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https://api.github.com/repos/huggingface/transformers/issues/11538 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11538/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11538/comments | https://api.github.com/repos/huggingface/transformers/issues/11538/events | https://github.com/huggingface/transformers/pull/11538 | 873,718,783 | MDExOlB1bGxSZXF1ZXN0NjI4NDYxNTAw | 11,538 | [Wav2vec2] Fixed tokenization mistakes while adding single-char tokens to tokenizer | {
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"Hey @Muktan,\r\n\r\nThanks a lot for working on this! Could you add a test that shows how your code solves the issue? :-)\r\n\r\nIt should be in `tests/test_tokenization_wav2vec2.py`",
"Welcome @patrickvonplaten, I will add a test that shows how the code solves the issue."
] | 1,619 | 1,631 | 1,620 | CONTRIBUTOR | null | # What does this PR do?
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"Hey @stancld,\r\n\r\nOne important thing we should implement before merging is the caching mechanismh similar to how it's done in GPT2: https://github.com/huggingface/transformers/blob/0b0a598452b02278075a75f84b5ca7bb457224ad/src/transformers/models/gpt2/modeling_flax_gpt2.py#L139. @patil-suraj, could you help her... | 1,619 | 1,623 | 1,623 | CONTRIBUTOR | null | # What does this PR do?
This PR adds Flax implementation of BART and classes for various downstream tasks. Fixes #11478.
Most of the code is inspired by the Flax implementation of BERT and PyTorch implementation of BART.
From Suraj:
A couple of important points to note:
- The seq2seq API is slightly differ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11536 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11536/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11536/comments | https://api.github.com/repos/huggingface/transformers/issues/11536/events | https://github.com/huggingface/transformers/issues/11536 | 873,587,853 | MDU6SXNzdWU4NzM1ODc4NTM= | 11,536 | Adafactor gives RuntimeError: tensors must be 2-D | {
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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)... | 1,619 | 1,639 | 1,639 | NONE | null | ## Environment info
- `transformers` version: 4.2.2 (also tried with the latest version v.4.5.1)
- Platform: Linux-4.4.0-1127-aws-x86_64-with-debian-stretch-sid
- Python version: 3.6.13
- PyTorch version (GPU?): 1.7.1 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: True
- Using dis... | {
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https://api.github.com/repos/huggingface/transformers/issues/11535 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11535/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11535/comments | https://api.github.com/repos/huggingface/transformers/issues/11535/events | https://github.com/huggingface/transformers/pull/11535 | 873,585,086 | MDExOlB1bGxSZXF1ZXN0NjI4MzcyODMw | 11,535 | Vectorized Numpy based functions to Torch based Functions for SpecAugment. | {
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"Following are the average test results for the `_compute_mask_indices` function when ran 100 times. Each X.1 subtest case is calculated with `attention_mask = None` and each X.2 subtest case is calculated with `attention_mask` calculated with the following code:\r\n```\r\nattention_mask = torch.ones((batch_size, s... | 1,619 | 1,620 | 1,620 | 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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https://api.github.com/repos/huggingface/transformers/issues/11534 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11534/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11534/comments | https://api.github.com/repos/huggingface/transformers/issues/11534/events | https://github.com/huggingface/transformers/issues/11534 | 872,941,605 | MDU6SXNzdWU4NzI5NDE2MDU= | 11,534 | How to run transformer model like t5-small, facebook/bart-large-cnn without loading pretrained weights? | {
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"For this you could either initialize a random model, save it and pass it's path as `model_name_or_path` arg.\r\nOr modify the script to create a random model instead of pre-trained. i.e to init the model use\r\n\r\n```\r\nmodel = AutoModelForSeq2SeqLM(config)\r\n```\r\ninstead of using `.from_pretrained`.",
"> F... | 1,619 | 1,623 | 1,623 | NONE | null | Same with the title. When using run_summarization.py, how to run transformer models like t5-small, facebook/bart-large-cnn without loading pre-trained weights? I only want to train their original model architecture without pre-trained model. Thanks! | {
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https://api.github.com/repos/huggingface/transformers/issues/11533 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11533/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11533/comments | https://api.github.com/repos/huggingface/transformers/issues/11533/events | https://github.com/huggingface/transformers/pull/11533 | 872,848,920 | MDExOlB1bGxSZXF1ZXN0NjI3NzE0ODk2 | 11,533 | Update training tutorial | {
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"Re: freezing layers, someone pointed me to your answer here as well: From your deepspeed talk: https://youtu.be/RG-yV5zgqjQ?t=2450\n\nI guess it's still a bit counterintuitive that the randomly initialized head doesn't cause havoc on the weights of base layers? Just to make sure, it's not that you unfreeze the wh... | 1,619 | 1,620 | 1,620 | COLLABORATOR | null | # What does this PR do?
