokens to voc | {
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https://api.github.com/repos/huggingface/transformers/issues/10330 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10330/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10330/comments | https://api.github.com/repos/huggingface/transformers/issues/10330/events | https://github.com/huggingface/transformers/issues/10330 | 813,515,833 | MDU6SXNzdWU4MTM1MTU4MzM= | 10,330 | [DeepSpeed] strange learning rate schedule in linear_schedule_with_warmup | {
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"Incidentally a bug fix was just merged as part of: https://github.com/huggingface/transformers/pull/10310\r\n- the scheduler step was getting run twice.\r\n\r\nCould you please re-test with `transformers` master?\r\n\r\nThank you!\r\n",
"Thank you for your response.\r\n\r\nI have tested the latest version, but t... | 1,614 | 1,614 | 1,614 | 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: 4.3.2
- Platform: Linux
- Python version: 3.7.3
- PyTorch version (GPU?): 1.7 (yes)
- Tensorflow version (G... | {
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https://api.github.com/repos/huggingface/transformers/issues/10329 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10329/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10329/comments | https://api.github.com/repos/huggingface/transformers/issues/10329/events | https://github.com/huggingface/transformers/issues/10329 | 813,500,123 | MDU6SXNzdWU4MTM1MDAxMjM= | 10,329 | Raise an error instead of a warning when model files are not loaded correctly | {
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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)... | 1,614 | 1,649 | 1,619 | CONTRIBUTOR | null | # 🚀 Feature request
Currently, when I initialize a model and if my pre-trained model files aren't fully matched with my model architecture, code silently logs the event and warns the user. I think it is better to have a flag to stop the training if model weights are not loaded as expected.
## Motivation
With ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10328 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10328/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10328/comments | https://api.github.com/repos/huggingface/transformers/issues/10328/events | https://github.com/huggingface/transformers/pull/10328 | 813,460,260 | MDExOlB1bGxSZXF1ZXN0NTc3NjA1MDA1 | 10,328 | DeBERTa-v2 fixes | {
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https://api.github.com/repos/huggingface/transformers/issues/10327 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10327/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10327/comments | https://api.github.com/repos/huggingface/transformers/issues/10327/events | https://github.com/huggingface/transformers/issues/10327 | 813,413,439 | MDU6SXNzdWU4MTM0MTM0Mzk= | 10,327 | mBART 50 models not found in model shortcut name list | {
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"Hi @codingnoobneedshelp , thank for reporting this issue. Right now MBart50Tokenizer does not work with `AutoTokenizer`.\r\nThere will be a new script for translation in the next ~2 weeks that will handle this issue. For now, you could just modify the script to use `MBart50Tokenizer`, instead of `AutoTokenizer`."... | 1,613 | 1,618 | 1,618 | NONE | null | Transformers version: 4.4.0.dev0
Hello, I'm trying to fine-tune mBART 50 with your seq2seq examples.
Getting this error:
Model name 'facebook/mbart-large-50' not found in model shortcut name list (facebook/mbart-large-en-ro, facebook/mbart-large-cc25).
Traceback (most recent call last):
File "/content/tr... | {
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I'm trying T5-3b with DeepSpeed on 2 V100-32GB GPU's. But I'm unable to increase batch size beyond 4 with max i/p sequence length of 512 and max o/p sequence length of 4.
Previously I tried with t5.parallelize() [ i.e, without DeepSpeed ] on same setup and was able to train with batch size of 2.
Below are ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10325 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10325/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10325/comments | https://api.github.com/repos/huggingface/transformers/issues/10325/events | https://github.com/huggingface/transformers/issues/10325 | 813,322,833 | MDU6SXNzdWU4MTMzMjI4MzM= | 10,325 | Input mismatch with TFDistilBert training from scratch inspite of cross checking input dimensions | {
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"Hello!\r\n\r\nAs first, I can see several issues on the way you want to train the model:\r\n1. The way you build your dataset is not correct. More precisely, in the `tokenize` function, the first element of the tuple (`a.ids`) is taken as the input, and the second (`a.attention_mask`) is taken as the label. Hence ... | 1,613 | 1,614 | 1,614 | 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: 4.3.2
- Platform: Colab
- Python version: 3.6
- PyTorch version (GPU?): None
- Tensorflow version (GPU?): 2... | {
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"> This approach looks great and doesn't seem limiting at all. Implementing it for Wav2Vec2/SpeechToTextTransformer and refactoring/upstreaming methods down the road seems like a good implementation roadmap.\r\n> \r\n> Regarding the implementation of `FeatureProcessors`, what do you have in mind regarding understan... | 1,613 | 1,614 | 1,614 | MEMBER | null | # 🚨🚨🚨**IMPORTANT** Wav2Vec2 repositories that were added before 4.4 should make sure to manually add a feature extractor class.
This can be done as easily as doing:
```
git clone <your/repo/>
cd <your/repo/>
```
```python
from transformers import Wav2Vec2FeatureExtractor
feat_extract = Wav2Vec2Feature... | {
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https://api.github.com/repos/huggingface/transformers/issues/10321 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10321/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10321/comments | https://api.github.com/repos/huggingface/transformers/issues/10321/events | https://github.com/huggingface/transformers/issues/10321 | 812,961,618 | MDU6SXNzdWU4MTI5NjE2MTg= | 10,321 | [Tensor Parallelism] Megatron-LM to transformers | {
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"@stas00 thanks for starting this thread!\r\n\r\nI guess, in order for everyone to be on the same page, a brief explanation of horizontal parallelism is needed. This would be a good place for future reference and introduce other contributors to the core concepts.\r\n\r\n**NOTE for everyone reading:** If you find an... | 1,613 | 1,706 | null | CONTRIBUTOR | null | # 🚀 Feature request
Splitting the discussion that started here: https://github.com/huggingface/transformers/pull/10301#issuecomment-782917393 to add the potential future feature of transformers and it's Tensor Parallelism (Horizontal Model Parallelism) - for bigger context please see [Parallelism notes](https://git... | {
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https://api.github.com/repos/huggingface/transformers/issues/10320 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10320/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10320/comments | https://api.github.com/repos/huggingface/transformers/issues/10320/events | https://github.com/huggingface/transformers/issues/10320 | 812,904,488 | MDU6SXNzdWU4MTI5MDQ0ODg= | 10,320 | BERT for speech | {
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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\nAlso, [here's the doc](https://huggingface.co/transformers/model_doc/wav2vec2.html#transformers.Wav2Vec2ForCTC) for `Wav2Vec... | 1,613 | 1,614 | 1,614 | NONE | null | How can I use HF's BERT models for speech-to-text training? | {
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https://api.github.com/repos/huggingface/transformers/issues/10319 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10319/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10319/comments | https://api.github.com/repos/huggingface/transformers/issues/10319/events | https://github.com/huggingface/transformers/issues/10319 | 812,902,286 | MDU6SXNzdWU4MTI5MDIyODY= | 10,319 | [Question] Add a new token to tokenizer and bart model | {
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"Hello! You should use the [resize_token_embeddings](https://huggingface.co/transformers/main_classes/model.html?highlight=resize_token_embeddings#transformers.PreTrainedModel.resize_token_embeddings) method for that. Will add that to the documentation."
] | 1,613 | 1,614 | 1,614 | NONE | null | Hi,
I have extended the word embedding of a tokenizer and a bart model through `tokenizer.add_token()` and `model.resize_token_embeddings(len(tokenizer))`. Because the ground truth consist of a newly added token, the dimension of the decoder output should be extended as well.
But I can't figure out how to extend ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10318 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10318/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10318/comments | https://api.github.com/repos/huggingface/transformers/issues/10318/events | https://github.com/huggingface/transformers/issues/10318 | 812,890,565 | MDU6SXNzdWU4MTI4OTA1NjU= | 10,318 | Guidance for continued pre-training of BART with de-noising. | {
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"also it is my questions, thanks ",
"denoising function is a part of T5 pretraining as well, is there a denoising function implementation in Huggingface repo ? Any advice is appreciated. thanks ",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still ... | 1,613 | 1,619 | 1,619 | NONE | null | # 🚀 Feature request
An example of continued pre-training of BART with de-noising.
