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https://api.github.com/repos/huggingface/transformers/issues/10735 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10735/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10735/comments | https://api.github.com/repos/huggingface/transformers/issues/10735/events | https://github.com/huggingface/transformers/pull/10735 | 832,350,238 | MDExOlB1bGxSZXF1ZXN0NTkzNTIyODI2 | 10,735 | Release utils | {
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This PR adds utilities to help with the release process and four make commands to use them easily:
1. `make pre-release` will do all the necessary steps prior to the commit with the release tag (put the right version in all the good places and clean the README from the references to the ma... | {
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"This looks good to me! I think it's a good idea to add `--source_prefix` for the 5 t5 checkpoints in the examples. We should specify though that it's only for these 5 checkpoints. Let's discuss summarization in the issue.",
"As discussed in https://github.com/huggingface/transformers/issues/10733#issuecomment-80... | 1,615 | 1,616 | 1,616 | CONTRIBUTOR | null | This PR:
* switches the summarization example to use CNN/DailyMail as with t5-small it provides high scores out of the box.
* fixes T5 examples to include `--source_prefix` - it's **not** optional. If you give it a try you will see that you get 10x worse bleu scores w/o it. w/ `27.6849`, w/o `2.374`
* adds a normal ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10733 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10733/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10733/comments | https://api.github.com/repos/huggingface/transformers/issues/10733/events | https://github.com/huggingface/transformers/issues/10733 | 832,329,894 | MDU6SXNzdWU4MzIzMjk4OTQ= | 10,733 | [examples run_summarization.py] t5 worse score w/ --source_prefix "summarize: " than w/o | {
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"`--max_train_samples 50` is a tiny sample, I am not surprised that the model doesn't learn anything here. Note that `t5-small` was pretrained on CNN/Dailymail and WMT, but **not** on XSum. So, it makes sense that one gets reasonable results when fine-tuning the model on just 50 translation samples of WMT16 because... | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null | I don't think the latest incarnation of summarization examples works for t5.
I'm lost with all the proposed let's-not-do-anything special for t5, except as you will see from numbers something isn't right:
With the latest master:
```
python examples/seq2seq/run_summarization.py --model_name_or_path t5-small --do... | {
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https://api.github.com/repos/huggingface/transformers/issues/10732 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10732/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10732/comments | https://api.github.com/repos/huggingface/transformers/issues/10732/events | https://github.com/huggingface/transformers/issues/10732 | 832,315,923 | MDU6SXNzdWU4MzIzMTU5MjM= | 10,732 | run_clm.py does not work with any other block_size other than 1024 | {
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"Indeed! Would you mind making a PR with that change since you found the correct fix?",
"Sure, I'll get that prepared!",
"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 iss... | 1,615 | 1,619 | 1,619 | NONE | null | **Note:** This issue can be fixed with one character change as described in last section.
## Environment info
- `transformers` version: 4.4.0.dev0
- Platform: Windows-10-10.0.19041-SP0
- Python version: 3.8.5
- PyTorch version (GPU?): 1.7.1 (True)
- Tensorflow version (GPU?): 2.4.1 (False)
- Using GPU in scrip... | {
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https://api.github.com/repos/huggingface/transformers/issues/10731 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10731/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10731/comments | https://api.github.com/repos/huggingface/transformers/issues/10731/events | https://github.com/huggingface/transformers/issues/10731 | 832,302,379 | MDU6SXNzdWU4MzIzMDIzNzk= | 10,731 | Fix log message for training from checkpoint with global step | {
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"Yes, that sounds clearer. Would you mind making a PR with this?",
"Will make time this week. ",
"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 t... | 1,615 | 1,619 | 1,619 | NONE | null | # 🚀 Feature request
I think the log message here is wrong:
https://github.com/huggingface/transformers/blob/master/src/transformers/trainer.py#L978
I think it should read something along these lines:
```
logger.info(
f" Will skip the first {epochs_trained} epochs then the first {step... | {
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https://api.github.com/repos/huggingface/transformers/issues/10730 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10730/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10730/comments | https://api.github.com/repos/huggingface/transformers/issues/10730/events | https://github.com/huggingface/transformers/issues/10730 | 832,245,861 | MDU6SXNzdWU4MzIyNDU4NjE= | 10,730 | Stacked Roberta run_mlm.py | {
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## Benchmark
I try to run [transformers/experiments/language_modeling/run_mlm.py](https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm.py) in order to train Roberta from scratch on Wikipedia dataset.
## Set-up
Transformers version: 4.4.0.d... | {
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https://api.github.com/repos/huggingface/transformers/issues/10729 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10729/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10729/comments | https://api.github.com/repos/huggingface/transformers/issues/10729/events | https://github.com/huggingface/transformers/issues/10729 | 832,211,831 | MDU6SXNzdWU4MzIyMTE4MzE= | 10,729 | Multi-node training with the latest transformers/examples code | {
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"cc @sgugger ",
"I'm unsure what you think is not supported. Launching any of the example scripts with \r\n```\r\npython -m torch.distributed.launch --nproc_per_node=xxx \\\r\n --node_rank=$THIS_MACHINE_INDEX \\\r\n --master_addr=\"192.168.1.1\" \\\r\n --master_port=1234 \\\r\n run_xxx.py\r\n```\r\nis goi... | 1,615 | 1,621 | 1,615 | NONE | null | Hi,
I am trying to follow the instructions on how to use the examples from [https://huggingface.co/transformers/examples.html] and I notice there is a difference between version 4.3 and 1.2 in the distributed training session. In the older version it seems that it supports multi-node training with
" --node_rank... | {
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https://api.github.com/repos/huggingface/transformers/issues/10728 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10728/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10728/comments | https://api.github.com/repos/huggingface/transformers/issues/10728/events | https://github.com/huggingface/transformers/pull/10728 | 832,195,843 | MDExOlB1bGxSZXF1ZXN0NTkzMzk1NDgy | 10,728 | [Issue template] need to update/extend who to tag | {
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"For broken models you would just tag the model author(s) – we'll add a feature to the model hub to tag someone in a conversation thread, but in the meantime you can use the Forum to ping them",
"That's a great idea to tag the model author - how would a user know the model author's corresponding forum username? I... | 1,615 | 1,616 | 1,616 | CONTRIBUTOR | null | This PR
* [x] adds an entry for what to do what to do when someone has model hub issues - thank you, @julien-c!
TODO/Input needed:
* [ ] need to update who to tag for `tensorflow` Issues
@LysandreJik
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https://api.github.com/repos/huggingface/transformers/issues/10727 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10727/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10727/comments | https://api.github.com/repos/huggingface/transformers/issues/10727/events | https://github.com/huggingface/transformers/pull/10727 | 832,172,939 | MDExOlB1bGxSZXF1ZXN0NTkzMzc2NTM0 | 10,727 | Rename zero-shot pipeline multi_class argument | {
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The name is changed in the zero-shot distill... | {
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https://api.github.com/repos/huggingface/transformers/issues/10726 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10726/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10726/comments | https://api.github.com/repos/huggingface/transformers/issues/10726/events | https://github.com/huggingface/transformers/issues/10726 | 832,137,409 | MDU6SXNzdWU4MzIxMzc0MDk= | 10,726 | broken models on the hub | {
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"I fixed this model (it had `bart` as a `model_type` instead of `mbart` in `config.json`). \r\n\r\nBut the point of this issue is that perhaps we could add to a todo list to run a cronjob that will validate the models and tokenizers? \r\n\r\n@theo-m, is this something that would fit with the project you're currentl... | 1,615 | 1,619 | 1,619 | CONTRIBUTOR | null | Go to https://huggingface.co/sshleifer/distill-mbart-en-ro-12-6 click on "use in transformers", copy-n-paste and nope can't use this in `transformers`:
```
python -c 'from transformers import AutoTokenizer; AutoTokenizer.from_pretrained("sshleifer/distill-mbart-en-ro-12-6")'
Traceback (most recent call last):
F... | {
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https://api.github.com/repos/huggingface/transformers/issues/10725 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10725/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10725/comments | https://api.github.com/repos/huggingface/transformers/issues/10725/events | https://github.com/huggingface/transformers/pull/10725 | 832,115,929 | MDExOlB1bGxSZXF1ZXN0NTkzMzI5MzQ2 | 10,725 | Flax testing should not run the full torch test suite | {
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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.