This PRs rewrites the training tutorial that needed a bit of a refresher. It uses a simple example on the IMDB dataset (for basic text classification) with fine-tuning using:
- Trainer
- Keras
- Raw training loop in PyTorch
One last section with the raw training loop in TensorFlow could... | {
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"@n1t0 might be knowledgeable about this :)",
"@n1t0 depending where huggingface.co is hosted, solving this issue may just boil down to turning on dual-stack support in the hosting provider's console.",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this ... | 1,619 | 1,700 | 1,629 | NONE | null | In certain cases (such as [1]), users only have access to the internet via IPv6. Unfortunately huggingface.co (or the domain hosting the files) does not have AAAA records and is not reachable from IPv6, causing `ValueError: Connection error, and we cannot find the requested files in the cached path. Please try again or... | {
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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)... | 1,619 | 1,695 | 1,695 | NONE | null | ## Environment info
- `transformers` version: 4.5.1
- Platform: Linux-3.10.0-957.5.1.el7.x86_64-x86_64-with-centos-7.6.1810-Core
- Python version: 3.6.13
- PyTorch version (GPU?): 1.7.1 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: No
- Using distributed or parallel set-up in s... | {
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https://api.github.com/repos/huggingface/transformers/issues/11530 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11530/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11530/comments | https://api.github.com/repos/huggingface/transformers/issues/11530/events | https://github.com/huggingface/transformers/issues/11530 | 872,755,969 | MDU6SXNzdWU4NzI3NTU5Njk= | 11,530 | generate text with inputs_embeds (instead of input_ids) for T5. | {
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"One possible solution is to get the `encoder_outputs` by passing `inputs_embeds` to `encoder` and then passing that `encoder_outputs` to `.generate`, so for example\r\n\r\n```\r\nwith torch.no_grad():\r\n encoder_outputs = model.get_encoder()(inputs_embeds=input_embeds)\r\n\r\ngen_ids = model.generate(input_ids... | 1,619 | 1,621 | 1,621 | NONE | null | model.generate() supports input_ids only
```
outs = model.model.generate(input_ids=batch['source_ids'],
attention_mask=batch['source_mask'],
output_scores=True,
max_length=model.model_arguments.max_output_... | {
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"Any kind soul please add fast tokenizer for Deberta V2. Would be really helpful and thanks in advance!",
"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 f... | 1,619 | 1,623 | 1,623 | CONTRIBUTOR | null | Fast tokenizers for deberta models were requested in #10498. For the deberta (v1) model, they were implemented in #11387.
Deberta v2 fast tokenizers are yet to be implemented. | {
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https://api.github.com/repos/huggingface/transformers/issues/11528 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11528/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11528/comments | https://api.github.com/repos/huggingface/transformers/issues/11528/events | https://github.com/huggingface/transformers/pull/11528 | 872,471,855 | MDExOlB1bGxSZXF1ZXN0NjI3Mzc1OTQz | 11,528 | Adds Flax BERT finetuning example on GLUE | {
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Adds Flax BERT finetuning example which finetunes on one of the GLUE tasks.
I evaluated all tasks 5 times and added the average runs, the best run. and stdev in a table in the README. I used the seed of the best run as the default.
I also ran all experiments on three devices: 8 Cloud TP... | {
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https://api.github.com/repos/huggingface/transformers/issues/11527 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11527/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11527/comments | https://api.github.com/repos/huggingface/transformers/issues/11527/events | https://github.com/huggingface/transformers/pull/11527 | 872,444,398 | MDExOlB1bGxSZXF1ZXN0NjI3MzUxOTMw | 11,527 | Run model templates on master | {
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https://api.github.com/repos/huggingface/transformers/issues/11526 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11526/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11526/comments | https://api.github.com/repos/huggingface/transformers/issues/11526/events | https://github.com/huggingface/transformers/pull/11526 | 872,433,763 | MDExOlB1bGxSZXF1ZXN0NjI3MzQyODMy | 11,526 | Add Stas and Suraj as authors | {
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"Thank you, Sylvain ❤️ ",
"Thank you, guys! That feels good!"
] | 1,619 | 1,619 | 1,619 | COLLABORATOR | null | # What does this PR do?
In recognition of all your hard work and the amazing stuff you've added to the lib, adding @stas00 and @patil-suraj to the authors of the lib 🤗 | {
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https://api.github.com/repos/huggingface/transformers/issues/11525 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11525/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11525/comments | https://api.github.com/repos/huggingface/transformers/issues/11525/events | https://github.com/huggingface/transformers/pull/11525 | 872,340,486 | MDExOlB1bGxSZXF1ZXN0NjI3MjYyNTM4 | 11,525 | Adding support for `pipeline("automatic-speech-recognition")`. | {
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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)... | 1,619 | 1,625 | 1,625 | CONTRIBUTOR | null | # What does this PR do?
Implements the default load logic to make `AutomaticSpeechRecognitionPipeline` work
like other pipelines with `pipeline(task="automatic-speech-recognition", ...)`.
The main issue with current implementation is `"config"` choice for AutoModel. It would be great to have the
possibility to have s... | {
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https://api.github.com/repos/huggingface/transformers/issues/11524 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11524/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11524/comments | https://api.github.com/repos/huggingface/transformers/issues/11524/events | https://github.com/huggingface/transformers/pull/11524 | 872,264,297 | MDExOlB1bGxSZXF1ZXN0NjI3MTk2NDI5 | 11,524 | [examples, translation/summerization] resize token embeds | {
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Resize token embedding in the summarization and translation examples.
Fixes #11518 | {
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https://api.github.com/repos/huggingface/transformers/issues/11523 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11523/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11523/comments | https://api.github.com/repos/huggingface/transformers/issues/11523/events | https://github.com/huggingface/transformers/issues/11523 | 872,202,929 | MDU6SXNzdWU4NzIyMDI5Mjk= | 11,523 | Distributed multi-node support for CPU cluster | {
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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)... | 1,619 | 1,623 | 1,623 | NONE | null | # 🚀 Feature request
## Motivation
Current distributed run supports only multi-GPU/TPU run. This feature requests adding support for distributed CPU runs using MPI/GLOO or recently added custom backend e.g. intel oneCCL backend using [torch-ccl](https://github.com/intel/torch-ccl) plugin.