## Motivation
I'm using the run causal LM [script](https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_clm.py), but it seems on line 340, it's simply copying input to output (learning the ident... | {
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https://api.github.com/repos/huggingface/transformers/issues/10317 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10317/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10317/comments | https://api.github.com/repos/huggingface/transformers/issues/10317/events | https://github.com/huggingface/transformers/issues/10317 | 812,868,377 | MDU6SXNzdWU4MTI4NjgzNzc= | 10,317 | ForTokenClassification head on BART | {
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"It would be great to have a `BartForTokenClassification`. Does it use the same head as `BertForTokenClassification`, etc.? \r\n\r\nFeel free to open a PR :) ",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment o... | 1,613 | 1,619 | 1,619 | CONTRIBUTOR | null | # 🚀 Feature request
Hello guys! I'm trying to reproduce the token classification experiments from the [BART paper](https://arxiv.org/abs/1910.13461) using the HF/Transformers and found that a token classification head is missing on the current BART model HF implementation.
The current BART implementation only h... | {
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https://api.github.com/repos/huggingface/transformers/issues/10316 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10316/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10316/comments | https://api.github.com/repos/huggingface/transformers/issues/10316/events | https://github.com/huggingface/transformers/pull/10316 | 812,853,423 | MDExOlB1bGxSZXF1ZXN0NTc3MTA5OTY0 | 10,316 | fix typo in conversion script | {
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"Wonderful! Thank you for this fix, @tagucci! \r\n\r\n(I tweaked your PR to run `make style` to appease to auto-formatters to have CI pass)"
] | 1,613 | 1,613 | 1,613 | CONTRIBUTOR | null | # What does this PR do?
Fix typo in `convert_fsmt_original_pytorch_checkpoint_to_pytorch.py`
## 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?
Anyone in the community is free to review the PR once the tests have ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10315 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10315/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10315/comments | https://api.github.com/repos/huggingface/transformers/issues/10315/events | https://github.com/huggingface/transformers/issues/10315 | 812,838,555 | MDU6SXNzdWU4MTI4Mzg1NTU= | 10,315 | Huggingface mt5 does not reach the performance of original mt5 on paws-x | {
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"Hey @dorost1234, \r\n\r\ncould you post your question on the [forum](https://discuss.huggingface.co/) and see whether you can get help from the community there? We try to keep GitHub issues for bug reports mostly. \r\n\r\nIt would also be very important that you attach a notebook or something that allows people to... | 1,613 | 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: 4.3.2
- Platform: linux
- Python version: 3.7
- PyTorch version (GPU?): 1.7
- Tensorflow version (GPU?): -... | {
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https://api.github.com/repos/huggingface/transformers/issues/10314 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10314/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10314/comments | https://api.github.com/repos/huggingface/transformers/issues/10314/events | https://github.com/huggingface/transformers/pull/10314 | 812,834,466 | MDExOlB1bGxSZXF1ZXN0NTc3MDk2Mjg5 | 10,314 | ConvBERT fix torch <> tf weights conversion | {
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"I'll push the fixed weights and remove from_pt in test.",
"> Ok with the change!\r\n> \r\n> Should we do a patch release for this?\r\n\r\nThink it's a good idea",
"Thanks @patrickvonplaten ",
"Ok will do a patch this afternoon",
"cc @stefan-it and @mrm8488 that have been playing with the model. We'll relea... | 1,613 | 1,614 | 1,614 | MEMBER | null | (from @patrickvonplaten):
This PR corrects the shape of the grouped linear layer weight so that the general conversion function does not have to be changed.
All models are tested to work correctly as follows:
```python
from transformers import ConvBertModel, TFConvBertModel
import tensorflow as tf
import to... | {
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https://api.github.com/repos/huggingface/transformers/issues/10313 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10313/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10313/comments | https://api.github.com/repos/huggingface/transformers/issues/10313/events | https://github.com/huggingface/transformers/issues/10313 | 812,813,439 | MDU6SXNzdWU4MTI4MTM0Mzk= | 10,313 | ValueError: too many values to unpack (expected 2) | {
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"Please post the full error stacktrace. Which version of the script are you using?",
"Hi thank you for your reply. I did post the trace back for the error.\n\nLooking forward to your reply\n\nHadeel\n\n\n\n> On 21 Feb 2021, at 10:01 am, cronoik <notifications@github.com> wrote:\n> \n> \n> Please post the full er... | 1,613 | 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: 3.0.2
- Platform: Linux-4.19.112+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.9
- PyTorch version (... | {
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https://api.github.com/repos/huggingface/transformers/issues/10312 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10312/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10312/comments | https://api.github.com/repos/huggingface/transformers/issues/10312/events | https://github.com/huggingface/transformers/issues/10312 | 812,812,987 | MDU6SXNzdWU4MTI4MTI5ODc= | 10,312 | LayoutLM Tensorflow model | {
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"Sure, I can guide you if you want.\r\n\r\nAs LayoutLM is only a slight adaptation from BERT, I guess you can define `modeling_tf_layoutlm.py` based on `modeling_tf_bert.py`. Note that all layers should be renamed, e.g. `TFBertEmbeddings` -> `TFLayoutLMEmbeddings`. LayoutLM adds position embeddings for the tokens ... | 1,613 | 1,616 | 1,616 | CONTRIBUTOR | null | # 🚀 Feature request
It would be great if there was a TF version of the layoutlm. I see there are scripts in the repo to convert PyTorch checkpoints to TF models but I think the requirement is to have a TF model architecture to be able to load PyTorch model's wights in it.
## Motivation
We are using TF in produc... | {
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https://api.github.com/repos/huggingface/transformers/issues/10311 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10311/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10311/comments | https://api.github.com/repos/huggingface/transformers/issues/10311/events | https://github.com/huggingface/transformers/issues/10311 | 812,799,578 | MDU6SXNzdWU4MTI3OTk1Nzg= | 10,311 | Matrix multiplication error for ReformerModelWithLMHead when tie_word_embeddings is True | {
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"Hey @xe442,\r\n\r\nActually Reformer cannot make use of `tie_word_embeddings=True` because the output word embedding layer is twice as big as the input layer (because of Reformer's architecture, see section 3) in this blog: https://huggingface.co/blog/reformer",
"But, we should in this case give a better error m... | 1,613 | 1,619 | 1,619 | NONE | null | ## Environment info
- `transformers` version: 4.3.2
- Platform: Windows 10
- Python version: 3.8.5
- PyTorch version (GPU?): 1.7.0 cpu-only
- Tensorflow version (GPU?): not installed
- Using GPU in script?: no
- Using distributed or parallel set-up in script?: no
### Who can help
- longformer, reformer, ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10310 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10310/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10310/comments | https://api.github.com/repos/huggingface/transformers/issues/10310/events | https://github.com/huggingface/transformers/pull/10310 | 812,794,898 | MDExOlB1bGxSZXF1ZXN0NTc3MDY3OTI0 | 10,310 | [Trainer] implement gradient_accumulation_steps support in DeepSpeed integration | {
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"> Cool that they added it! This all looks pretty good to me!\r\n\r\nWell, it has been there all this time, this PR just bolts it on correctly.\r\n\r\n> Absolutely no problems with moving the regression trainer somewhere accessible, it was just in `test_trainer` because only used there.\r\n\r\nAh, that makes sense.... | 1,613 | 1,614 | 1,614 | CONTRIBUTOR | null | This PR:
Fixes in a bug:
- `lr_scheduler.step()` shouldn't be called under DeepSpeed - it's already called in its `optimizer.step()` internally - so it was moving through the scheduler rate change at twice the speed :(
Adds support for `gradient_accumulation_steps`:
* makes `gradient_accumulation_steps` work wi... | {
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https://api.github.com/repos/huggingface/transformers/issues/10309 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10309/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10309/comments | https://api.github.com/repos/huggingface/transformers/issues/10309/events | https://github.com/huggingface/transformers/issues/10309 | 812,733,551 | MDU6SXNzdWU4MTI3MzM1NTE= | 10,309 | [Example] Using label_smoothing_factor raise error when evaluating model | {
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"Can reproduce locally, here is a short reproducer from the root of the repo:\r\n```\r\npython examples/token-classification/run_ner.py \\\r\n --model_name_or_path bert-base-uncased \\\r\n --train_file tests/fixtures/tests_samples/conll/sample.json \\\r\n --validation_file tests/fixtures/tests_samples/conll/samp... | 1,613 | 1,614 | 1,614 | 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: 4.3.2
- Platform: Ubuntu 20.04
- Python version: 3.8
- PyTorch version (GPU): 1.6.0
### Who can help
L... | {
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https://api.github.com/repos/huggingface/transformers/issues/10308 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10308/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10308/comments | https://api.github.com/repos/huggingface/transformers/issues/10308/events | https://github.com/huggingface/transformers/pull/10308 | 812,709,424 | MDExOlB1bGxSZXF1ZXN0NTc3MDA4MzMx | 10,308 | [ci] don't fail when there are no zombies | {
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```
Run pkill -f tests; pkill -f examples
4
Error: Process completed with exit code 1.