Then, please replace this w... | {
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https://api.github.com/repos/huggingface/transformers/issues/10724 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10724/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10724/comments | https://api.github.com/repos/huggingface/transformers/issues/10724/events | https://github.com/huggingface/transformers/pull/10724 | 832,073,364 | MDExOlB1bGxSZXF1ZXN0NTkzMjk0MDc5 | 10,724 | Add minimum version check in examples | {
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This PR adds a minimum version check to all examples, in order to avoid the waves of issues created each time they use a functionality that was just released into `Trainer`. The script will immediately error if the version of Transformers does not match the required minimum version. At each r... | {
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https://api.github.com/repos/huggingface/transformers/issues/10723 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10723/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10723/comments | https://api.github.com/repos/huggingface/transformers/issues/10723/events | https://github.com/huggingface/transformers/issues/10723 | 832,007,146 | MDU6SXNzdWU4MzIwMDcxNDY= | 10,723 | Train tokenizer for Deberta | {
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"HuggingFace has another library called [tokenizers](https://github.com/huggingface/tokenizers) especially for this.",
"Currently, the training of Deberta Tokenizer is not supported directly by huggingface. Of course, you can create the required files by yourself from BPETokenizer training output, but you could ... | 1,615 | 1,619 | 1,619 | NONE | null | Hi, I would like to know how can I train a DeBERTa tokenizer. From the paper I saw it uses BPETokenizer, but the BPETokenizer from huggingface/tokenizers doesn't work for this. Could you recommend me another implementation or library or a correct configuration for huggingface/tokenizers implementation to be able to tra... | {
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https://api.github.com/repos/huggingface/transformers/issues/10722 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10722/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10722/comments | https://api.github.com/repos/huggingface/transformers/issues/10722/events | https://github.com/huggingface/transformers/issues/10722 | 831,955,586 | MDU6SXNzdWU4MzE5NTU1ODY= | 10,722 | iterative evaluation in Trainer to save memory | {
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"This would result in an inaccurate metric in most cases, as metric functions are seldom linear. I'm afraid you will have to run evaluation on smaller chunks or use your own evaluation loop.",
"Yes of course I thought maybe to gather a reduced version of the predictions before actually computing the metric\r\n\r\... | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null | # 🚀 Feature request
In Trainer.prediction_loop, compute metrics batch per batch (or allow to tweak this number) instead of gathering the whole predictions in a single array (nb: I'm aware of `eval_accumulation_steps` but it only allows to save GPU memory)
## Motivation
Running a ses2seq evaluation on a datase... | {
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https://api.github.com/repos/huggingface/transformers/issues/10721 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10721/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10721/comments | https://api.github.com/repos/huggingface/transformers/issues/10721/events | https://github.com/huggingface/transformers/issues/10721 | 831,933,725 | MDU6SXNzdWU4MzE5MzM3MjU= | 10,721 | Run Time Error: RuntimeError: Expected hidden[0] size (2, 1, 512), got [2, 128, 512] - Seq2Seq Model with PreTrained BERT 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)... | 1,615 | 1,623 | 1,623 | NONE | null | Hi,
I am facing this run time error while training a seq2seq model with pretrained bert model.
```
RuntimeError Traceback (most recent call last)
<ipython-input-63-472071541d41> in <module>()
8 start_time = time.time()
9
---> 10 train_loss = train(model, tr... | {
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https://api.github.com/repos/huggingface/transformers/issues/10720 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10720/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10720/comments | https://api.github.com/repos/huggingface/transformers/issues/10720/events | https://github.com/huggingface/transformers/issues/10720 | 831,926,683 | MDU6SXNzdWU4MzE5MjY2ODM= | 10,720 | Cannot use custom roberta tokenizer with run_mlm_wwm.py | {
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"That example only runs with `BERT`, which is why it has been moved to a separate research project.",
"I tried this script with albert and it worked, which script should I use to train a Roberta model from scratch with Whole word Masking??",
"Is that intended:\r\n`--model_type deberta`\r\n?\r\n@alexvaca0 ",
... | 1,615 | 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.dev0
- Platform: Ubuntu 18
- Python version: 3.7
- PyTorch version (GPU?): 1.7.1 (YES)
- Tensorflow ver... | {
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https://api.github.com/repos/huggingface/transformers/issues/10719 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10719/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10719/comments | https://api.github.com/repos/huggingface/transformers/issues/10719/events | https://github.com/huggingface/transformers/pull/10719 | 831,858,368 | MDExOlB1bGxSZXF1ZXN0NTkzMTE0MTI3 | 10,719 | [WIP] Extend LayoutLMTokenizer to handle bounding boxes | {
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"The fixup target fails because `get_modified_files.py` reports `tokenization_layoutlm_fast.py` as differing from the master branch.\r\nThen calling e.g. `black` to format that file fails because it doesn't exist anymore. How would I fix that?",
"Hello! Thank you for your PR, and sorry for getting back to you so ... | 1,615 | 1,622 | 1,621 | CONTRIBUTOR | null | # What does this PR do?
LayoutLMTokenizer does not take care properly of additional model input `bbox` (Bounding Boxes for words/tokens on a document), see https://github.com/huggingface/transformers/issues/10349.
With this PR, LayoutLMTokenizer will take care of bounding boxes when doing tokenization, that is re... | {
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https://api.github.com/repos/huggingface/transformers/issues/10718 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10718/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10718/comments | https://api.github.com/repos/huggingface/transformers/issues/10718/events | https://github.com/huggingface/transformers/pull/10718 | 831,838,689 | MDExOlB1bGxSZXF1ZXN0NTkzMDk3NTMy | 10,718 | Fix backward compatibility with EvaluationStrategy | {
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As mentioned in #10666, the switch from `EvaluationStrategy` to `IntervalStrategy` is not fully backward compatible. This PR fixes that. | {
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https://api.github.com/repos/huggingface/transformers/issues/10717 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10717/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10717/comments | https://api.github.com/repos/huggingface/transformers/issues/10717/events | https://github.com/huggingface/transformers/issues/10717 | 831,780,165 | MDU6SXNzdWU4MzE3ODAxNjU= | 10,717 | How can I get the exact position von answers? | {
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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!",
"> Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.\r\n> Could yo... | 1,615 | 1,615 | 1,615 | NONE | null | I want to load a local model for Question and Answers task. I have copied the almost Code from Pipeline like follow:
model = MyBert()
checkpoint = torch.load('./training_mode_aim/checkpoint.pth.tar')
model.load_state_dict(checkpoint['model'])
model.eval()
#read the context in local file
texts = utils.readTxt()
... | {
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https://api.github.com/repos/huggingface/transformers/issues/10716 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10716/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10716/comments | https://api.github.com/repos/huggingface/transformers/issues/10716/events | https://github.com/huggingface/transformers/issues/10716 | 831,779,915 | MDU6SXNzdWU4MzE3Nzk5MTU= | 10,716 | Language model for wav2vec2.0 decoding | {
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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\nYou can ping @patrickvonplaten on the forum as he's the best suited to help you out.\r\n\r\nThanks!",
"I moved the questio... | 1,615 | 1,636 | 1,615 | NONE | null | Hello, I implemented [wav2vec2.0 code](https://huggingface.co/blog/fine-tune-xlsr-wav2vec2) and a language model is not used for decoding. How can I add a language model (let's say a language model which is trained with KenLM) for decoding?