## Your contribution
A... | {
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https://api.github.com/repos/huggingface/transformers/issues/11522 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11522/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11522/comments | https://api.github.com/repos/huggingface/transformers/issues/11522/events | https://github.com/huggingface/transformers/issues/11522 | 872,175,464 | MDU6SXNzdWU4NzIxNzU0NjQ= | 11,522 | Compute probability of target sentences given an input | {
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"Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.\r\nCould you ask your question on the [forum](https://discusss.huggingface.co) instead?\r\n\r\nThanks!",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this sti... | 1,619 | 1,623 | 1,623 | NONE | null | I need to test the probabilities that the model would produce certain outputs. Let me give you an example:
I have a source sentence X, and several possible target sentences Y1, Y2, Y3, Y4 , ...
I want to know if I can compute the probability that the model would give to each of the translation Y, given X.
Is the... | {
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https://api.github.com/repos/huggingface/transformers/issues/11521 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11521/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11521/comments | https://api.github.com/repos/huggingface/transformers/issues/11521/events | https://github.com/huggingface/transformers/issues/11521 | 872,172,201 | MDU6SXNzdWU4NzIxNzIyMDE= | 11,521 | How to set up a custom tokenizer for distilbart | {
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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!"
] | 1,619 | 1,620 | 1,620 | NONE | null | Hi, I am currently using the distillbart. I pretrained a bart-large model with my own Chinese corpus and I just simply map each character to an id when I do the pre-training. In the distillition.py, the path or name of the tokenizer should be defined. My question is how can I build a custom tokenizer class which can be... | {
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https://api.github.com/repos/huggingface/transformers/issues/11520 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11520/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11520/comments | https://api.github.com/repos/huggingface/transformers/issues/11520/events | https://github.com/huggingface/transformers/pull/11520 | 872,131,589 | MDExOlB1bGxSZXF1ZXN0NjI3MDg1MTY1 | 11,520 | [Master] Make style | {
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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/11519 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11519/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11519/comments | https://api.github.com/repos/huggingface/transformers/issues/11519/events | https://github.com/huggingface/transformers/issues/11519 | 872,101,481 | MDU6SXNzdWU4NzIxMDE0ODE= | 11,519 | RoBERTa adds two sep tokens | {
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"> Is this intentional? \r\n\r\nYes. It is in line with the original implementation. (Check [link](https://github.com/pytorch/fairseq/blob/master/examples/roberta/README.md) for more information).\r\n\r\n> I ran into two issues - this, and the fact that as per the comment \"RoBERTa does not make use of token type i... | 1,619 | 1,619 | 1,619 | NONE | null | ## Environment info
- `transformers` version: 4.5.1
- Platform: Linux-5.4.0-72-generic-x86_64-with-debian-bullseye-sid
- Python version: 3.7.6
- PyTorch version (GPU?): NA
- Tensorflow version (GPU?): NA
- Using GPU in script?: NA
- Using distributed or parallel set-up in script?: NA
## Information
I'm... | {
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https://api.github.com/repos/huggingface/transformers/issues/11518 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11518/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11518/comments | https://api.github.com/repos/huggingface/transformers/issues/11518/events | https://github.com/huggingface/transformers/issues/11518 | 871,864,329 | MDU6SXNzdWU4NzE4NjQzMjk= | 11,518 | BART summarization, tokenizer not working | {
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"Did you resize the embeddings after adding the new tokens ? To resize the embedding \r\n```python3\r\nmodel.resize_token_embeddings(len(tokenizer))\r\n```",
"> Did you resize the embeddings after adding the new tokens ? To resize the embedding\r\n> \r\n> ```python\r\n> model.resize_token_embeddings(len(tokenizer... | 1,619 | 1,619 | 1,619 | NONE | null | @patil-suraj
When I am running pytorch/summarization, the logs are as below:
```
Adding AddedToken(content='<s>', single_word=False, lstrip=False, rstrip=False, normalized=True) to the vocabulary
Adding AddedToken(content='</s>', single_word=False, lstrip=False, rstrip=False, normalized=True) to the vocabulary
Ad... | {
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https://api.github.com/repos/huggingface/transformers/issues/11517 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11517/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11517/comments | https://api.github.com/repos/huggingface/transformers/issues/11517/events | https://github.com/huggingface/transformers/pull/11517 | 871,300,830 | MDExOlB1bGxSZXF1ZXN0NjI2MzQwMjk4 | 11,517 | rag import not on windows | {
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"There's a lot of changes relative to `black` - could you install the version the repo uses with:\r\n```\r\npip install -U -e .[quality]\r\n```\r\n?\r\n\r\n\r\nAlso I would put this behind a `if is_faiss_available():` rather than a platform check. Could you show the error you obtain on Windows when using an auto mo... | 1,619 | 1,619 | 1,619 | CONTRIBUTOR | null | just a small fix to use automodels on windows
faiss is not available on windows, and RAG is using faiss, so the import fails | {
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https://api.github.com/repos/huggingface/transformers/issues/11516 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11516/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11516/comments | https://api.github.com/repos/huggingface/transformers/issues/11516/events | https://github.com/huggingface/transformers/issues/11516 | 871,265,447 | MDU6SXNzdWU4NzEyNjU0NDc= | 11,516 | Run_summarization not working for mbart50 | {