```
Didn't think that it'd `exit(1)` when there is nothing to kill
@sgugger | {
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https://api.github.com/repos/huggingface/transformers/issues/10307 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10307/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10307/comments | https://api.github.com/repos/huggingface/transformers/issues/10307/events | https://github.com/huggingface/transformers/issues/10307 | 812,702,719 | MDU6SXNzdWU4MTI3MDI3MTk= | 10,307 | pretraining objective of T5 model | {
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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)... | 1,613 | 1,619 | 1,619 | 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. -->
Hi, it would be great to have pretraining of T5 model implemented. Currently, run_mlm.py script does not support it.
## Motivation
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https://api.github.com/repos/huggingface/transformers/issues/10306 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10306/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10306/comments | https://api.github.com/repos/huggingface/transformers/issues/10306/events | https://github.com/huggingface/transformers/issues/10306 | 812,684,885 | MDU6SXNzdWU4MTI2ODQ4ODU= | 10,306 | Issue Loading bert-based-german-cased | {
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"Which code caused this error?",
"This issue comes from the hosted API https://huggingface.co/bert-base-german-cased?text=Ich+bin+%5BMASK%5D",
"@tholor The url above currently loads for me, but to be future-proof should we cp the files currently loaded from that S3 bucket to the corresponding model repo (here, ... | 1,613 | 1,614 | 1,614 | NONE | null | Message on the website is:
Can't load tokenizer using from_pretrained, please update its configuration: 400 Client Error: Bad Request for url: https://int-deepset-models-bert.s3.eu-central-1.amazonaws.com/pytorch/bert-base-german-cased-vocab.txt
| {
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https://api.github.com/repos/huggingface/transformers/issues/10305 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10305/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10305/comments | https://api.github.com/repos/huggingface/transformers/issues/10305/events | https://github.com/huggingface/transformers/issues/10305 | 812,671,303 | MDU6SXNzdWU4MTI2NzEzMDM= | 10,305 | Documentation of the decode method is missing | {
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"This has been fixed a few days ago, I believe. Look at the [master doc tokenizer page](https://huggingface.co/transformers/master/main_classes/tokenizer.html) (the stable documentation is only updated at each release).",
"Yes, you are right."
] | 1,613 | 1,613 | 1,613 | CONTRIBUTOR | null | The tokenizer documentation [page](https://huggingface.co/transformers/main_classes/tokenizer.html) is generated from the following files:
- tokenization_utils_base.py
- tokenization_utils_fast.py
- tokenization_utils.py
At least the documentation of the decode method is missing even if it is properly doc... | {
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https://api.github.com/repos/huggingface/transformers/issues/10304 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10304/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10304/comments | https://api.github.com/repos/huggingface/transformers/issues/10304/events | https://github.com/huggingface/transformers/pull/10304 | 812,668,607 | MDExOlB1bGxSZXF1ZXN0NTc2OTc5MTcw | 10,304 | fixes #10303 | {
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"Thanks for fixing!"
] | 1,613 | 1,613 | 1,613 | CONTRIBUTOR | null | # What does this PR do?
Fixes #10303
## Before submitting
- [X] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [X] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md#start-contributing-pull-reque... | {
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https://api.github.com/repos/huggingface/transformers/issues/10303 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10303/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10303/comments | https://api.github.com/repos/huggingface/transformers/issues/10303/events | https://github.com/huggingface/transformers/issues/10303 | 812,665,794 | MDU6SXNzdWU4MTI2NjU3OTQ= | 10,303 | convert_tokens_to_string documentation bug | {
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That is actually not correct as it converts a sequence of tokens. The method... | {
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https://api.github.com/repos/huggingface/transformers/issues/10302 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10302/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10302/comments | https://api.github.com/repos/huggingface/transformers/issues/10302/events | https://github.com/huggingface/transformers/issues/10302 | 812,650,571 | MDU6SXNzdWU4MTI2NTA1NzE= | 10,302 | Tensorflow not found but i can import it | {
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"What is the output of:\r\n```\r\nimport tensorflow\r\nprint(tensorflow.__version__)\r\n```\r\n?",
"> What is the output of:\r\n> \r\n> ```\r\n> import tensorflow\r\n> print(tensorflow.__version__)\r\n> ```\r\n> \r\n> ?\r\n\r\n'2.4.0-rc0'",
"Hello!\r\n\r\nWe currently don't support other implementations than th... | 1,613 | 1,619 | 1,619 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.4.0.dev0
- Platform: macOS-11.2.1-arm64-arm-64bit
- Python version: 3.8.6
- PyTorch version (GPU?): not in... | {
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https://api.github.com/repos/huggingface/transformers/issues/10301 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10301/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10301/comments | https://api.github.com/repos/huggingface/transformers/issues/10301/events | https://github.com/huggingface/transformers/pull/10301 | 812,641,342 | MDExOlB1bGxSZXF1ZXN0NTc2OTU5MDY2 | 10,301 | [WIP] Add Megatron-11B | {
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"That's very neat, @anton-l! thank you for the port\r\n\r\nYou demonstrated a very good creativity by finding a way to recompose the model shards!\r\n\r\n> This one will probably be fun to test with DeepSpeed, as @stas00 mentioned it's referenced a lot in its docs \r\n\r\nAs you correctly noticed studying Megatron-... | 1,613 | 1,648 | 1,648 | MEMBER | null | # What does this PR do?
Fixes #9560
This PR introduces the Megatron model as described in https://github.com/pytorch/fairseq/blob/master/examples/megatron_11b/README.md
This one will probably be fun to test with DeepSpeed, as @stas00 mentioned it's referenced a lot in its docs :smile:
It's important to menti... | {
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https://api.github.com/repos/huggingface/transformers/issues/10300 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10300/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10300/comments | https://api.github.com/repos/huggingface/transformers/issues/10300/events | https://github.com/huggingface/transformers/issues/10300 | 812,636,157 | MDU6SXNzdWU4MTI2MzYxNTc= | 10,300 | unexpected keyword argument 'forced_bos_token_id' when using mbart-large-50-many-to-many-mmt | {
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"hi @IamAdiSri \r\n\r\nWhat is your Transformers version ? mBART-50 currently only works on master.",
"@patil-suraj I'm on version 4.3.2, but I tried it with the modules in master branch. I searched through the repository but as far as I can tell, none of the relevant mbart modules take `forced_bos_token_id` as ... | 1,613 | 1,614 | 1,614 | NONE | null | When I try to run the example on the model card, I get this error;
```
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-9-88d049aaf9c0> in <module>
5 tokenizer.src_lang = "hi_IN"
6 e... | {
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https://api.github.com/repos/huggingface/transformers/issues/10299 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10299/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10299/comments | https://api.github.com/repos/huggingface/transformers/issues/10299/events | https://github.com/huggingface/transformers/issues/10299 | 812,609,813 | MDU6SXNzdWU4MTI2MDk4MTM= | 10,299 | Object of type 'int64' is not JSON serializable in Trainer.save_checkpoint | {
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"I too ran into this problem and its caused by turning on evaluation strategy which then adds metrics in the log_history of the models state, which is using numpy data types and causes the JSON encoder issue. That was the case with 4.3.3. There appear to be a bunch of changes in the trainer in the works, whether th... | 1,613 | 1,615 | 1,615 | NONE | null | I am using the recent run_ner.py example script to train an NER model. I want to evaluate the performance of the model during training and use the following command for training:
```
python3 run_ner.py
--model_name_or_path bert-base-uncased ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10298 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10298/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10298/comments | https://api.github.com/repos/huggingface/transformers/issues/10298/events | https://github.com/huggingface/transformers/issues/10298 | 812,564,384 | MDU6SXNzdWU4MTI1NjQzODQ= | 10,298 | Converting fairseq NMT to transformers misses model weight | {
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"Pinging @stas00 here",
"Thank you for the ping, @NielsRogge \r\n\r\n@tagucci, when you file an issue you will find a list of who to tag for what topic, so please use it to tag the right people. Otherwise it's hard for everybody to try to follow all issues.\r\n\r\nalso when you link to a line of code in github, a... | 1,613 | 1,614 | 1,614 | CONTRIBUTOR | null | Hi there, question about fairseq NMT model ([FSMT](https://huggingface.co/transformers/model_doc/fsmt.html)) conversion.