thanks in advance. | {
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https://api.github.com/repos/huggingface/transformers/issues/10715 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10715/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10715/comments | https://api.github.com/repos/huggingface/transformers/issues/10715/events | https://github.com/huggingface/transformers/issues/10715 | 831,631,676 | MDU6SXNzdWU4MzE2MzE2NzY= | 10,715 | Pegasus-Large Question | {
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"`pegasus-large` is a pre-trained checkpoint. It's not fine-tuned on downstream task. The finetuned checkpoint name will have the name of the datsets in them. \r\n\r\nAlso please the [forum](https://discuss.huggingface.co/) to ask such questions.\r\n\r\nThanks.",
"This issue has been automatically marked as stale... | 1,615 | 1,619 | 1,619 | NONE | null | Is [Pegasus Large model checkpoint](https://huggingface.co/google/pegasus-large) trained on any downstream task? Or is it only trained on pre-training task of gap sentence? | {
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https://api.github.com/repos/huggingface/transformers/issues/10714 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10714/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10714/comments | https://api.github.com/repos/huggingface/transformers/issues/10714/events | https://github.com/huggingface/transformers/pull/10714 | 831,537,704 | MDExOlB1bGxSZXF1ZXN0NTkyODQzOTc2 | 10,714 | [Wav2Vec2] Make wav2vec2 test deterministic | {
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The Wav2Vec2 tests are not deterministic on some machines. This PR should force all tests to use the expected samples. | {
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https://api.github.com/repos/huggingface/transformers/issues/10713 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10713/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10713/comments | https://api.github.com/repos/huggingface/transformers/issues/10713/events | https://github.com/huggingface/transformers/issues/10713 | 831,506,758 | MDU6SXNzdWU4MzE1MDY3NTg= | 10,713 | Is any possible with pipeline for using local model? | {
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"As mentioned in the [docs](https://huggingface.co/transformers/main_classes/pipelines.html), you can either provide a model identifier from the hub or a model that inherits from `PreTrainedModel` or `TFPreTrainedModel`. \r\n\r\nSo suppose you have fine-tuned a model and stored it into a variable called `model`, th... | 1,615 | 1,615 | 1,615 | NONE | null | Hallo
I have fine tuned a model in my local PC. I have read the Doc for Pipeline to search a way to use local model in Pipeline. But didn't find. Someone who knows how should I do? | {
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https://api.github.com/repos/huggingface/transformers/issues/10712 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10712/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10712/comments | https://api.github.com/repos/huggingface/transformers/issues/10712/events | https://github.com/huggingface/transformers/pull/10712 | 831,498,736 | MDExOlB1bGxSZXF1ZXN0NTkyODEwMzgw | 10,712 | Update modeling_tf_pytorch_utils.py | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,615 | 1,620 | 1,620 | NONE | null | # What does this PR do?
Fix a bug in convert_tf_weight_name_to_pt_weight_name().
Similar to the kernel parameters, the recurrent_kernel parameters in the LSTM networks need to be transposed, too.
Fixes # (issue)
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other ch... | {
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https://api.github.com/repos/huggingface/transformers/issues/10711 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10711/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10711/comments | https://api.github.com/repos/huggingface/transformers/issues/10711/events | https://github.com/huggingface/transformers/issues/10711 | 831,367,559 | MDU6SXNzdWU4MzEzNjc1NTk= | 10,711 | 'Trainer' object has no attribute 'log_metrics' | {
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"Btw ,these 3 APIs show similar error:\r\n**API:**\r\n```\r\n trainer.log_metrics(\"train\", metrics)\r\n trainer.save_metrics(\"train\", metrics)\r\n trainer.save_state()\r\n```\r\n\r\n**error**\r\n```\r\nTraceback (most recent call last):\r\n File \"run_mlm.py\", line 476, in <module>\r\n main()\r\n File \"r... | 1,615 | 1,615 | 1,615 | 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:4.3.3
- Platform:Pytorch
- Python version:3.7.0
- PyTorch version (GPU?):GPU
- Tensorflow version (GPU?):
-... | {
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https://api.github.com/repos/huggingface/transformers/issues/10710 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10710/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10710/comments | https://api.github.com/repos/huggingface/transformers/issues/10710/events | https://github.com/huggingface/transformers/pull/10710 | 831,286,063 | MDExOlB1bGxSZXF1ZXN0NTkyNjM3OTUx | 10,710 | independent training / eval with local files | {
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"Thanks!"
] | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null | # What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/10709 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10709/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10709/comments | https://api.github.com/repos/huggingface/transformers/issues/10709/events | https://github.com/huggingface/transformers/pull/10709 | 831,187,907 | MDExOlB1bGxSZXF1ZXN0NTkyNTY2MTEx | 10,709 | Wrong link to super class | {
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Documentation was referring to slow tokenizer class while it should be the fast tokenizer.
## 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/h... | {
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https://api.github.com/repos/huggingface/transformers/issues/10708 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10708/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10708/comments | https://api.github.com/repos/huggingface/transformers/issues/10708/events | https://github.com/huggingface/transformers/issues/10708 | 831,178,412 | MDU6SXNzdWU4MzExNzg0MTI= | 10,708 | ValueError: Unsupported value type BatchEncoding returned by IteratorSpec._serialize | {
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```
from transformers import TFDistilBertForSequenceClassification, DistilBertTokenizerFast
# initialize longformer tokenizer and model
tokenizer = DistilBertTokenizerFast.from_pretrained("distilbert-base-uncased", do_lower_case=True)
model ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10707 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10707/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10707/comments | https://api.github.com/repos/huggingface/transformers/issues/10707/events | https://github.com/huggingface/transformers/issues/10707 | 831,158,242 | MDU6SXNzdWU4MzExNTgyNDI= | 10,707 | Inheriting from BartForConditionalGeneration into a new class - weight not initializing | {
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https://api.github.com/repos/huggingface/transformers/issues/10706 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10706/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10706/comments | https://api.github.com/repos/huggingface/transformers/issues/10706/events | https://github.com/huggingface/transformers/issues/10706 | 831,134,128 | MDU6SXNzdWU4MzExMzQxMjg= | 10,706 | Trainer crashes when saving checkpoint | {
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"As indicated in the [documentation](https://huggingface.co/transformers/main_classes/trainer.html#trainingarguments) `metric_for_best_model` _Must be the name of a metric returned by the evaluation with or without the prefix \"eval\\_\"_. You passed a Metric object to it instead of the name returned by your `compu... | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 4.3.3
- Platform: Linux-4.4.0-161-generic-x86_64-with-glibc2.10
- Python version: 3.8.8
- PyTorch version (GPU?): 1.8.0+cu101 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: Yes, distributed
- Using distributed or parallel set-up in... | {
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https://api.github.com/repos/huggingface/transformers/issues/10705 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10705/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10705/comments | https://api.github.com/repos/huggingface/transformers/issues/10705/events | https://github.com/huggingface/transformers/issues/10705 | 831,108,595 | MDU6SXNzdWU4MzExMDg1OTU= | 10,705 | Please provide format of the dataset to finetuning wav2vec using run_asr.py script | {
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"We are organizing a \"fine-tuning XLSR-53\" event. Check this announcement: https://discuss.huggingface.co/t/open-to-the-community-xlsr-wav2vec2-fine-tuning-week-for-low-resource-languages/4467. Would be awesome if you want to participate :-)",
"This issue has been automatically marked as stale because it has no... | 1,615 | 1,618 | 1,618 | NONE | null | Hi @patrickvonplaten, thanks for the great work, could you please provide some examples for the dataset format to train the wav2vec model using run_asr.py script. | {
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https://api.github.com/repos/huggingface/transformers/issues/10704 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10704/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10704/comments | https://api.github.com/repos/huggingface/transformers/issues/10704/events | https://github.com/huggingface/transformers/issues/10704 | 831,093,479 | MDU6SXNzdWU4MzEwOTM0Nzk= | 10,704 | How to generate texts in huggingface in a batch way? | {
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"Looking at the [source code](https://github.com/huggingface/transformers/blob/4c32f9f26e6a84f0d9843fec8757e6ce640bb44e/src/transformers/pipelines/text_generation.py#L108) of the text-generation pipeline, it seems that the texts are indeed generated one by one, so it's not ideal for batch generation. \r\n\r\nIn ord... | 1,615 | 1,669 | 1,619 | NONE | null | I am new to huggingface. My task is quite simple, where I want to generate contents based on the given titles. The below codes is of low efficiency, that the GPU Util is only about 15%. It seems that it makes generation one by one. How can I improve the code to process and generate the contents in a batch way?
```
... | {
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https://api.github.com/repos/huggingface/transformers/issues/10703 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10703/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10703/comments | https://api.github.com/repos/huggingface/transformers/issues/10703/events | https://github.com/huggingface/transformers/pull/10703 | 831,075,817 | MDExOlB1bGxSZXF1ZXN0NTkyNDgxOTI2 | 10,703 | DebertaTokenizer Rework closes #10258 | {
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"This is great @cronoik! I just tested it and reproduced identical results between the previous version and this one. Fantastic!\r\n\r\nCould you add an integration tests for the DeBERTa tokenizer to ensure the implementations don't diverge? You can just copy paste the [test for ALBERT tokenizers](https://github.co... | 1,615 | 1,617 | 1,617 | CONTRIBUTOR | null | # What does this PR do?