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"Hi @Aniruddha-JU \r\n\r\nRight now the `run_summarization.py` does not support fine-tuning mBART for summarization, we need to set the proper language tokens for mBART50. For now, you could easily modify the script to adapt it for mBART50 by setting the correct language tokens, as is done in the translation exampl... | 1,619 | 1,638 | 1,623 | NONE | null | - `transformers` 4.5.0
- Platform: linux:
- Python version: 1.7.1
- PyTorch version (GPU?):
- Tensorflow version (GPU?):
- Using GPU in script?:
- Using distributed or parallel set-up in script?:
### Who can help
@patil-suraj @LysandreJik
Models: mbart
I am running the run_summarization.py class usi... | {
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https://api.github.com/repos/huggingface/transformers/issues/11515 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11515/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11515/comments | https://api.github.com/repos/huggingface/transformers/issues/11515/events | https://github.com/huggingface/transformers/issues/11515 | 871,252,650 | MDU6SXNzdWU4NzEyNTI2NTA= | 11,515 | Issues with TFGPT2ForSequenceClassification | {
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"Thanks for the very in-detail issue description! @Rocketknight1 do you maybe want to give it a try here? Otherwise I'm happy to take a look :-)",
"Taking a look now!",
"Hi @cytwill, can you share a few lines of the data you're loading as X_train and y_train? If it's a private dataset, you can replace the text ... | 1,619 | 1,645 | 1,623 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.5.1
- Platform: Google Colab
- Python version:
- PyTorch version (GPU?):
- Tensorflow version (GPU?): 2.4... | {
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https://api.github.com/repos/huggingface/transformers/issues/11514 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11514/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11514/comments | https://api.github.com/repos/huggingface/transformers/issues/11514/events | https://github.com/huggingface/transformers/pull/11514 | 871,211,448 | MDExOlB1bGxSZXF1ZXN0NjI2MjY4Mjk3 | 11,514 | solved coefficient issue for the TF version of gelu_fast | {
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This PR solves a bug in the Tensorflow version of gelu_fast: the two coefficients being used to compute the approximation were swapped, making the computation inaccurate. | {
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https://api.github.com/repos/huggingface/transformers/issues/11513 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11513/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11513/comments | https://api.github.com/repos/huggingface/transformers/issues/11513/events | https://github.com/huggingface/transformers/pull/11513 | 871,204,356 | MDExOlB1bGxSZXF1ZXN0NjI2MjYyNTQ1 | 11,513 | Improve task summary docs | {
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"heh not sure why CI failed, just see this error message\r\n\r\n> Received \"killed\" signal",
"@sgugger sorry for the double comment (I commented on an old commit by accident), what I meant to say I made the changes you suggested, LMK if this does a good job of conveying the message!",
"Thanks again!"
] | 1,619 | 1,619 | 1,619 | CONTRIBUTOR | null | This PR makes various improvements to the [Summary of Tasks](file:///Users/hamelsmu/github/transformers/docs/_build/html/task_summary.html#named-entity-recognition) docs.
Instead of providing a summary of changes at the top, I added a comment to all my changes below to give more context behind why I suggested the ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11512 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11512/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11512/comments | https://api.github.com/repos/huggingface/transformers/issues/11512/events | https://github.com/huggingface/transformers/issues/11512 | 871,202,837 | MDU6SXNzdWU4NzEyMDI4Mzc= | 11,512 | Piece A | {
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"Could you elaborate more? ",
"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/transform... | 1,619 | 1,623 | 1,623 | NONE | null | {
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https://api.github.com/repos/huggingface/transformers/issues/11511 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11511/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11511/comments | https://api.github.com/repos/huggingface/transformers/issues/11511/events | https://github.com/huggingface/transformers/pull/11511 | 871,182,458 | MDExOlB1bGxSZXF1ZXN0NjI2MjQzNzI5 | 11,511 | Fix do_eval default value in training_args.py | {
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According to <do_eval> description, when <evaluation_strategy> is different from 'no' it will be set 'True'.
But the <do_eval>'s defualt setting is None. So, this code can't be executed unless the the user set <do_eval = False>.
`if self.do_eval is False and self.evaluation_strategy != In... | {
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https://api.github.com/repos/huggingface/transformers/issues/11510 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11510/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11510/comments | https://api.github.com/repos/huggingface/transformers/issues/11510/events | https://github.com/huggingface/transformers/pull/11510 | 871,173,953 | MDExOlB1bGxSZXF1ZXN0NjI2MjM2NzQ5 | 11,510 | [Examples] Added support for test-file in QA examples with no trainer | {
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"One More thing i want to mention is below code,\r\nhttps://github.com/huggingface/transformers/blob/ad1f7bef13f03287af00f819605d696138a5e6ec/examples/pytorch/question-answering/run_qa_no_trainer.py#L543-L547\r\ni changed to\r\n```python\r\n eval_dataset.set_format(type=\"torch\", columns=[\"attention_mask\", \"... | 1,619 | 1,648 | 1,619 | CONTRIBUTOR | null | # What does this PR do?