I tried to convert my own fairseq-nmt model ([`transformer_wmt_en_de`](https://github.com/pytorch/fairseq/blob/master/fairseq/models/transformer.py#L1046)) based on [this conversion script](https:... | {
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"Hello! Thank you for opening an issue with a reproducible example, it helps a lot.\r\n\r\nThe issue here is that you're using the `encode` method to encode a batch, which it can't do. Encode only encodes single sequences, and can accept a \"batch\" of two because it processes them as two independent sequences that... | 1,613 | 1,617 | 1,614 | 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: 4.3.2
- Platform: Arch Linux
- Python version: 3.9.1
- PyTorch version (GPU?): 1.7.1, no
- Tensorflow vers... | {
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https://api.github.com/repos/huggingface/transformers/issues/10296 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10296/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10296/comments | https://api.github.com/repos/huggingface/transformers/issues/10296/events | https://github.com/huggingface/transformers/issues/10296 | 812,510,410 | MDU6SXNzdWU4MTI1MTA0MTA= | 10,296 | [predict] AttributeError: 'Seq2SeqTrainer' object has no attribute 'metrics_format' | {
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"`metrics_format` was recently introduced on master, you should update the transformers version to master.",
"Thanks! I'll try it again!"
] | 1,613 | 1,614 | 1,614 | NONE | null | Hi everybody
When using mbart for machine translation prediction, i got:
Traceback (most recent call last):
File "/Users/lishuqi/Desktop/WAT2021/transformers-master/examples/seq2seq/run_seq2seq.py", line 667, in <module>
main()
File "/Users/lishuqi/Desktop/WAT2021/transformers-master/examples/seq2seq/r... | {
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https://api.github.com/repos/huggingface/transformers/issues/10295 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10295/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10295/comments | https://api.github.com/repos/huggingface/transformers/issues/10295/events | https://github.com/huggingface/transformers/pull/10295 | 812,507,839 | MDExOlB1bGxSZXF1ZXN0NTc2ODYxMzQ4 | 10,295 | [examples/seq2seq] defensive programming + expand/correct README | {
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This PR:
`run_seq2seq.py`:
* checks for invalid column names
`README.md`:
* largely expands the document explaining and exemplifying the supported formats
* documents the nuances of t5 and mbart translation - I hope we fix this on t... | {
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"Hey @Mehrad0711,\r\n\r\nThanks a lot for the very clean & easy to understand issue!\r\nI can reproduce the error and would be super happy about a PR to fix it! Your fix to let the context manager handle the `spm_target` sounds like the correct solution to me!",
"Hi @patrickvonplaten!\r\nThank you for your feedba... | 1,613 | 1,615 | 1,615 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Marian
Language I am using the model on (English, Chinese ...): English, German
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
The tasks I am working ... | {
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"Ah indeed, that's a good request ! There's no reason, we could definitely raise a warning when loading the weights by checking the model type in the configuration against the arch's model type. Do you want to open a PR?",
"Why a warning and not an assert? If the code throws a totally unrelated long backtrace how... | 1,613 | 1,616 | 1,616 | CONTRIBUTOR | null | While comparing different models trained on xsum (most of which are Bart) I made a mistake and passed "google/pegasus-xsum" to `BartForConditionalGeneration`
```
BartForConditionalGeneration.from_pretrained("google/pegasus-xsum")
```
I got:
```
Some weights of the model checkpoint at google/pegasus-xsum w... | {
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"#10287 contains the fix.",
"Confirmed that it works, albeit the cl args changed so tested with:\r\n```\r\nPYTHONPATH=src python examples/seq2seq/run_translation.py --model_name_or_path facebook/mbart-large-en-ro --do_train --do_eval --dataset_name wmt16 --dataset_config_name ro-en --o... | 1,613 | 1,615 | 1,615 | CONTRIBUTOR | null | After this PR https://github.com/huggingface/transformers/pull/10205 This is still broken for other models:
```
python examples/seq2seq/run_seq2seq.py --model_name_or_path facebook/mbart-large-en-ro --do_train --do_eval --task translation_en_to_ro --dataset_name wmt16 --dataset_config_name ... | {
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This PR fixes (and adds or removes) the links shown in the task summary.
Fixes #10288 | {
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"Indeed, I can see the problem. I'm not sure there is an easy fix however and I don't have time right now to build a proper callback checkpointing system. Will have to wait a little bit to be fixed!",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this stil... | 1,613 | 1,705 | 1,619 | 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! -->
When continuing training from checkpoint, Trainer does not check if the checkpoint terminated with an `self.control.should_training_stop ==... | {
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"Hey @xxbidiao, \r\n\r\nFor batched generation GPT2 has to be used in quite a special way... -> could you check out [this](https://discuss.huggingface.co/t/batch-generation-with-gpt2/1517/2) forum post to see whether this makes sense for you?",
"```\r\nimport torch,transformers\r\ngpt2_model = transformers.GPT2LM... | 1,613 | 1,619 | 1,619 | CONTRIBUTOR | null | Is this intended behavior, that padding a sentence and attention_mask it will not give the exact same generation result comparing to the same sentence unpadded?
Edit: [This notebook](https://colab.research.google.com/drive/1oyFRFigtSNUYwKO1EQPRHfEqke0-F6_N?usp=sharing) demonstrates this, with the newest version avai... | {
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"Thanks for flagging! Those have not been updated in a while so I made a pass over that file.",
"I still see the bad links. Is the change getting pushed/merged later?",
"It will only be seen in the [master documentation](https://huggingface.co/transformers/master/) for now. At the next release, it will become ... | 1,613 | 1,613 | 1,613 | NONE | null | ## Minor issue in the Fine tuning docs
In the "Named Entity Recognition" section of the "Summary of tasks" documentation page there are some bad links.
Here is a link to the section: https://huggingface.co/transformers/task_summary.html#named-entity-recognition
The text in question is:
##Named Entity Recognition
... | {
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https://api.github.com/repos/huggingface/transformers/issues/10287 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10287/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10287/comments | https://api.github.com/repos/huggingface/transformers/issues/10287/events | https://github.com/huggingface/transformers/pull/10287 | 812,324,206 | MDExOlB1bGxSZXF1ZXN0NTc2NzA5MDg3 | 10,287 | Deprecate prepare_seq2seq_batch | {
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"Hi all! Sorry, but this seems to be cleaner: (Some feature request: #14255)\r\n```python\r\nencoded_train_dataset = train_dataset.map(\r\n lambda batch: tokenizer.prepare_seq2seq_batch(\r\n batch['text'], batch['summary'], padding='max_length', truncation=True, max_length=256, max_target_length=64\r\n ... | 1,613 | 1,635 | 1,614 | COLLABORATOR | null | # What does this PR do?
This PR officially deprecates `prepare_seq2seq_batch` to prepare its removal in Transformers v5. As discussed before, the proper way to prepare data for sequence-to-sequence tasks is to:
- call the tokenizer on the inputs
- call the tokenizers on the targets inside the context manager `as_t... | {
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https://api.github.com/repos/huggingface/transformers/issues/10286 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10286/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10286/comments | https://api.github.com/repos/huggingface/transformers/issues/10286/events | https://github.com/huggingface/transformers/pull/10286 | 812,315,025 | MDExOlB1bGxSZXF1ZXN0NTc2NzAwNjY5 | 10,286 | Introduce save_strategy training argument | {
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"Hi @sgugger, \r\nGot some time to raise the changes we talked about in [my previous PR](https://github.com/huggingface/transformers/pull/10267). \r\nDo let me know if I missed something. \r\nThanks!",
"Hi @LysandreJik / @sgugger,\r\n\r\nThanks for your inputs! I can think of some better names, _but before tha... | 1,613 | 1,614 | 1,614 | CONTRIBUTOR | null | * Introduce save_strategy training argument
* collapse EvaluationStrategy and LoggingStrategy into a single TimeStrategy enum
* modify tests to use modified enum
# What does this PR do?
1. Introduce new `save_strategy` argument to decide on interval between 2 model saves during training.
2. Introduce a unified... | {
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"Nevermind, didn't see the not for replaced indices so it's 50% of the remaining 20% after masking"
] | 1,613 | 1,613 | 1,613 | NONE | null | Hi,
It appears that the token masking function replaces tokens with random words 50% of the time instead of the commented 10%.
https://github.com/huggingface/transformers/blob/709c86b5a925f1efe650e24ee8b1f52bdc5a3acb/src/transformers/data/data_collator.py#L381 | {
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https://api.github.com/repos/huggingface/transformers/issues/10284 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10284/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10284/comments | https://api.github.com/repos/huggingface/transformers/issues/10284/events | https://github.com/huggingface/transformers/pull/10284 | 812,264,600 | MDExOlB1bGxSZXF1ZXN0NTc2NjU3OTE0 | 10,284 | Patch zero shot distillation script cuda issue | {
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https://api.github.com/repos/huggingface/transformers/issues/10283 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10283/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10283/comments | https://api.github.com/repos/huggingface/transformers/issues/10283/events | https://github.com/huggingface/transformers/pull/10283 | 812,244,065 | MDExOlB1bGxSZXF1ZXN0NTc2NjQwODQ5 | 10,283 | Clean TF BART and TF Seq2Ses template | {
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... | [] | closed | false | null | [] | [] | 1,613 | 1,614 | 1,614 | CONTRIBUTOR | null | # What does this PR do?