Fixes #10258
@BigBird01 Please upload these [files](https://drive.google.com/drive/folders/1gH5EMABR94iHO7SCb_AdNGCOOIdSloxh?usp=sharing) to your deberta repositories.
@huggingface: Please don't merge before @BigBird01 has uploaded the files to his repository.
## Before submitting
- [... | {
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https://api.github.com/repos/huggingface/transformers/issues/10702 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10702/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10702/comments | https://api.github.com/repos/huggingface/transformers/issues/10702/events | https://github.com/huggingface/transformers/issues/10702 | 831,071,620 | MDU6SXNzdWU4MzEwNzE2MjA= | 10,702 | Performance Issue in doing inferencing hugging face models | {
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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!"
] | 1,615 | 1,615 | 1,615 | 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:3.2.0
- Platform:windows azure with GPU
- Python version: 3.6
- PyTorch version (GPU?):CUDA 10.1
- Tensorflo... | {
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https://api.github.com/repos/huggingface/transformers/issues/10701 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10701/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10701/comments | https://api.github.com/repos/huggingface/transformers/issues/10701/events | https://github.com/huggingface/transformers/issues/10701 | 831,063,893 | MDU6SXNzdWU4MzEwNjM4OTM= | 10,701 | Seq2Seq Model with PreTrained BERT Model is Throwing Error During Training: ValueError("You cannot specify both input_ids and inputs_embeds at the same time") | {
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"Hi @Ninja16180 \r\n\r\nCould you please post a short code snippet to reproduce the issue? Thanks.",
"Hi Suraj,\r\n\r\nI was able to find out the issue; there was a variable name I wrongly passed into the decoder class and hence the error.\r\n\r\nCorrection made:\r\n`embedded = self.bert(sent2)[0] should be embed... | 1,615 | 1,615 | 1,615 | NONE | null | Hi,
I tried creating a seq2seq model using pretrained BERT model following your tutorials:
https://github.com/bentrevett/pytorch-sentiment-analysis/blob/master/6%20-%20Transformers%20for%20Sentiment%20Analysis.ipynb
https://github.com/bentrevett/pytorch-seq2seq/blob/master/1%20-%20Sequence%20to%20Sequence%20Lear... | {
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"Thanks for your interest! LUKE is not part of the master branch yet.\r\n\r\nActually, the current implementation of LUKE is here (at my `adding_luke_v2` branch): https://github.com/NielsRogge/transformers/tree/adding_luke_v2/src/transformers/models/luke\r\n\r\nNote that it is work-in-progress, but you can already ... | 1,615 | 1,615 | 1,615 | NONE | null | ## Environment info
- `transformers` version: 4.1.1
- Platform: Windows-10-10.0.19041-SP0
- Python version: 3.8.3
- PyTorch version (GPU?): 1.7.1+cpu (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No
### Who can help
@Ly... | {
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https://api.github.com/repos/huggingface/transformers/issues/10699 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10699/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10699/comments | https://api.github.com/repos/huggingface/transformers/issues/10699/events | https://github.com/huggingface/transformers/pull/10699 | 830,881,920 | MDExOlB1bGxSZXF1ZXN0NTkyMzUwNDk5 | 10,699 | TF BART models - Add `cross_attentions` to model output and fix cross-attention head masking | {
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"Currently, there are some Torch/TF equivalent tests failing but it should be settled down once #10605 be merged.",
"@jplu - I'm gonna run all slow tests today and will let you know if everything works or not.",
"@jplu - I ran all (slow) non-GPU tests and it seems to me everything is passing :) ",
"Ok, if all... | 1,615 | 1,619 | 1,619 | CONTRIBUTOR | null | This PR fixes some missing and invalid things around `cross_attentions` for the TensorFlow implementation of BART models:
- `Bart`,
- `Blenderbot` / `Blenderbot_small`,
- `Marian`,
- `MBart`,
- `Pegasus`.
More specifically, this PR includes:
- Enable returning `cross_attentions`
- Add class `TFBaseModelOutp... | {
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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)... | 1,615 | 1,619 | 1,619 | CONTRIBUTOR | null | # 🚀 Feature request
TensorFlow encoder-decoder models cannot return `cross_attentions` as do their PyTorch counterparts.
## Motivation
It would be nice to narrow the gap between PyTorch and Tensorflow implementations.
## Your contribution
I've been working on PR fixing this issue.
## Reviewers
@jplu and... | {
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https://api.github.com/repos/huggingface/transformers/issues/10697 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10697/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10697/comments | https://api.github.com/repos/huggingface/transformers/issues/10697/events | https://github.com/huggingface/transformers/pull/10697 | 830,830,301 | MDExOlB1bGxSZXF1ZXN0NTkyMzExMDY2 | 10,697 | Fix Wav2Vec2 classes imports | {
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Fixes imports for the following classes:
* Wav2Vec2CTCTokenizer
* Wav2Vec2FeatureExtractor
* Wav2Vec2Processor
In order to fine tune FB's Wav2Vec2 XLSR model, these classes need to be accessible. Importing using the instructions in the current [blog post](https://huggingface.co/blog/f... | {
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https://api.github.com/repos/huggingface/transformers/issues/10696 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10696/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10696/comments | https://api.github.com/repos/huggingface/transformers/issues/10696/events | https://github.com/huggingface/transformers/issues/10696 | 830,802,513 | MDU6SXNzdWU4MzA4MDI1MTM= | 10,696 | OSerror, when loading 'wav2vec2-large-xlsr-53' Model of Wav2vec2 | {
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"The model doesn't contains the tokenizer and preprocessing files.\r\nCheckout this notebook:\r\nhttps://huggingface.co/blog/fine-tune-xlsr-wav2vec2\r\n\r\nTo build your own vocab etc",
"@flozi00 Thank you! \r\n\r\n> The model doesn't contains the tokenizer and preprocessing files.\r\n> Checkout this notebook:\r\... | 1,615 | 1,661 | 1,615 | NONE | null | ## Environment info
- `transformers` version: 4.3.3
- Platform: Linux-4.15.0-29-generic-x86_64-with-glibc2.10
- Python version: 3.8.8
- PyTorch version (GPU?): 1.8.0 (False)
- Tensorflow version (GPU?): not installed (NA)
@patrickvonplaten
## Information
Model I am using Wav2vec2.0:
The problem ... | {
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"Great! Thanks a lot for correcting those :-)\r\n",
"Hey @MikeG112, sorry could you run `make style` once to fix the code quality issue? Then we can merge :-)",
"Hey @patrickvonplaten, absolutely, I added the changes made by `make style`. Thanks for the review and the wav2vec2 implementation :)"
] | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null | # What does this PR do?
This PR resolves two Wav2Vec2 documentation statements that I believe are typos.
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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)... | 1,615 | 1,618 | 1,618 | CONTRIBUTOR | null | mBART Large-50 MMT provides incorrect translation when the source and target language are the same, e.g. when translating from "en_XX" to "en_XX"
## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
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"@LysandreJik I've been mostly following: https://huggingface.co/transformers/add_new_model.html so far.\r\nTrying to add the tokenizer. I think I am good for the slow one but not sure what to do for the fast one, in particular how to generate the tokenizer.json style files (e.g: https://huggingface.co/t5-small/res... | 1,615 | 1,628 | 1,627 | CONTRIBUTOR | null | Add RemBERT model to Huggingface ( https://arxiv.org/abs/2010.12821 ).
This adds code to support the RemBERT model in Huggingface.
In terms of implementation, this is roughly a scaled up version of mBERT with ALBERT-like factorized embeddings and tokenizer.