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md#start-contributing-pull-requests),
Pull R... | {
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https://api.github.com/repos/huggingface/transformers/issues/11509 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11509/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11509/comments | https://api.github.com/repos/huggingface/transformers/issues/11509/events | https://github.com/huggingface/transformers/issues/11509 | 871,054,857 | MDU6SXNzdWU4NzEwNTQ4NTc= | 11,509 | I-BERT: expected str, bytes or os.PathLike object, not NoneType | {
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"Hi! I believe this checkpoint does not have a slow tokenizer, only a fast tokenizer. Can you try with:\r\n\r\n```py\r\nfrom transformers import RobertaTokenizerFast\r\ntokenizer = RobertaTokenizerFast.from_pretrained('kssteven/ibert-roberta-base')\r\n```",
"Thank you! It loaded the tokenizer without showing an e... | 1,619 | 1,620 | 1,620 | NONE | null | Hi, I have an issue when running this code provided by the HF documentation:
>>> from transformers import RobertaTokenizer, IBertForTokenClassification
>>> import torch
>>> tokenizer = RobertaTokenizer.from_pretrained('kssteven/ibert-roberta-base')
When running this i get the following error for the tokenizer:
... | {
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https://api.github.com/repos/huggingface/transformers/issues/11508 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11508/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11508/comments | https://api.github.com/repos/huggingface/transformers/issues/11508/events | https://github.com/huggingface/transformers/issues/11508 | 870,992,704 | MDU6SXNzdWU4NzA5OTI3MDQ= | 11,508 | Help understanding how to build a dataset for language as with the old TextDataset | {
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Hello,
I am trying to load a custom dataset that I will then use for language modeling. The dataset consists of a text file that has a whole document in each line, meaning that eac... | {
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https://api.github.com/repos/huggingface/transformers/issues/11507 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11507/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11507/comments | https://api.github.com/repos/huggingface/transformers/issues/11507/events | https://github.com/huggingface/transformers/issues/11507 | 870,935,455 | MDU6SXNzdWU4NzA5MzU0NTU= | 11,507 | Fine-Tuning TFGPT2LMHeadModel / What to pass to fit | {
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"When I run code supplied by another user from [another issue](https://github.com/huggingface/transformers/issues/2439), which supposedly worked at one point in time, I get a similar dimension mismatch. Is there a golden combination of tf and transformers I am supposed to be using?",
"Ah, the 16 above is the bat... | 1,619 | 1,623 | 1,623 | NONE | null | I am trying to fine-tune this pretrained model on my own data and I can't seem to get the format correct for what the model would like to see as input.
I am using TFGPT2LMHeadModel, GPT2Config and GPT2TokenizerFast.
When I do `model.fit(x,y, epochs=EPOCHS)`,
- If x and y are the outputs of tokenizing on GPT2To... | {
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https://api.github.com/repos/huggingface/transformers/issues/11506 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11506/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11506/comments | https://api.github.com/repos/huggingface/transformers/issues/11506/events | https://github.com/huggingface/transformers/pull/11506 | 870,934,642 | MDExOlB1bGxSZXF1ZXN0NjI2MDQwNjAx | 11,506 | [WIP] Adding DETR | {
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"Thanks for the review, yes you've made it a lot more clear for me now:\r\n* it's only `rgb2id` and `id2rgb` which are used from `panopticapi`, and it's only about 20 lines of code I see now. So indeed, we can just copy that code into the library (and cite the authors).\r\n* however, I think it's still useful to ha... | 1,619 | 1,620 | 1,620 | CONTRIBUTOR | null | # What does this PR do?
I've made quite a lot of progress on implementing HuggingFace's version of [DETR](https://arxiv.org/abs/2005.12872). However, there are some remaining things to be discussed, mainly regarding `DetrFeatureExtractor`, which can be used to prepare images + annotations for the model.
## What ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11505 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11505/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11505/comments | https://api.github.com/repos/huggingface/transformers/issues/11505/events | https://github.com/huggingface/transformers/issues/11505 | 870,934,374 | MDU6SXNzdWU4NzA5MzQzNzQ= | 11,505 | encoder decoder in transformers | {
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"Hi there!\r\n\r\nIt would be nice if you ask such questions on the [forum](https://discuss.huggingface.co/). Use issues to report bugs and for feature requests or anything else that can't be discussed on the forum. Thanks!",
"This issue has been automatically marked as stale because it has not had recent activit... | 1,619 | 1,623 | 1,623 | NONE | null | Thanks for your contribution for EncoderDecoderModel
I want to ask a question about the pool_layer of encoder.
Generally the default 'add_pooling_layer=True' in encoder, while the output of encoder in EncoderDecoder is without pool_layer. Is my understanding correct?
Now i want to add a classification layer in... | {
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https://api.github.com/repos/huggingface/transformers/issues/11504 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11504/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11504/comments | https://api.github.com/repos/huggingface/transformers/issues/11504/events | https://github.com/huggingface/transformers/issues/11504 | 870,805,724 | MDU6SXNzdWU4NzA4MDU3MjQ= | 11,504 | Issue in checkpointing | {
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<!-- 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: 4.6.0
- Platform: -
- Python version: 3.8
- PyTorch version (GPU?): 3.7
- Tensorflow version (GPU?): -
-... | {
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https://api.github.com/repos/huggingface/transformers/issues/11503 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11503/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11503/comments | https://api.github.com/repos/huggingface/transformers/issues/11503/events | https://github.com/huggingface/transformers/pull/11503 | 870,775,203 | MDExOlB1bGxSZXF1ZXN0NjI1OTEyMTI3 | 11,503 | [Examples] Check key exists in datasets first | {
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"Hi @oToToT,\r\nThanks for the PR, The changes seem valid to me. It should be as per changes in this PR.\r\n@sgugger what's your view on these changes?",
"Hi, @sgugger\r\nI'm not familiar with how huggingface do with pull requests, did I miss something to make it be merged?\r\nOr I just need to stay and wait it.\... | 1,619 | 1,620 | 1,620 | CONTRIBUTOR | null | # What does this PR do?
Correctly check the key exists before accessing it in some example scripts. I guess this is probably a mistake when writing example scripts.