This PR aims to clean TF BART and the TF Seq2Seq template by adding explicit keyword arguments, typing and update the documentation in the model implementation to make it easier to understand and read.
| {
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https://api.github.com/repos/huggingface/transformers/issues/10282 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10282/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10282/comments | https://api.github.com/repos/huggingface/transformers/issues/10282/events | https://github.com/huggingface/transformers/issues/10282 | 812,236,535 | MDU6SXNzdWU4MTIyMzY1MzU= | 10,282 | [tests] tests/test_trainer_distributed.py intermittent failure | {
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"One other solution - since this is a single node we could use a unique file rather than port for setting up the distributed process group.\r\n\r\nThat is `init_process_group()` with `init_method=\"file:///tmp/unique_file\"` - but the trainer currently hardcodes the `env://` method so we may need to make it more fl... | 1,613 | 1,616 | 1,616 | CONTRIBUTOR | null | `tests/test_trainer_distributed.py` fails occasionally on multi-gpu github runner CI and as a result doesn't free up the 29500 default distributed port.
This could be caused by an occasional deadlock discusses in testing_utils.py's `_stream_subprocess``. When debugging one such zombie it was stuck in `exec(eval(sy... | {
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https://api.github.com/repos/huggingface/transformers/issues/10281 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10281/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10281/comments | https://api.github.com/repos/huggingface/transformers/issues/10281/events | https://github.com/huggingface/transformers/pull/10281 | 812,198,366 | MDExOlB1bGxSZXF1ZXN0NTc2NjAyODYx | 10,281 | [CI] Kill any run-away pytest processes | {
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@LysandreJik | {
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https://api.github.com/repos/huggingface/transformers/issues/10280 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10280/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10280/comments | https://api.github.com/repos/huggingface/transformers/issues/10280/events | https://github.com/huggingface/transformers/issues/10280 | 812,134,417 | MDU6SXNzdWU4MTIxMzQ0MTc= | 10,280 | Trainer.train argument resume_from_last_checkpoint | {
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"Instead of adding a new argument, I would use the existing `resume_from_checkpoint` and change its type to bool or str/PathLike. If it's a bool and if it's `True`, we then use `get_last_checkpoint` to get the last checkpoint in `args.output_dir`. Does that sound good to you?",
"Yes, SGTM. I have raised [a PR](ht... | 1,613 | 1,665 | 1,614 | CONTRIBUTOR | 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. -->
`Trainer.train` accepts `resume_from_checkpoint` argument, which requires the user to explicitly provide the checkpoint location to continue training from.
`r... | {
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https://api.github.com/repos/huggingface/transformers/issues/10279 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10279/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10279/comments | https://api.github.com/repos/huggingface/transformers/issues/10279/events | https://github.com/huggingface/transformers/issues/10279 | 812,133,918 | MDU6SXNzdWU4MTIxMzM5MTg= | 10,279 | Performance of mbart-large-50-many-to-many-mmt on de/fr/it | {
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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)... | 1,613 | 1,621 | 1,621 | MEMBER | null | Hi everybody
I am using ` mbart-large-50-many-to-many-mmt` and I am running into the following problem.
## 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... | {
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https://api.github.com/repos/huggingface/transformers/issues/10278 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10278/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10278/comments | https://api.github.com/repos/huggingface/transformers/issues/10278/events | https://github.com/huggingface/transformers/issues/10278 | 812,102,166 | MDU6SXNzdWU4MTIxMDIxNjY= | 10,278 | Improving training time for Marian MT model with the Trainer | {
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"+1 I found the same problem. The bottleneck seems to be huggingface/datasets. Hence I switched back to use the old customized dataset, which was way more faster.",
"Hi ! There's currently an issue in huggingface/datasets that makes iterating through the dataset slow if your dataset is big.\r\nWe're working on a ... | 1,613 | 1,627 | 1,619 | NONE | null | ## Environment info
- Platform: Linux-4.19.0-14-cloud-amd64-x86_64-with-debian-10.7
- Python version: 3.7.9
- PyTorch version (GPU): 1.7.1
- Using GPU in script?: Yes (2 Tesla V100 GPUs with 16160MiB memory)
- CUDA Version: 11.0
- transformers: 4.3.2
- datasets: 1.3.0
### Who can help
@lhoestq @sgugger @ssh... | {
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https://api.github.com/repos/huggingface/transformers/issues/10277 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10277/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10277/comments | https://api.github.com/repos/huggingface/transformers/issues/10277/events | https://github.com/huggingface/transformers/issues/10277 | 812,082,080 | MDU6SXNzdWU4MTIwODIwODA= | 10,277 | ImportError: cannot import name 'pipeline' from 'transformers' (unknown location) | {
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"I'm on MacOS btw.",
"Possibly duplicate of https://github.com/huggingface/transformers/issues/9939",
"> Possibly duplicate of https://github.com/huggingface/transformers/issues/9939\n\nI have installed TF 2.0 right at the start. Is there a version to update to resolve this error?",
"So after install TF 2.0 w... | 1,613 | 1,674 | 1,613 | NONE | null | Hi, I created an env with conda, installed TF, then installed PyTorch, then "pip install git+https://github.com/huggingface/transformers", but when I ran 'python -c "from transformers import pipeline; print(pipeline('sentiment-analysis')('I hate you'))"', it gave me the ImportError. How can I resolve this? | {
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https://api.github.com/repos/huggingface/transformers/issues/10276 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10276/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10276/comments | https://api.github.com/repos/huggingface/transformers/issues/10276/events | https://github.com/huggingface/transformers/pull/10276 | 812,024,747 | MDExOlB1bGxSZXF1ZXN0NTc2NDU5MjQ3 | 10,276 | Move the TF NER example | {
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"Nice! What means \"same way of training\", same way than what?",
"Same way as the current `run_ner` script."
] | 1,613 | 1,614 | 1,613 | CONTRIBUTOR | null | # What does this PR do?
This PR moves the `run_tf_ner.py` example into the legacy folder because it uses the "legacy" way to train a model with the `utils_ner.py` file.
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https://api.github.com/repos/huggingface/transformers/issues/10275 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10275/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10275/comments | https://api.github.com/repos/huggingface/transformers/issues/10275/events | https://github.com/huggingface/transformers/pull/10275 | 812,003,724 | MDExOlB1bGxSZXF1ZXN0NTc2NDQxNTQx | 10,275 | Fix squad processor for TF | {
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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)... | 1,613 | 1,686 | 1,619 | CONTRIBUTOR | null | # What does this PR do?
This PR fixes the Squad processor that prepares and creates a `tf.data.dataset` to be able to be used in the `TFTrainer` through the `run_tf_squad.py` example script.
There were two issues:
1. The `token_type_ids` was forced to be `True` in the tokenizer output even if this argument was... | {
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https://api.github.com/repos/huggingface/transformers/issues/10274 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10274/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10274/comments | https://api.github.com/repos/huggingface/transformers/issues/10274/events | https://github.com/huggingface/transformers/pull/10274 | 811,915,965 | MDExOlB1bGxSZXF1ZXN0NTc2MzY4MTA1 | 10,274 | Rework the AMP for TF XLNet | {
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"Yes, `bfloat16` is only for TPU. Hence, we cannot really test it elsewhere than inside a TPU context. I have added the `bfloat16` condition only if XLNet is run on TPU because we were handling a specific case when the model is run under AMP."
] | 1,613 | 1,614 | 1,614 | CONTRIBUTOR | null | # What does this PR do?