Still needs to be done:
- [x] Check results validity... | {
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https://api.github.com/repos/huggingface/transformers/issues/10691 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10691/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10691/comments | https://api.github.com/repos/huggingface/transformers/issues/10691/events | https://github.com/huggingface/transformers/issues/10691 | 830,377,713 | MDU6SXNzdWU4MzAzNzc3MTM= | 10,691 | Naming convention for (pytorch) checkpoints broken? | {
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"I think I might have come up with a bandaid solution for now. If the output dir exists and overwrite output dir flag is not set, load the configuration from the output dir and resume training from `pytorch_model.bin`. I'm going to give this a try, I think it's going to work. ",
"Yes, as I expected, it worked. I ... | 1,615 | 1,615 | 1,615 | NONE | null | # 🚀 Feature request
In previous versions of the library and sample files, checkpoints were saved with some naming convention that had `checkpoint` in the name file. Subsequent jobs could look in the output directory and check if any checkpoint is available first; if found, it would load the checkpoint and the corre... | {
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https://api.github.com/repos/huggingface/transformers/issues/10690 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10690/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10690/comments | https://api.github.com/repos/huggingface/transformers/issues/10690/events | https://github.com/huggingface/transformers/pull/10690 | 830,324,665 | MDExOlB1bGxSZXF1ZXN0NTkxODU0MDU2 | 10,690 | enable loading Mbart50Tokenizer with AutoTokenizer | {
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"Very nice ! "
] | 1,615 | 1,615 | 1,615 | MEMBER | null | # What does this PR do?
Currently `MBart50Tokenizer`, `MBart50TokenizerFast` can't be loaded using `AutoTokenizer` because they use the `MBartConfig` which is associated with `MBartTokenizer`.
This PR enables loading `MBart50Tokenizer(Fast)` by adding them to the `NO_CONFIG_TOKENIZER` list. I've also added the... | {
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"> This is not the proper way to proceed. Here you force the dtype to float32 which is not correct, because you might encounter conflicts with other values that are in float16.\r\n\r\nYes, you're right, I should not force the dtype to float32, maybe I should force it to float32 when using `mixed_precision`.\r\n\r\n... | 1,615 | 1,625 | 1,625 | CONTRIBUTOR | null | Fixed the loss of precision when using mixed_precision.
Not sure it's the right way to do this, correct me if it's wrong.
related issue: https://github.com/huggingface/transformers/issues/8559#issuecomment-797528526
- gpt2: @patrickvonplaten, @LysandreJik
- tensorflow: @jplu | {
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https://api.github.com/repos/huggingface/transformers/issues/10688 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10688/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10688/comments | https://api.github.com/repos/huggingface/transformers/issues/10688/events | https://github.com/huggingface/transformers/pull/10688 | 830,184,068 | MDExOlB1bGxSZXF1ZXN0NTkxNzM1NDc3 | 10,688 | Adding required flags to non-default arguments in hf_argparser | {
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"No problem. I can't see what test failed in CircleCI as it wants to bind to my Github account and access private things in my org. Is there any way to see the failures without letting it into my account?"
] | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null | Signed-off-by: Adam Pocock <adam.pocock@oracle.com>
# What does this PR do?
Fixes #10677. I didn't update the docs as I think this is the intended behaviour, but I can do if you think this change would be unexpected.
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the oth... | {
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https://api.github.com/repos/huggingface/transformers/issues/10687 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10687/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10687/comments | https://api.github.com/repos/huggingface/transformers/issues/10687/events | https://github.com/huggingface/transformers/pull/10687 | 830,150,548 | MDExOlB1bGxSZXF1ZXN0NTkxNzA2OTA4 | 10,687 | Multiple fixes in SageMakerTrainer | {
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This PR adds quite a few fixes to the `SageMakerTrainer` to make sure example scripts run fully. In particular it fixes:
- save made the training hanging forever
- predict didn't work
- evaluation required using `drop_last=True` which is not something anyone wants.
The goal is now to te... | {
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https://api.github.com/repos/huggingface/transformers/issues/10686 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10686/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10686/comments | https://api.github.com/repos/huggingface/transformers/issues/10686/events | https://github.com/huggingface/transformers/pull/10686 | 830,130,646 | MDExOlB1bGxSZXF1ZXN0NTkxNjg5ODI3 | 10,686 | fix backend tokenizer args override: key mismatch | {
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"I'm talking with @n1t0 soon to get a better sense of where it might make sense as well yes! Will update then",
"went looking for similar case with this regex `(\\[|\\()\"do_lower_case`, found only one more: 7e42461\r\n\r\nI think this is it, will move onto #10121 once this is merged",
"There does seem to be an... | 1,615 | 1,616 | 1,616 | CONTRIBUTOR | null | # What does this PR do?
Related to #10390
Turns out it was a simple key mismatch - leaving as draft for now just to see the results of the full test suites, but hopeful this will fix the main problem for the related issue. | {
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https://api.github.com/repos/huggingface/transformers/issues/10685 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10685/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10685/comments | https://api.github.com/repos/huggingface/transformers/issues/10685/events | https://github.com/huggingface/transformers/pull/10685 | 830,125,709 | MDExOlB1bGxSZXF1ZXN0NTkxNjg1NjI1 | 10,685 | Distributed barrier before loading model | {
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This PR adds a distributed barrier before the final load when the option `load_best_model_at_end` is selected. This is because a process might get to that point before process 0 has finished saving the checkpoint that is re-loaded, which would result in an error.
Fixes #10666 | {
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"Here's an answer to your questions:\r\n\r\n> 1. Now that I have this model, how can I use it to answer to a \"custom\" question on a specific context? I am assuming that I will need to preprocess the question+context in a way similar to the preprocessing of training dataset, but how can I exactly do that?\r\n\r\nY... | 1,615 | 1,615 | 1,615 | NONE | null | Hello everybody
First of all, I'm kinda new to HF and transformers library, so I apologize if my questions may be be trivial.
I followed the very well explained guide provided [here](https://github.com/huggingface/notebooks/blob/master/examples/question_answering.ipynbl) to fine-tune a pre-trained model (for the ... | {
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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)... | 1,615 | 1,619 | 1,619 | CONTRIBUTOR | null | # What does this PR do?
<!--
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"Hi,\r\n\r\nwould it be possible to ask this question on HuggingFace's [forum](https://discuss.huggingface.co/)? Some people like Sylvain (who created the tutorial you mention) are very active there, and are happy to help you. The authors like to keep Github issues for bugs caused by the Transformers library or fea... | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null | Hello Huggingface,
I try to solve a token classification task where the documents are longer than the model's max length.
I modified the `tokenize_and_align_labels` function from [example token classification notebook](https://github.com/huggingface/notebooks/blob/master/examples/token_classification.ipynb). I set t... | {
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"@stas00 I hear you regarding the installation of dependencies. We are installing every dependency except the main one (PT/TF) on the GPU machine, so I would say most errors are caught.\r\nFurthermore, we are installing these exact dependencies on the CircleCI runs, so I believe we are testing that already on every... | 1,615 | 1,615 | 1,615 | MEMBER | null | This PR updates the GPU-based tests to run on docker images. This:
- Simplifies maintenance
- Horizontal scaling is made much simpler
- Environment can be managed with a single line change (the docker image) hello pytorch 1.3-1.7 tests!
- Setups a notification service to get alerted when scheduled tests fail.
... | {
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"This is a very weird bug actually and can be reproduced the easiest ass follows:\r\n\r\n```python\r\n#!/usr/bin/env python3\r\nfrom transformers import TFMarianMTModel, MarianMTModel, MarianTokenizer\r\n\r\ntokenizer = MarianTokenizer.from_pretrained(\"Helsinki-NLP/opus-mt-mt-en\")\r\n\r\nmodel_pt = MarianMTModel.... | 1,615 | 1,623 | 1,623 | MEMBER | null | After having uploaded the TF weights of:
- https://huggingface.co/Helsinki-NLP/opus-mt-mt-en/commit/552db365bf294f7a2604fadcedfca0ed5b29bd66
- https://huggingface.co/Helsinki-NLP/opus-mt-en-zh/commit/137ef1a50f7a0eaf22a7d5685d07b66bb670ddd1
- https://huggingface.co/Helsinki-NLP/opus-mt-en-ROMANCE/commit/1854185e5a3... | {
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https://api.github.com/repos/huggingface/transformers/issues/10678 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10678/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10678/comments | https://api.github.com/repos/huggingface/transformers/issues/10678/events | https://github.com/huggingface/transformers/issues/10678 | 829,810,571 | MDU6SXNzdWU4Mjk4MTA1NzE= | 10,678 | T5-base out of memory on one 2080 GPU with batchsize 4, sequence length 100 | {
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"I don't think you should use `torch.cuda.empty_cache()`, as explained on [PyTorch's forum](https://discuss.pytorch.org/t/about-torch-cuda-empty-cache/34232/2), \"This function should not be used by the end-user except in very edge cases.\". \r\n\r\nAlso, you can set `truncation=True`, because currently you're only... | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null | I want to finetune T5 on totto dataset but failed.