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https://api.github.com/repos/huggingface/transformers/issues/11502 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11502/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11502/comments | https://api.github.com/repos/huggingface/transformers/issues/11502/events | https://github.com/huggingface/transformers/pull/11502 | 870,769,716 | MDExOlB1bGxSZXF1ZXN0NjI1OTA3NTk4 | 11,502 | Pin HuggingFace Hub dependency | {
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https://api.github.com/repos/huggingface/transformers/issues/11501 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11501/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11501/comments | https://api.github.com/repos/huggingface/transformers/issues/11501/events | https://github.com/huggingface/transformers/issues/11501 | 870,767,988 | MDU6SXNzdWU4NzA3Njc5ODg= | 11,501 | Penalise n-gram repetition in generated sequences | {
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"Hi @KMFODA \r\n\r\nThe `generate` method already supports penalizing n-gram repetition, this can be done by passing the argument `no_repeat_ngram_size` , if it's passed it will ensure that all n-grams of the given size will only occur once.\r\n\r\nThis however does not mean that the different `num_returned_sequenc... | 1,619 | 1,623 | 1,623 | CONTRIBUTOR | null | # 🚀 Feature request
As per this [forum post](https://discuss.huggingface.co/t/force-decoder-to-avoid-repetition-between-generated-sentences/625) sometimes it's helpful to have a parameter that can increase the diversity amongst different generated sentences. This can be a penalty on the number of repeated n-grams b... | {
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https://api.github.com/repos/huggingface/transformers/issues/11500 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11500/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11500/comments | https://api.github.com/repos/huggingface/transformers/issues/11500/events | https://github.com/huggingface/transformers/issues/11500 | 870,662,283 | MDU6SXNzdWU4NzA2NjIyODM= | 11,500 | not able load model from pipeline NotFound error | {
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"Could you try with the full revision, i.e., `672273686ecedd6fbbd5c0593b17df082ab65e31`?",
"same issues @LysandreJik \r\n\r\n```\r\nmodel = pipeline('sentiment-analysis', model='textattack/bert-base-uncased-yelp-polarity',revision=\"672273686ecedd6fbbd5c0593b17df082ab65e31\")\r\n\r\n\r\n404 Client Error: Not Fou... | 1,619 | 1,623 | 1,623 | NONE | null | I am trying to load textattack ylep model in pipeline but it was saying below error
```
/home/tiru/anaconda3/envs/td-solutions/bin/python /snap/pycharm-community/236/plugins/python-ce/helpers/pydev/pydevconsole.py --mode=client --port=40643
import sys; print('Python %s on %s' % (sys.version, sys.platform))
sys.pa... | {
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https://api.github.com/repos/huggingface/transformers/issues/11499 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11499/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11499/comments | https://api.github.com/repos/huggingface/transformers/issues/11499/events | https://github.com/huggingface/transformers/pull/11499 | 870,458,725 | MDExOlB1bGxSZXF1ZXN0NjI1NjU3ODY3 | 11,499 | [DeepSpeed] fp32 support | {
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"That's correct. \r\n\r\nEarlier I tried to use `cur_version>pre_version` so it'd already work with master version, but then people were reporting bugs because they were on some older master version, so while this is less convenient, it avoids invalid bug reports and saves time to all ;)\r\n\r\n "
] | 1,619 | 1,619 | 1,619 | CONTRIBUTOR | null | Things we need to sync with the upcoming `deepspeed==0.3.16` release:
- `zero.Init` now takes a config as an argument
- fp32-support integration, plus doc and tests
- start troubleshooting section
### Future TODO
will probably do in the next PR:
- switch `from_config()` to perform the same `zero.Init` as `f... | {
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https://api.github.com/repos/huggingface/transformers/issues/11498 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11498/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11498/comments | https://api.github.com/repos/huggingface/transformers/issues/11498/events | https://github.com/huggingface/transformers/pull/11498 | 870,286,838 | MDExOlB1bGxSZXF1ZXN0NjI1NTA3MjM0 | 11,498 | [Flax] Add docstrings & model outputs | {
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<!--
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/11497 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11497/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11497/comments | https://api.github.com/repos/huggingface/transformers/issues/11497/events | https://github.com/huggingface/transformers/pull/11497 | 870,275,534 | MDExOlB1bGxSZXF1ZXN0NjI1NDk3MTcx | 11,497 | Reformat to make code clearer in tokenizer call | {
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"\"unuglify\" -> best branch name ever haha"
] | 1,619 | 1,619 | 1,619 | COLLABORATOR | null | # What does this PR do?
While reviewing a PR on the tokenizer call this morning, I had some trouble parsing what was happening, as black reformatted the tests in a way that is quite unreadable (IMO). This PR fixes that.
No logic is changed, it's just put in a more human-readable way (again maybe this is just me). | {
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It's late so I'd like to do one more pass over everything before merging tomorrow, but I'm opening for reviews before I head off for the evening! | {
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https://api.github.com/repos/huggingface/transformers/issues/11495 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11495/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11495/comments | https://api.github.com/repos/huggingface/transformers/issues/11495/events | https://github.com/huggingface/transformers/issues/11495 | 870,161,899 | MDU6SXNzdWU4NzAxNjE4OTk= | 11,495 | mbart encoder decoder model | {
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"Hey,\r\n\r\nCould you leave more details:\r\n- Your environment\r\n- Your code(or edited so i can try it)\r\n\r\nLooking here:\r\nhttps://huggingface.co/transformers/model_doc/mbart.html?highlight=config#transformers.MBartConfig\r\n\r\nIt doesnt seem to be using hidden_states. Depending how you use the model, you... | 1,619 | 1,623 | 1,623 | NONE | null | Hi,
I've been following [this](https://colab.research.google.com/drive/1WIk2bxglElfZewOHboPFNj8H44_VAyKE?usp=sharing) to implement a bert2bert seq2seq model which works pretty well. Now I would like to change this to mbart (facebook/mbart-large-50) instead of bert.