This PR reworks the AMP of XLNet to remove some useless casts for better and less confusing AMP compliancy. | {
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https://api.github.com/repos/huggingface/transformers/issues/10273 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10273/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10273/comments | https://api.github.com/repos/huggingface/transformers/issues/10273/events | https://github.com/huggingface/transformers/issues/10273 | 811,721,478 | MDU6SXNzdWU4MTE3MjE0Nzg= | 10,273 | ElectraForQuestionAnswering with SQuADHead | {
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"Hello! We would welcome a PR that offers this. Maybe instead of renaming the current QA model to `Simple` (which would break backwards-compatibility), we could add a new model called `ElectraForQuestionAnsweringBeamSearch`? What do you think?",
"Agreed. We should use a new name for the model for backward-compati... | 1,613 | 1,619 | 1,619 | NONE | null | # 🚀 Feature request
<!-- -->
Implement ElectraForQuestionAnswering as described in the paper. https://arxiv.org/abs/2003.10555
## Motivation
<!-- -->
In the original implementation, the authors use question answering module from XLNet rather than simple linear layer. There is a huge gap of performance between... | {
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https://api.github.com/repos/huggingface/transformers/issues/10272 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10272/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10272/comments | https://api.github.com/repos/huggingface/transformers/issues/10272/events | https://github.com/huggingface/transformers/issues/10272 | 811,715,503 | MDU6SXNzdWU4MTE3MTU1MDM= | 10,272 | Summarization of long text with T5 seems to output random memory content | {
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"Hey @db1981,\r\n\r\ncould you please post a fully reproducible code snippet in the following format:\r\n\r\n```python\r\nfrom transformers import T5ForConditionalGeneration\r\n\r\nmodel = T5ForConditionalGeneration.from_pretrained(\"...\")\r\n\r\n...\r\n```\r\n\r\nso that we can help you better?",
"Hi @patrickvo... | 1,613 | 1,619 | 1,619 | NONE | null | Hello everyone,
I'm trying to summarizing a long text (~1800 words) using the T5 model. I set the max-length and min_length parameters as well, and when I do so, the output seems to contain random memory content...
Here my code:
#len_text=1755
inputs = tokenizer.encode("summarize: " + proc_text, return_tens... | {
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https://api.github.com/repos/huggingface/transformers/issues/10271 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10271/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10271/comments | https://api.github.com/repos/huggingface/transformers/issues/10271/events | https://github.com/huggingface/transformers/pull/10271 | 811,551,271 | MDExOlB1bGxSZXF1ZXN0NTc2MDYzNzI3 | 10,271 | [test] fix func signature | {
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@sgugger | {
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https://api.github.com/repos/huggingface/transformers/issues/10270 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10270/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10270/comments | https://api.github.com/repos/huggingface/transformers/issues/10270/events | https://github.com/huggingface/transformers/pull/10270 | 811,545,519 | MDExOlB1bGxSZXF1ZXN0NTc2MDU4OTA1 | 10,270 | [ISSUES.md] propose using google colab to reproduce problems | {
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This PR adds this suggestion to the existing how-to list.
@sgugger, @LysandreJik | {
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"Hi Colin. I ran into this same issue when I switched over to using the datasets library to load my poetry corpus, where line breaks are super important. \r\n\r\nI ended up making a slightly modified version of the built-in [text](https://github.com/huggingface/datasets/blob/master/src/datasets/packaged_modules/tex... | 1,613 | 1,614 | 1,614 | NONE | null | The legacy run_language_modeling.py script produced output that respected line breaks in the train_data_file. The updated run_clm.py script does not. I imagine this is likely due to how the dataset is processed in the new script, but if it is, how do I intervene and fix it?
## Environment info
- general environme... | {
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https://api.github.com/repos/huggingface/transformers/issues/10268 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10268/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10268/comments | https://api.github.com/repos/huggingface/transformers/issues/10268/events | https://github.com/huggingface/transformers/pull/10268 | 811,465,551 | MDExOlB1bGxSZXF1ZXN0NTc1OTg5MDQ5 | 10,268 | [trainer] implement support for full fp16 in evaluation/predict | {
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https://api.github.com/repos/huggingface/transformers/issues/10267 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10267/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10267/comments | https://api.github.com/repos/huggingface/transformers/issues/10267/events | https://github.com/huggingface/transformers/pull/10267 | 811,426,635 | MDExOlB1bGxSZXF1ZXN0NTc1OTU2NDM4 | 10,267 | Introduce logging_strategy training argument | {
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"Currently WIP. \r\nThanks!",
"Thanks, yes that worked out! \r\nIMO, defaulting `eval_steps` to `logging_steps` is not a good decision any longer. \r\nWith `logging_strategy` introduced, it seems more intuitive to decouple both. In case user chooses `logging_strategy=\"epoch\"`, `logging_steps` is no longer a ... | 1,613 | 1,613 | 1,613 | CONTRIBUTOR | null | Introduce logging_strategy training argument
in TrainingArguments and TFTrainingArguments. (#9838)
# 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 ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10266 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10266/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10266/comments | https://api.github.com/repos/huggingface/transformers/issues/10266/events | https://github.com/huggingface/transformers/pull/10266 | 811,410,806 | MDExOlB1bGxSZXF1ZXN0NTc1OTQzMjQ3 | 10,266 | [trainer] add Trainer methods for metrics logging and saving | {
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"@sgugger, are you ok if we merge this and I will ask Second Good Issue to help with this - I'm not sure I will have time to do this and test all the scripts in the coming days, and since you guys discuss changing this script again, we should probably merge this first.",
"I'm fine with that!",
"Started an issue... | 1,613 | 1,614 | 1,614 | CONTRIBUTOR | null | This PR introduces:
* [x] `trainer.log_metrics` - to perform consistent formatting for logged metrics
* [x] `trainer.save_metrics` - to save the metrics
This removes a lot of pointless noise from the example scripts and makes them much easier to read and understand. It doesn't take away from a user understanding t... | {
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https://api.github.com/repos/huggingface/transformers/issues/10265 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10265/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10265/comments | https://api.github.com/repos/huggingface/transformers/issues/10265/events | https://github.com/huggingface/transformers/issues/10265 | 811,280,768 | MDU6SXNzdWU4MTEyODA3Njg= | 10,265 | Tapas Tokenizer makes DataFrame iterrows() iterator crazy ... | {
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"Hi,\r\n\r\nCan you provide the table on which you tried this?\r\n\r\nTo add numeric value information to the table, each cell in the table is replaced by a `Cell` object. A `Cell` object has 2 attributes: `text` (the original string corresponding to the cell value) and an optional `numeric_value` (which can be a `... | 1,613 | 1,619 | 1,619 | NONE | null | ## Environment info
- `transformers` version: 4.3.2
- Platform: Colab Pro
- Python version: Python 3.6.9
- PyTorch version (GPU?): 1.7.0+cu101 torch-scatter 2.0.5
- Tensorflow version (GPU?): 2.4.1
- Using GPU in script?: Tesla P100
- Using distributed or parallel set-up in script?: no
### ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10264 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10264/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10264/comments | https://api.github.com/repos/huggingface/transformers/issues/10264/events | https://github.com/huggingface/transformers/pull/10264 | 811,237,394 | MDExOlB1bGxSZXF1ZXN0NTc1Nzk4Mzcw | 10,264 | Making TF TransfoXL model compliant with AMP | {
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This PR makes the TF TransfoXL model compliant with AMP. All the slow tests are passing as well for these models.
These two models cannot be XLA compliant for now, as it seems that tf.where cannot be used in XLA if the x and y parameters are None. See the _get_global_attn_indices method wh... | {
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"Hello @joshdevins! Indeed, this is a valid issue. The current pipeline outputs tokens that were attributed a class, but ignores the following tokens. For models that were trained with labels on all subwords this works, but using a padded sub-word label like you've done yields unsatisfactory results.\r\n\r\nI think... | 1,613 | 1,621 | 1,621 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 4.3.1
- Platform: Darwin-19.6.0-x86_64-i386-64bit
- Python version: 3.7.7
- PyTorch version (GPU?): 1.7.1 (False)
- Tensorflow version (GPU?): not installed (NA)
- 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/10262 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10262/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10262/comments | https://api.github.com/repos/huggingface/transformers/issues/10262/events | https://github.com/huggingface/transformers/pull/10262 | 811,189,257 | MDExOlB1bGxSZXF1ZXN0NTc1NzU3NDY2 | 10,262 | Making TF T5 model compliant with AMP and XLA | {
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This PR makes the TF T5 model compliant with AMP and XLA. All the slow tests are passing as well for the model. | {
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This PR makes the TF OpenAI GPT model compliant with AMP and XLA. All the slow tests are passing as well for the model. | {
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https://api.github.com/repos/huggingface/transformers/issues/10260 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10260/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10260/comments | https://api.github.com/repos/huggingface/transformers/issues/10260/events | https://github.com/huggingface/transformers/pull/10260 | 811,101,145 | MDExOlB1bGxSZXF1ZXN0NTc1NjgzODAz | 10,260 | Making TF MPNet model compliant with XLA | {
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This PR makes the TF MPNet model compliant with XLA. All the slow tests are passing as well for the model.
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This PR makes the TF MobileBert model compliant with AMP. All the slow tests are passing as well for the model.