This is werid that it is OOM suddenly when it is training about 10% of one epoch.
And before that it is normal. about 3500M.
Very grateful for help! thx!
here is my simple code:
```
import torch
from transformers import T5Tokenizer, T5ForConditionalGeneration... | {
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"I agree with your assessment and your proposed fix, so by all means, please suggest a PR! Thanks!"
] | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 3.0.0-4.3.3
- Platform: macOS
- Python version: 3.9
- PyTorch version (GPU?): n/a
- Tensorflow version (GPU?): n/a
- Using GPU in script?: n/a
- Using distributed or parallel set-up in script?: n/a
### Who can help
I'm not sure who the owner is of hf_argparse... | {
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"@lhoestq If this looks good to you, I can help create a PR. Thanks!",
"Hi !\r\nThis looks like a great solution, feel free to open a PR ! :)",
"Great, thanks! Just made a PR here: https://github.com/huggingface/transformers/pull/10780"
] | 1,615 | 1,617 | 1,617 | 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. -->
~~Make `PreTrainedTokenizer.unique_no_split_tokens` a type `Set[str]`, or use a temporary `Set[str]` variable for adding tokens from `added_tokens.json`.~~
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https://api.github.com/repos/huggingface/transformers/issues/10675 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10675/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10675/comments | https://api.github.com/repos/huggingface/transformers/issues/10675/events | https://github.com/huggingface/transformers/issues/10675 | 829,574,581 | MDU6SXNzdWU4Mjk1NzQ1ODE= | 10,675 | Reformer _pad_to_mult_of_chunk_length seems incorrect | {
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"Hey @fostiropoulos,\r\n\r\nSorry to answer this late - could you provide a code example to reproduce the error? ",
"@patrickvonplaten It would take me time to come up with a full working minimal example in colab. \r\n\r\nHowever you can try a model that you supply only the input_embeds and leave input_ids,posit... | 1,615 | 1,621 | 1,621 | NONE | null | ## Environment info
- `transformers` version: 4.3.3
- Platform: Linux-4.15.0-136-generic-x86_64-with-glibc2.10
- Python version: 3.8.5
- PyTorch version (GPU?): 1.7.1 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: yes
- Using distributed or parallel set-up in script?: no
... | {
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https://api.github.com/repos/huggingface/transformers/issues/10674 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10674/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10674/comments | https://api.github.com/repos/huggingface/transformers/issues/10674/events | https://github.com/huggingface/transformers/issues/10674 | 829,508,078 | MDU6SXNzdWU4Mjk1MDgwNzg= | 10,674 | [trainer] loss = NaN with label_smoothing and full-fp16 eval | {
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"I am unsure what you want me to fix. Yes evaluation in FP16 is not as precise as evaluation in FP32 and results in NaNs more easily, in particular in the loss, that's precisely the reason I was reluctant to add the --fp16_full_eval option.",
"well, first of all I'm reporting this behavior.\r\n\r\nSecondly, it lo... | 1,615 | 1,616 | 1,616 | CONTRIBUTOR | null | It looks like our `--label_smoothing_factor` Trainer's feature doesn't handle fp16 well. It's a problem with the deepspeed zero3 I'm integrating right now, since it evals in fp16, but also can be reproduced with the recently added `--fp16_full_eval` trainer option.
To reproduce:
```
export BS=16; rm -r output_dir;... | {
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https://api.github.com/repos/huggingface/transformers/issues/10673 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10673/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10673/comments | https://api.github.com/repos/huggingface/transformers/issues/10673/events | https://github.com/huggingface/transformers/pull/10673 | 829,488,996 | MDExOlB1bGxSZXF1ZXN0NTkxMTQ2MTQy | 10,673 | Add auto_wrap option in fairscale integration | {
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This PR adds support for the `auto_wrap` function added by fairscale to automatically wrap the model's modules in the `FSDP` container (necessary for ZeRO-DP3).
cc @stas00 So you are informed for when you want to experiment more with fairscale. | {
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"No, `Optional[bool]` are dealt with later on at [this line](https://github.com/huggingface/transformers/blob/master/src/transformers/hf_argparser.py#L101) and need to stay wrapped until then.\r\n\r\nWithout more information on your error it's hard to help find the right fix.",
"Hi @sugger, thank you for the quic... | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null | `TrainingArguments` uses the `Optional[bool]` type for [a couple arguments](https://github.com/huggingface/transformers/blob/master/src/transformers/training_args.py#L443). I ran into the following error when using transformers v4.3.3 with python 3.8:
`"TrainingArguments" TypeError: issubclass() arg 1 must be a cla... | {
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https://api.github.com/repos/huggingface/transformers/issues/10670 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10670/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10670/comments | https://api.github.com/repos/huggingface/transformers/issues/10670/events | https://github.com/huggingface/transformers/pull/10670 | 829,418,897 | MDExOlB1bGxSZXF1ZXN0NTkxMDg4MTA0 | 10,670 | Fix integration slow tests | {
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This PR fixes the following slow tests which are failing because of the change of beahvior in the `Embeddings` layer in PyTorh 1.8. This is done by adding an attention mask to ignore the padding token and checking a slice that does not contain the padding hidden states.
```
tests/test_model... | {
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"followers_url": "https://api.github.com/... | [] | closed | false | null | [] | [] | 1,615 | 1,615 | 1,615 | MEMBER | null | @patrickvonplaten, this test didn't pass. If you can double check that it has the expected outputs, that would be great. The difference I'm seeing on my machine is of 1.1e-4, which is slightly higher than the value proposed here of 1e-4. | {
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"@LysandreJik Added!",
"Very cool, thanks! Will merge once all the tests are green."
] | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null | # What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this w... | {
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`attention_mask` should always be passed for the `S2T` model. This PR fixes the examples in the doc. | {
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"Hi! Do you mind posting the error message with the stacktrace? Thank you!\r\n\r\nPinging @sgugger ",
"Here you go:\r\n```\r\nTraining completed. Do not forget to share your model on huggingface.co/models =)\r\nLoading best model from /mnt/pipeline/636d29be-97f9-458a-8174-70ae425a2a6a/pytorch_model/checkpoint-8 (... | 1,615 | 1,615 | 1,615 | NONE | null | Not sure whether this issue should be posted here or rather in the pytorch repo, please let me know if it is not a transformer issue.
When training LayoutLM with the Trainer in distributed mode for only one epoch, with setting `load_best_model_at_end` to `True`, I get an error when the model is loaded at the end. Ac... | {
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https://api.github.com/repos/huggingface/transformers/issues/10665 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10665/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10665/comments | https://api.github.com/repos/huggingface/transformers/issues/10665/events | https://github.com/huggingface/transformers/pull/10665 | 829,315,758 | MDExOlB1bGxSZXF1ZXN0NTkxMDAwMDI4 | 10,665 | W2v2 test require torch | {
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"@LysandreJik - I'll upload the respective weights today and then check that all these slow tests here work without `from_pt`",
"Uploaded all the TF weights and checked that:\r\n\r\n`RUN_SLOW=1 pytest tests/test_modeling_tf_rag.py`\r\n`RUN_SLOW=1 pytest tests/test_modeling_tf_blenderbot.py` \r\n\r\npass.\r\n\r\nF... | 1,615 | 1,615 | 1,615 | MEMBER | null | Some tests were executed without having torch installed, while they require torch. Namely, all the tests that have a `from_pt=True` requirement require torch to be installed.
This is a draft PR as several of the requirements to merge this PR are not met:
- The Marian models do not have their tensorflow variant avai... | {
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https://api.github.com/repos/huggingface/transformers/issues/10663 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10663/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10663/comments | https://api.github.com/repos/huggingface/transformers/issues/10663/events | https://github.com/huggingface/transformers/pull/10663 | 829,307,485 | MDExOlB1bGxSZXF1ZXN0NTkwOTkzMDYz | 10,663 | Onnx fix test | {
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"Merging now to rebase the slow tests and re-run them."
] | 1,615 | 1,615 | 1,615 | MEMBER | null | GPT2 `past_keys_values` format seems to have changed since last time I checked, now exporting for each layer tuple with 2 elements.
PyTorch's ONNX exporter doesn't seem to handle this format, so it was crashing with an error.