I'm very new to this, but my assumption was that... | {
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https://api.github.com/repos/huggingface/transformers/issues/11494 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11494/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11494/comments | https://api.github.com/repos/huggingface/transformers/issues/11494/events | https://github.com/huggingface/transformers/pull/11494 | 870,081,172 | MDExOlB1bGxSZXF1ZXN0NjI1MzM3MjMx | 11,494 | correct incorrect dimension comment in Longformer model | {
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- [x ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's... | {
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https://api.github.com/repos/huggingface/transformers/issues/11493 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11493/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11493/comments | https://api.github.com/repos/huggingface/transformers/issues/11493/events | https://github.com/huggingface/transformers/pull/11493 | 870,003,406 | MDExOlB1bGxSZXF1ZXN0NjI1MjcyNjU3 | 11,493 | [Docs] remove paragraph on CI from installation instructions | {
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@julien-c suggested to remove this paragraph in #11479
@sgugger | {
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https://api.github.com/repos/huggingface/transformers/issues/11492 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11492/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11492/comments | https://api.github.com/repos/huggingface/transformers/issues/11492/events | https://github.com/huggingface/transformers/pull/11492 | 869,949,607 | MDExOlB1bGxSZXF1ZXN0NjI1MjI3ODgz | 11,492 | Split checkpoint from model_name_or_path in examples | {
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"Hi guys, just one comment/question from my side: instead of introducing new commandline options (allowing to resume from a checkpoint), what do you think about the following workflow: \r\n\r\na) load the model (with AutoModel)\r\nb) check if the loaded model is from type \"TokenClassification\"\r\n\r\n:thinking: "... | 1,619 | 1,619 | 1,619 | COLLABORATOR | null | # What does this PR do?
There is currently a problem in the way we handle resuming from checkpoint in our PyTorch example scripts with `Trainer`: if the user wants to resume form a specific checkpoint, they have to pass `--model_name_or_path checkpoint_folder` which is a bit counter-intuitive but also poses the prob... | {
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https://api.github.com/repos/huggingface/transformers/issues/11491 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11491/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11491/comments | https://api.github.com/repos/huggingface/transformers/issues/11491/events | https://github.com/huggingface/transformers/issues/11491 | 869,934,434 | MDU6SXNzdWU4Njk5MzQ0MzQ= | 11,491 | Tensorflow “Index out of bound” error when trying to use the TF Longformer transformer in a custom TF network | {
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"I think you should replace `transformer_outputs = transformer[1]` with `transformer_outputs = transformer[0]`. ",
"> I think you should replace `transformer_outputs = transformer[1]` with `transformer_outputs = transformer[0]`.\r\n\r\n@fredo838 Thanks for the reply, yes i have tried this -- in this case the outp... | 1,619 | 1,622 | 1,622 | NONE | null | I am trying to adapt the longformer transformer TF model from huggingface into a bigger three class classification model, i have gotten the model to compile but i cannot run a test example on it. The model and attempted output is as below:
>Environment info
>transformers version: 2.4.1
>Platform: Windows 10
>P... | {
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https://api.github.com/repos/huggingface/transformers/issues/11490 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11490/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11490/comments | https://api.github.com/repos/huggingface/transformers/issues/11490/events | https://github.com/huggingface/transformers/pull/11490 | 869,900,824 | MDExOlB1bGxSZXF1ZXN0NjI1MTg3Mzk5 | 11,490 | add importlib_metadata as dependency as it is required for py<3.8 | {
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"Shouldn't this only be installed for python versions inferior to 3.8?",
"@LysandreJik, thanks for reviewing my PR.\r\n\r\nI think at the moment, we cannot use selectors with `noarch` python packages. Please see warning at - https://docs.conda.io/projects/conda-build/en/latest/resources/define-metadata.html?highl... | 1,619 | 1,620 | 1,620 | CONTRIBUTOR | null | # What does this PR do?
<!--
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https://api.github.com/repos/huggingface/transformers/issues/11489 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11489/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11489/comments | https://api.github.com/repos/huggingface/transformers/issues/11489/events | https://github.com/huggingface/transformers/pull/11489 | 869,837,653 | MDExOlB1bGxSZXF1ZXN0NjI1MTM1NjQx | 11,489 | Update README.md | {
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# What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/11488 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11488/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11488/comments | https://api.github.com/repos/huggingface/transformers/issues/11488/events | https://github.com/huggingface/transformers/issues/11488 | 869,793,715 | MDU6SXNzdWU4Njk3OTM3MTU= | 11,488 | TFLongformerForMaskedMLM example throws ValueError "shapes are incompatible" | {
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"Hi! The model is working fine here, but the problem is that \"[MASK]\" and \"Paris\" are being tokenized as different numbers of tokens, which is where your shape error is coming from. Can you link me to the exact script you got this example from?",
"It's under this headline, here's the permalink: https://huggin... | 1,619 | 1,620 | 1,620 | CONTRIBUTOR | null | An official example of the `TFLongFormerX` page does not work.