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https://api.github.com/repos/huggingface/transformers/issues/10258 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10258/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10258/comments | https://api.github.com/repos/huggingface/transformers/issues/10258/events | https://github.com/huggingface/transformers/issues/10258 | 811,046,305 | MDU6SXNzdWU4MTEwNDYzMDU= | 10,258 | Deberta Tokenizer convert_ids_to_tokens() is not giving expected results | {
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"It seems expected behavior but something is still not right with this tokenizer",
"Seems like they have not implemented a decoder for the tokenizer. I will have a look at it.",
"It might be expected behaviour because it is based on GPT2 tokenizer and it is also having similar results\r\n",
"That is not true:... | 1,613 | 1,617 | 1,617 | 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: 4.3.0
- Platform: Colab
- Python version: 3.9
- PyTorch version (GPU?): No
- Tensorflow version (GPU?): No
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https://api.github.com/repos/huggingface/transformers/issues/10257 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10257/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10257/comments | https://api.github.com/repos/huggingface/transformers/issues/10257/events | https://github.com/huggingface/transformers/pull/10257 | 811,039,610 | MDExOlB1bGxSZXF1ZXN0NTc1NjMxMzE1 | 10,257 | Making TF Lxmert model compliant with AMP | {
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This PR makes the TF Lxmert model compliant with AMP. All the slow tests are passing as well for the model. | {
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https://api.github.com/repos/huggingface/transformers/issues/10256 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10256/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10256/comments | https://api.github.com/repos/huggingface/transformers/issues/10256/events | https://github.com/huggingface/transformers/issues/10256 | 810,994,180 | MDU6SXNzdWU4MTA5OTQxODA= | 10,256 | [Question]: Register new Tokenizer | {
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"Hi! `AutoTokenizer` is only used to redirect to the correct tokenizer implementation under the hood, and not to resolve to any tokenizer object. The procedure here would be to create your tokenizer like you want it to be, either by using the `tokenizers` library, by tweaking an existing one or by creating yours fr... | 1,613 | 1,631 | 1,619 | CONTRIBUTOR | null | Hi there,
I'm in the process of creating a new Transformer model. I have my own codebase and I'm using Transformers as an external library. If I implement a new Tokenizer that inherits from an existing one (say the BERT one) is there any way to "register" my new tokenizer so that Huggingface automatically instantiat... | {
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"Thanks for your PR! We don't want to switch the examples to use on-the-fly tokenization however as in most cases it's actually faster to do it once and for all. Having to do it on-the-fly for a training with huge data is more of a specific use-case. Your PR can be referenced as an example of how to do it in practi... | 1,613 | 1,613 | 1,613 | NONE | null | # What does this PR do?
<!--
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/10254 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10254/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10254/comments | https://api.github.com/repos/huggingface/transformers/issues/10254/events | https://github.com/huggingface/transformers/issues/10254 | 810,856,096 | MDU6SXNzdWU4MTA4NTYwOTY= | 10,254 | ImportError: cannot import name 'MBart50TokenizerFast' from 'transformers' (unknown location) | {
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"Hi @loretoparisi \r\n\r\nDid you install sentencepiece ? The tokenizer needs sentencepiece",
"@patil-suraj thanks I did right now\r\n\r\n```\r\nroot@d2f0e8a5ec76:/app# pip install sentencepiece\r\nCollecting sentencepiece\r\n Downloading https://files.pythonhosted.org/packages/f5/99/e0808cb947ba10f575839c43e8fa... | 1,613 | 1,614 | 1,614 | 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: 4.3.2
- Platform: Linux-4.19.121-linuxkit-x86_64-with-debian-10.1
- Python version: 3.7.4
- PyTorch version ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10253 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10253/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10253/comments | https://api.github.com/repos/huggingface/transformers/issues/10253/events | https://github.com/huggingface/transformers/issues/10253 | 810,691,443 | MDU6SXNzdWU4MTA2OTE0NDM= | 10,253 | Load custom models | {
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"Hello! Could you provide a reproducible code example, for example the extended custom model you created, so that we can take a look?\r\n\r\nAlso, can you let us know what's in the `./SqueezeBert/results/best_checkpoint/` directory? It's trying to look for a configuration file there but it doesn't find it.",
"Tha... | 1,613 | 1,613 | 1,613 | 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: 4.3.2
- Platform: RHEL 7
- Python version: 3.7
- PyTorch version (GPU?): 1.7.0 (GPU)
- Tensorflow version (... | {
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https://api.github.com/repos/huggingface/transformers/issues/10252 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10252/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10252/comments | https://api.github.com/repos/huggingface/transformers/issues/10252/events | https://github.com/huggingface/transformers/issues/10252 | 810,610,888 | MDU6SXNzdWU4MTA2MTA4ODg= | 10,252 | microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract not available for tensorflow | {
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"Hello!\r\n\r\nYou can load PyTorch weights into Tensorflow with `TFBertModel.from_pretrained(\"microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract\", from_pt=True)`",
"That works, thanks!"
] | 1,613 | 1,613 | 1,613 | NONE | null | @jplu
The above said model is available for pytorch but not for tensorflow. How to convert a pytorch checkpoint to tensorflow for this one? Is it possible for doing a contribution for the same?
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https://api.github.com/repos/huggingface/transformers/issues/10251 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10251/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10251/comments | https://api.github.com/repos/huggingface/transformers/issues/10251/events | https://github.com/huggingface/transformers/pull/10251 | 810,605,926 | MDExOlB1bGxSZXF1ZXN0NTc1MjY4OTY1 | 10,251 | [ci] scheduled job test | {
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"well, the job never finished, something or something aborted the workflow - so the test wasn't complete.",
"The test was probably too long (>6 hours) and was stopped by CircleCI. This PR that was just merged should help in that regard: https://github.com/huggingface/transformers/pull/10152",
"That PR won't hel... | 1,613 | 1,613 | 1,613 | CONTRIBUTOR | null | please ignore
this time a branch on huggingface and not a fork | {
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testing only SLOW pt job | {
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- fixes invalid port
- adds missing requirements install which lead to multiple test failures
@LysandreJik
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https://api.github.com/repos/huggingface/transformers/issues/10247 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10247/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10247/comments | https://api.github.com/repos/huggingface/transformers/issues/10247/events | https://github.com/huggingface/transformers/issues/10247 | 810,559,530 | MDU6SXNzdWU4MTA1NTk1MzA= | 10,247 | [BUG] [Ray-Tune] ValueError: checkpoint not in list | {
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"@neel04 can you try a few things:\r\n- What version of Ray are you using? Can you try with the latest Ray (1.2).\r\n- When using the PBT scheduler, it's actually not compatible with Tune search algorithms (see the compatibility matrix here https://docs.ray.io/en/master/tune/api_docs/schedulers.html#summary). Can y... | 1,613 | 1,625 | 1,613 | NONE | null | ## Environment info
- `transformers` version: 4.4.0.dev0
- Platform: Linux-4.19.112+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.9
- PyTorch version (GPU?): 1.7.0+cu101 (True)
- Tensorflow version (GPU?): 2.4.1 (True)
- Using GPU in script?: Yes
### Who can help
Models:
- tensorflow: @jplu
L... | {
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"cc @jplu since it seems to come from the `TFTrainer`.",
"Hello!\r\n\r\nSince transformers 4.2.0 you need to have TensorFlow 2.3 at least.",
"@jplu With TensorFlow 2.3 and transformers 4.4.0.dev0, I'm getting the error below:\r\n\r\n[INFO|trainer_tf.py:522] 2021-02-18 19:18:25,103 >> ***** Running training ****... | 1,613 | 1,698 | 1,619 | NONE | null | ## Environment info
- `transformers` version: 4.4.0.dev0
- Platform: Linux-4.15.0-111-generic-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.8
- PyTorch version (GPU?): 1.7.1 (False)
- Tensorflow version (GPU?): 2.2.0 (False)
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: ... | {
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"Pinging @patrickvonplaten and @sgugger ",
"Did you use the flag `--predict_with_generate`? It's there just for this: predicting using the `generate` method and the labels are then not passed (except to compute the loss).",
"Thank you for the hint. I followed this tutorial [this example](https://huggingface.co/... | 1,613 | 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: 4.3.2
- Platform: Linux-5.8.18-050818-generic-x86_64-with-glibc2.10
- Python version: 3.8.5
- PyTorch versio... | {
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"@LysandreJik cool thanks for the feedback. \r\n\r\n@sgugger Thanks, I added `fp16` for the teacher predictions. It will also now throw an error if someone tries to run it w/ distributed or TPUs and I added a note in the readme about that as well. It _can_ do multi-gpu though and will do so automatically if multip... | 1,613 | 1,613 | 1,613 | CONTRIBUTOR | null | This PR introduces a script that provides a way to improve the speed and memory performance of a zero-shot classifier by training a more efficient student model from the zero-shot teacher's predictions over an unlabeled dataset.