The PR assumes we don't currently support exporting `past_keys_values` for GPT2 and then... | {
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"@patil-suraj, you must have meant `1.4.12` \r\n"
] | 1,615 | 1,615 | 1,615 | MEMBER | null | The `_tests_requirements.txt` require an install of sacrebleu without any version specified. However, some `sacrebleu` versions don't have the same API. I've had problems with version `1.2.10`, and @lhoestq confirmed the issue is not present in `1.4.12`.
The error was the following:
```
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cc @patrickvonplaten (Marian) and @sgugger (author of the recent changes) | {
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"Thanks a lot for fixing that issue!"
] | 1,615 | 1,615 | 1,615 | CONTRIBUTOR | null |
## Who can review?
- trainer: @sgugger
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https://api.github.com/repos/huggingface/transformers/issues/10659 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10659/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10659/comments | https://api.github.com/repos/huggingface/transformers/issues/10659/events | https://github.com/huggingface/transformers/issues/10659 | 829,246,421 | MDU6SXNzdWU4MjkyNDY0MjE= | 10,659 | How to use deepspeed finetune RAG? | {
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"Thank you for your kind words, @qixintechnology \r\n\r\nI haven't tried it with RAG, but I don't see any reason why it shouldn't work - if you encounter any problems please open a specific issue with details so that we could reproduce it. "
] | 1,615 | 1,615 | 1,615 | NONE | null | Hi Stas!@stas00 Thanks for your great work! I have a question that is it possible to use deepspeed finetune RAG (finetune_rag.py)? Thanks! | {
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"@patrickvonplaten , @LysandreJik",
"Also pinging @stas00 here - does it make sense to add parallelize ability to GPT2DoubleHeadsModel?",
"If it's being used then yes since `GPT2LMHeadModel` has it.",
"@alexorona, do you want to take a look at this?",
"@stas00 yeah, so I've been using the `GPT2DoubleHeadsMo... | 1,615 | 1,616 | 1,615 | CONTRIBUTOR | null | # What does this PR do?
GPT2DoubleHeadsModel made parallelizable; it is also reflected in the test_modeling_gpt2.py suite
<!--
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 gr... | {
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Was it a choice not to add these to the tokenizer auto, or is it because that's not covered in the template? | {
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https://api.github.com/repos/huggingface/transformers/issues/10656 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10656/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10656/comments | https://api.github.com/repos/huggingface/transformers/issues/10656/events | https://github.com/huggingface/transformers/pull/10656 | 829,195,864 | MDExOlB1bGxSZXF1ZXN0NTkwODk5NzQx | 10,656 | Fix broken link | {
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Fixes a broken link in model_doc/pegasus
Link was pointing to: https://github.com/huggingface/transformers/blob/master/examples/seq2seq/finetune_pegasus_xsum.sh
File had been moved to: https://github.com/huggingface/transformers/blob/master/examples/research_projects/seq2seq-distillatio... | {
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"Hi @gagy3798 \r\n\r\nI couldn't reproduce the issue on master and with the latest pypi version as well. What is your transformers version? \r\n(please always make sure to post the env info when opening an issue)",
"Hi @patil-suraj \r\n\r\nplease try it on this colab https://colab.research.google.com/drive/1z9UtS... | 1,615 | 1,615 | 1,615 | NONE | null | ## Environment info
- colab.research.google.com
### Who can help
@patrickvonplaten
Models:
- MarianMT
Examples:
https://huggingface.co/transformers/model_doc/marian.html
## Information
I'm trying to run example code in colab but it fails
`from transformers import MarianMTModel, MarianTokenizer
src_... | {
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https://api.github.com/repos/huggingface/transformers/issues/10654 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10654/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10654/comments | https://api.github.com/repos/huggingface/transformers/issues/10654/events | https://github.com/huggingface/transformers/issues/10654 | 829,158,624 | MDU6SXNzdWU4MjkxNTg2MjQ= | 10,654 | Allow private model hosting and resolution | {
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"I think it's a brilliant idea. \r\n\r\nSo just to validate I understood your proposal correclty, in addition to checking the usual places, it'll first check the env var `HUGGINGFACE_CO_PREFIX` and join it with `model_path` and check if it's available - and if not proceed with the normal algorithm.\r\n\r\nSo in you... | 1,615 | 1,619 | 1,619 | CONTRIBUTOR | null | # 🚀 Feature request
It would be great to provide model hosting and automatic naming resolution on remote storage outside of HF hub/infra. Currently, it is possible to store a model on, say, S3 and resolve it via AutoModel and AutoConfig. However, in this case, a user has to explicitly specify the full path to the c... | {
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https://api.github.com/repos/huggingface/transformers/issues/10653 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10653/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10653/comments | https://api.github.com/repos/huggingface/transformers/issues/10653/events | https://github.com/huggingface/transformers/pull/10653 | 829,156,823 | MDExOlB1bGxSZXF1ZXN0NTkwODY3MzYz | 10,653 | Fix Longformer tokenizer filename | {
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https://api.github.com/repos/huggingface/transformers/issues/10652 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10652/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10652/comments | https://api.github.com/repos/huggingface/transformers/issues/10652/events | https://github.com/huggingface/transformers/issues/10652 | 829,133,805 | MDU6SXNzdWU4MjkxMzM4MDU= | 10,652 | Infernal tokenizer loading trained | {
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"The tokenizers library powers the fast tokenizers, not the Python \"slow\" tokenizers. As there is no fast tokenizer for deberta, you can't use the tokenizers library for that model.\r\n\r\nYou can check which tokenizers have a version backed by the Tokenizers library in [this table](https://huggingface.co/transfo... | 1,615 | 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.dev0
- Platform: Ubuntu 18
- Python version: 3.7
- PyTorch version (GPU?): 1.7.1 (YES)
- Tensorflow ver... | {
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https://api.github.com/repos/huggingface/transformers/issues/10651 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10651/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10651/comments | https://api.github.com/repos/huggingface/transformers/issues/10651/events | https://github.com/huggingface/transformers/pull/10651 | 829,124,492 | MDExOlB1bGxSZXF1ZXN0NTkwODQwMjM5 | 10,651 | added support for exporting of T5 models to onnx with past_key_values. | {
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"@patrickvonplaten, @patil-suraj any updates on this PR or [10645](https://github.com/huggingface/transformers/issues/10645) issue?",
"@mfuntowicz or @Narsil do you have 2min to give your feedback on this maybe? :-)",
"+1 for this",
"+1, this is needed for fastT5",
"Sorry, I failed to see the first mention... | 1,615 | 1,619 | 1,619 | CONTRIBUTOR | null | # What does this PR do?
>by applying this fix I was able to create **[fastT5](https://pypi.org/project/fastt5/)** library. which increases the T5 model inference speed up to 5x. for more details check out my [GitHub](https://github.com/Ki6an/fastT5) repo.
addressing [this ](https://github.com/huggingface/transf... | {
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https://api.github.com/repos/huggingface/transformers/issues/10650 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10650/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10650/comments | https://api.github.com/repos/huggingface/transformers/issues/10650/events | https://github.com/huggingface/transformers/issues/10650 | 829,114,161 | MDU6SXNzdWU4MjkxMTQxNjE= | 10,650 | DistilBertTokenizerFast ignores "do_lower_case=False" parameter | {
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"Hi @PierceEigirthon! Thanks for submitting, we're aware of this bug, it's related to #10390 and on my backlog",
"I'll close this one as duplicate, you'll be able to follow progress on #10390 ;) "
] | 1,615 | 1,615 | 1,615 | NONE | null | Hi, hope all is well :)
It looks like DistilBertTokenizerFast doesn't take do_lower_case into account.
```
from transformers import DistilBertTokenizerFast, DistilBertTokenizer
PRE_TRAINED_MODEL_NAME = "distilbert-base-uncased"
tokenizer_f = DistilBertTokenizerFast.from_pretrained(PRE_TRAINED_MODEL_NAME, do... | {
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"I think I may have been an idiot; shortly after posting this I found that instead of `padding=True` I should set `padding='max_length'`. Woops."
] | 1,615 | 1,615 | 1,615 | NONE | null | I'm taking a pre-trained pegasus model (specifically, google/pegasus-cnn_dailymail, and I'm using Huggingface transformers through Pytorch) and I want to finetune it on my own data. This is however quite a large dataset and I've run into the problem of running out of VRAM halfway through training, which because of the ... | {
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So this PR only adds a new doc page and a tiny change in the conversion script.