For a given sequence, the zero-shot classification pipeline requires each possible label... | {
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* refactors 3 places of `place_model_on_device` logic - into one public attribute with the same name as the `TrainingArguments.place_model_on_device` attribute
* adds deepspeed to that logic (it was missing in 2 places)
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https://api.github.com/repos/huggingface/transformers/issues/10242 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10242/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10242/comments | https://api.github.com/repos/huggingface/transformers/issues/10242/events | https://github.com/huggingface/transformers/issues/10242 | 810,429,935 | MDU6SXNzdWU4MTA0Mjk5MzU= | 10,242 | Upgrade transformers from 3.5.0 to 4.3.2 instance error | {
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"Hi, thanks for opening an issue. The breaking changes from version v3 to v4 are heavily documented: https://huggingface.co/transformers/migration.html#migrating-from-transformers-v3-x-to-v4-x\r\n\r\nYour particular issue is [bullet number 4](https://huggingface.co/transformers/migration.html#switching-the-return-d... | 1,613 | 1,619 | 1,619 | NONE | null | Hi guys. I tried to update the transformers module from the version 3.5.0 to the version 4.3.2.
After this upgrade, the code that previously was working now has some problems.
This is my code:
```
from transformers import AutoConfig, AutoTokenizer, TFAutoModel
config = AutoConfig.from_pretrained("amazon/bort")... | {
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* [x] port the instructions to use the new `run_seq2seq.py` script
* [x] add clarifications to using DeepSpeed in the notebook
@sgugger | {
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"By setting `num_return_sequences` you're creating bigger batches, so it is expected to have an OOM if you ask for too much returned sequences.",
"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.\... | 1,613 | 1,619 | 1,619 | NONE | null | I am getting CUDA memory error when generating text with num_return_sequences set to more than 100 for a self-trained gpt2 model. This is not expected since after every generation there should be nothing left in the GPU.
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https://api.github.com/repos/huggingface/transformers/issues/10239 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10239/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10239/comments | https://api.github.com/repos/huggingface/transformers/issues/10239/events | https://github.com/huggingface/transformers/issues/10239 | 810,348,948 | MDU6SXNzdWU4MTAzNDg5NDg= | 10,239 | Question about (no_decay = ['bias', 'LayerNorm.weight']) in BERT(Transformer-based) | {
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"Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.\r\nCould you ask your question on the [forum](https://discusss.huggingface.co) instead?\r\n\r\nThanks!"
] | 1,613 | 1,613 | 1,613 | NONE | null | Hi, I have a Question about the BERT model code.
I saw "no_decay = ['bias', 'LayerNorm.weight']" in BERT code(especially, in Optimizer part). It seemed reasonable, however, did this prove to be better performance? Or is it just to speed up calculations? | {
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https://api.github.com/repos/huggingface/transformers/issues/10238 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10238/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10238/comments | https://api.github.com/repos/huggingface/transformers/issues/10238/events | https://github.com/huggingface/transformers/issues/10238 | 810,329,858 | MDU6SXNzdWU4MTAzMjk4NTg= | 10,238 | ConvBert not compatible with torch v1.6 | {
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"Testing all versions from torch v1.3.0+ is indeed on the roadmap, I expect ~1 month out alongside all the other tests improvements.",
"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 n... | 1,613 | 1,619 | 1,619 | MEMBER | null | ConvBERT uses statements like `torch.multiply` which did not exist in pytorch v1.6 => ConvBERT is not compatible with v1.6 (cc @abhishekkrthakur).
This can easily be checked when running:
`pytest tests/test_modeling_convbert.py`
@LysandreJik, @sgugger - It would be great to test all the different pytorch versi... | {
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https://api.github.com/repos/huggingface/transformers/issues/10237 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10237/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10237/comments | https://api.github.com/repos/huggingface/transformers/issues/10237/events | https://github.com/huggingface/transformers/pull/10237 | 810,309,933 | MDExOlB1bGxSZXF1ZXN0NTc1MDIyNjA1 | 10,237 | TransCoder | {
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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)... | 1,613 | 1,619 | 1,619 | MEMBER | null | # What does this PR do?
Adds TransCoder https://github.com/facebookresearch/TransCoder | {
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"Sure, Patrick !",
"I’ve addressed all the review comments, and all the slow/fast tests are now passing.\r\n\r\nI didn’t add fast tokenizer because `M2M100` is `sentencepiece` based tokenizer, but it uses `sentencepiece` for just tokenizing and then uses a vocab file to convert the tokens to ids and ids to toke... | 1,613 | 1,631 | 1,615 | MEMBER | null | # What does this PR do?
Adds the M2M100 model
https://github.com/pytorch/fairseq/tree/master/examples/m2m_100
Fixes #8054 | {
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https://api.github.com/repos/huggingface/transformers/issues/10235 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10235/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10235/comments | https://api.github.com/repos/huggingface/transformers/issues/10235/events | https://github.com/huggingface/transformers/pull/10235 | 810,267,710 | MDExOlB1bGxSZXF1ZXN0NTc0OTg3MTM1 | 10,235 | [file_utils] do not gobble certain kinds of requests.ConnectionError | {
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"@sgugger Definitely on my radar at some point.\r\n\r\nFor now though it's useful for me to have a more experimental codebase where the API can change/break :)",
"> LGTM but I don't have sufficient `requests` knowledge to be sure this catches all exceptions that we want to catch\r\n\r\nwe're in the same boat, sai... | 1,613 | 1,616 | 1,616 | MEMBER | null | Backport from https://github.com/huggingface/huggingface_hub/pull/14/commits/34b7b70d07ab1c9fc2f7da603d47cb344e256af6
might close (or at the very least provide more transparency into) #8690, #10067, and others | {
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" Google released the source code for transformer-based mixture-of-experts (the switch architecture): https://github.com/tensorflow/mesh/blob/master/mesh_tensorflow/transformer/moe.py\r\n\r\nAccording to https://www.infoq.com/news/2021/02/google-trillion-parameter-ai/ the model weights are not available yet."
] | 1,613 | 1,613 | null | NONE | null | Google has come up with yet another transformer: https://arxiv.org/pdf/2101.03961.pdf | {
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https://api.github.com/repos/huggingface/transformers/issues/10233 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10233/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10233/comments | https://api.github.com/repos/huggingface/transformers/issues/10233/events | https://github.com/huggingface/transformers/pull/10233 | 810,238,952 | MDExOlB1bGxSZXF1ZXN0NTc0OTYzMDA2 | 10,233 | Making TF Longformer-like models compliant with AMP | {
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This PR makes the TF Longformer-like models compliant with AMP. All the slow tests are passing as well for these models.
These two models cannot be XLA compliant for now, as it seems that `tf.where` cannot be used in XLA if the `x` and `y` parameters are `None`. See the `_get_global_attn_i... | {
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https://api.github.com/repos/huggingface/transformers/issues/10232 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10232/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10232/comments | https://api.github.com/repos/huggingface/transformers/issues/10232/events | https://github.com/huggingface/transformers/issues/10232 | 810,165,137 | MDU6SXNzdWU4MTAxNjUxMzc= | 10,232 | Multilabel Sequence Classification in trainer | {
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"Hi @LysandreJik, \r\nIf no one is working on this can I start on this feature? \r\nI imagine this will not be that difficult and should be possible by using the sigmoid instead of the softmax, where we're calculating a probability between 0-1 for each class which will be encapsulated in a class similar to [ModelNa... | 1,613 | 1,628 | null | CONTRIBUTOR | null | # 🚀 Feature request
We need to be able to use the trainer for multilabel classification problems.
## Motivation
Right now we create our models in the old fashioned way, with a sigmoid layer at the end so we can do multilabel. However if we could use the trainer directly, we wouldn't need to maintain different... | {
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https://api.github.com/repos/huggingface/transformers/issues/10231 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10231/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10231/comments | https://api.github.com/repos/huggingface/transformers/issues/10231/events | https://github.com/huggingface/transformers/issues/10231 | 810,150,822 | MDU6SXNzdWU4MTAxNTA4MjI= | 10,231 | Wav2Vec2 finetune | {
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"Patrick is working on it, see #10145 "
] | 1,613 | 1,614 | 1,614 | 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. -->
Can you please share code to how to finetune transformers.Wav2Vec2ForCTC, or maybe on how to give labels to the model in order to get loss?
## Motivation
... | {
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