Check out the new models here: https://huggingface.co/models?search=wav2vec2-large-xlsr | {
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"hi @gyin-ai \r\n\r\nThank you for reporting the issue. The `run_seq2seq.py` currently does not work for encoder-decoder models. This is because the encoder-decoder models expect both `decoder_input_ids` and `labels` whereas the script only passes the `labels`. Which is causing the above error.\r\n\r\nYou could ref... | 1,615 | 1,616 | 1,616 | 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
- blenderbot, bart, marian, pegasus, encoderdecoder, t5: @patrickvonplaten, @patil-suraj
```
p... | {
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https://api.github.com/repos/huggingface/transformers/issues/10645 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10645/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10645/comments | https://api.github.com/repos/huggingface/transformers/issues/10645/events | https://github.com/huggingface/transformers/issues/10645 | 829,011,989 | MDU6SXNzdWU4MjkwMTE5ODk= | 10,645 | export T5 model to onnx with past_key_values | {
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"@LysandreJik @mfuntowicz - how do we deal with ONNX issues currently? ",
"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 guidelin... | 1,615 | 1,619 | 1,619 | CONTRIBUTOR | null | ## Environment info
- `transformers` version: 4.3.3
- torch version 1.7.0
- Platform: Linux-4.19.112+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.10
- PyTorch version (GPU?): 1.7.0 (False)
- Tensorflow version (GPU?): 2.4.1 (False)
- Using GPU in script?: <fill in>
- Using distributed or parallel set-... | {
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https://api.github.com/repos/huggingface/transformers/issues/10644 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10644/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10644/comments | https://api.github.com/repos/huggingface/transformers/issues/10644/events | https://github.com/huggingface/transformers/pull/10644 | 829,006,202 | MDExOlB1bGxSZXF1ZXN0NTkwNzQxNDUx | 10,644 | Numeracy | {
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<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this w... | {
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https://api.github.com/repos/huggingface/transformers/issues/10643 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10643/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10643/comments | https://api.github.com/repos/huggingface/transformers/issues/10643/events | https://github.com/huggingface/transformers/issues/10643 | 828,954,067 | MDU6SXNzdWU4Mjg5NTQwNjc= | 10,643 | Space token cannot be add when is_split_into_words = True | {
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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)... | 1,615 | 1,619 | 1,619 | NONE | null | for example,
```python
>>> tokenizer = BertTokenizer.from_pretrained('bert-base-chinese')
>>> tokenizer.add_tokens(' ')
1
```
```python
>>> tokenizer.encode('你好 世界', add_special_tokens=False)
[872, 1962, 21128, 686, 4518]
>>> tokenizer.encode(['你','好',' ', '世', '界'], is_split_into_words=True, add_special_to... | {
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https://api.github.com/repos/huggingface/transformers/issues/10642 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10642/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10642/comments | https://api.github.com/repos/huggingface/transformers/issues/10642/events | https://github.com/huggingface/transformers/issues/10642 | 828,880,311 | MDU6SXNzdWU4Mjg4ODAzMTE= | 10,642 | Unable To Load Pretrained Longformer Models' Tokenizers | {
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"Indeed, I can reproduce and traced it back to https://github.com/huggingface/transformers/issues/10624. Investigating!",
"Found the issue, opening a PR shortly.",
"It should now be fixed on `master`. Thanks a lot for using the `master` branch and letting us know of the issue!"
] | 1,615 | 1,615 | 1,615 | NONE | null | ## Environment info
- `transformers` version: 4.4.0.dev0
- Platform: Windows
- Python version : 3.7.10
- Using GPU in script?: Issue is with both
- Using distributed or parallel set-up in script?: Single device
@patrickvonplaten (because the issue is with longformers)
@LysandreJik (because the iss... | {
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https://api.github.com/repos/huggingface/transformers/issues/10641 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10641/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10641/comments | https://api.github.com/repos/huggingface/transformers/issues/10641/events | https://github.com/huggingface/transformers/issues/10641 | 828,871,639 | MDU6SXNzdWU4Mjg4NzE2Mzk= | 10,641 | Unable to reduce time in summarization! | {
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"Hello!\r\n\r\nThe generation part of TensorFlow can only be run on eagermode, hence doesn't matter how you execute it, you will not be able to run it \"fast\". It is planned to bring a graph execution for the generation, but no ETA yet. Sorry for the inconvenience."
] | 1,615 | 1,616 | 1,616 | 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: `t5-large`
- Platform: Amazon Sagemaker
- Python version: 3.7
- Tensorflow version (GPU?):2.3
- Using dis... | {
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https://api.github.com/repos/huggingface/transformers/issues/10640 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10640/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10640/comments | https://api.github.com/repos/huggingface/transformers/issues/10640/events | https://github.com/huggingface/transformers/issues/10640 | 828,830,142 | MDU6SXNzdWU4Mjg4MzAxNDI= | 10,640 | Nonetype when using deepspeed | {
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"Hi! I think the error you're looking for is actually a bit above to the error you're mentioning, namely:\r\n```\r\nRuntimeError: [enforce fail at CPUAllocator.cpp:67] . DefaultCPUAllocator: can't allocate memory: you tried to allocate 2329531392 bytes. Error code 12 (Cannot allocate memory)\r\n```\r\nwhich would i... | 1,615 | 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: 4.3.3
- Platform: linux
- Python version: 3.7
- PyTorch version (GPU?): 1.8
- Tensorflow version (GPU?): - ... | {
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https://api.github.com/repos/huggingface/transformers/issues/10639 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10639/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10639/comments | https://api.github.com/repos/huggingface/transformers/issues/10639/events | https://github.com/huggingface/transformers/issues/10639 | 828,788,589 | MDU6SXNzdWU4Mjg3ODg1ODk= | 10,639 | Support Quantization Aware Fine-tuning in all models (pytorch) | {
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"Hello! Would [I-BERT](https://huggingface.co/transformers/master/model_doc/ibert.html), available on `master` and contributed by @kssteven418 be of interest?",
"@LysandreJik, Thanks for the useful reference. I guess the i-BERT model has manually implemented the architectural components (kernels, int8 layer norm ... | 1,615 | 1,624 | 1,619 | NONE | null | # 🚀 Feature request
Pytorch supports mimicking quantization errors while training the models.
Here is the [tutorial](https://pytorch.org/tutorials/recipes/quantization.html#quantization-aware-training) on this. For our NLP transformers, it requires a "fake quantization" operation to be done on the embeddings. I f... | {
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https://api.github.com/repos/huggingface/transformers/issues/10638 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/10638/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/10638/comments | https://api.github.com/repos/huggingface/transformers/issues/10638/events | https://github.com/huggingface/transformers/pull/10638 | 828,651,712 | MDExOlB1bGxSZXF1ZXN0NTkwNDM0MTc5 | 10,638 | Fix decoding score comparison when using logits processors or warpers | {
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"The failing test is `test_90_generation_from_short_input`, which generates \"have you ever heard of sam harris? he is an american singer and songwriter. have you heard of him?\" instead of \"have you ever been to a sam club? it's a great club in the south.\" or \"have you ever heard of sam harris? he's an american... | 1,615 | 1,666 | 1,649 | CONTRIBUTOR | null | When doing beam search or other decoding search strategies, the logit scores are normalized (with `log_softmax`) so the comparisons between the beams (hypotheses) are meaningful. However, the logit processors or warpers may change the scores, and thus may not be normalized anymore.
For example, say you have a beam s... | {
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This PR follows up from #10624 and removes the ability to specify a custom vocab file that doesn't lie in the model repo for a tokenizer (which prevents using the versioning system for those tokenizers).
It also cleans up a tiny bit the `from_pretrained` method, mainly:
- use f-strings in... | {
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"@LysandreJik Thanks to you all tests passed! It's ready for an in depth review. \r\nI've already uploaded TF2 model files under:\r\n- https://huggingface.co/atahmasb/tf-layoutlm-base-uncased\r\n- https://huggingface.co/atahmasb/tf-layoutlm-large-uncased\r\n\r\nwould you please copy them to the main repos when the ... | 1,615 | 1,616 | 1,616 | CONTRIBUTOR | 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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