## Environment info
- `transformers` version: 2.4.1
- Platform: ubuntu 20.04
- Python version: python3.8
- PyTorch version (GPU?): N/A
- Tensorflow version (GPU?): 2.4.1
- Using GPU in script?: no
- Using distributed or parallel set-up in script?... | {
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https://api.github.com/repos/huggingface/transformers/issues/11487 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11487/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11487/comments | https://api.github.com/repos/huggingface/transformers/issues/11487/events | https://github.com/huggingface/transformers/issues/11487 | 869,688,541 | MDU6SXNzdWU4Njk2ODg1NDE= | 11,487 | Importing problem | {
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"try the newest version 4.6.0.dev0\r\n\r\n\r\n\r\n",
"Could you install `sentencepiece` and try again? The `PegasusTokenizer` is based on the `sentencepiece` library.",
"This issue has been automatical... | 1,619 | 1,639 | 1,622 | NONE | null | - `transformers` version: 4.5.1
- It just cannot import the version., . cannot import name 'PegasusTokenizer' from 'transformers', python 3.8 | {
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https://api.github.com/repos/huggingface/transformers/issues/11486 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11486/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11486/comments | https://api.github.com/repos/huggingface/transformers/issues/11486/events | https://github.com/huggingface/transformers/pull/11486 | 869,617,597 | MDExOlB1bGxSZXF1ZXN0NjI0OTQ4NjI4 | 11,486 | Update `PreTrainedTokenizerBase` to check/handle batch length for `text_pair` parameter | {
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"Thanks! Failure in the tests is unrelated (some connection problem), so merging."
] | 1,619 | 1,619 | 1,619 | CONTRIBUTOR | null | Consider the following example:
```py
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
import torch
tokenizer = AutoTokenizer.from_pretrained("bert-large-uncased-whole-word-masking-finetuned-squad")
text = r"""
🤗 Transformers (formerly known as pytorch-transformers and pytorch-pretrained-b... | {
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https://api.github.com/repos/huggingface/transformers/issues/11485 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11485/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11485/comments | https://api.github.com/repos/huggingface/transformers/issues/11485/events | https://github.com/huggingface/transformers/issues/11485 | 869,594,228 | MDU6SXNzdWU4Njk1OTQyMjg= | 11,485 | run_mlm.py : Missing key(s) in state_dict & Unexpected key(s) in state_dict | {
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"The command runs for me and according to your logs, the `Trainer` is loading a local checkpoint named `roberta-base`. Do you have a local folder named `roberta-base`? It looks like it contains a checkpoint different from the actual `roberta-base` model, which messes up and creates the error. Could you move that fo... | 1,619 | 1,619 | 1,619 | NONE | null | ## Environment info
- `transformers` version: 4.6.0.dev0
- Platform: Ubuntu 16.04.3 LTS
- Python version: Python 3.6.13 :: Anaconda, Inc.
- PyTorch version (GPU?): 1.8.1+cu102
- Tensorflow version (GPU?):
- Using GPU in script?: YES
- Using distributed or parallel set-up in script?: YES
### Who can help
@sg... | {
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https://api.github.com/repos/huggingface/transformers/issues/11484 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11484/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11484/comments | https://api.github.com/repos/huggingface/transformers/issues/11484/events | https://github.com/huggingface/transformers/issues/11484 | 869,467,578 | MDU6SXNzdWU4Njk0Njc1Nzg= | 11,484 | MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50") Not working | {
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"I can load the model without any issues, I think the issue here is the `from_pretrained` call is hitting the cache and the model is not cached properly. You could force the download by passing `force_download=True`\r\n\r\n```python\r\nmodel = MBartForConditionalGeneration.from_pretrained(\"facebook/mbart-large-50\... | 1,619 | 1,622 | 1,622 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.5.0
- Platform: anaconda
- Python version: 3.7
- PyTorch version (GPU?): 1.1.0
- Tensorflow version (GPU?... | {
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https://api.github.com/repos/huggingface/transformers/issues/11483 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11483/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11483/comments | https://api.github.com/repos/huggingface/transformers/issues/11483/events | https://github.com/huggingface/transformers/issues/11483 | 869,432,931 | MDU6SXNzdWU4Njk0MzI5MzE= | 11,483 | The performance of the huggingface QA model depend on the order in which it loads | {
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"Hi there,\r\n\r\nPlease use the [forum](https://discuss.huggingface.co/) to ask these types of questions, use issues to report bugs or feature requests.\r\n\r\nThanks!",
"> Hi there,\r\n> \r\n> Please use the [forum](https://discuss.huggingface.co/) to ask these types of questions, use issues to report bugs or f... | 1,619 | 1,619 | 1,619 | NONE | null | - `transformers` version: 4.4.2
- Python version: 3.7
I am implementing a paper that I read based on the Question Answering code "run_qa.py" on huggingface.
I added a few layer in the ELECTRA, and I trained and saved only the parameters for the added layer.
when I evaluate, I load that parameters and the rest w... | {
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https://api.github.com/repos/huggingface/transformers/issues/11482 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11482/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11482/comments | https://api.github.com/repos/huggingface/transformers/issues/11482/events | https://github.com/huggingface/transformers/issues/11482 | 869,393,396 | MDU6SXNzdWU4NjkzOTMzOTY= | 11,482 | [Docs] Clarify Subphrase classification? | {
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"The problem lies mostly on the model page in that case, it should show the text classification widget, not the masked LM widget. As for adding a model card or expanding its capabilities, the feedback should go on the [forums](https://discuss.huggingface.co/), this is not really an issue with transformers per se.\r... | 1,619 | 1,619 | 1,619 | CONTRIBUTOR | null | I am going through the docs linearly and am reading [Summary of The tasks](https://huggingface.co/transformers/task_summary.html).
The second section of [Sequence Classification](https://huggingface.co/transformers/task_summary.html) uses `bert-base-cased-finetuned-mrpc` to do paraphrase classification.
This is... | {
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https://api.github.com/repos/huggingface/transformers/issues/11481 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11481/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11481/comments | https://api.github.com/repos/huggingface/transformers/issues/11481/events | https://github.com/huggingface/transformers/pull/11481 | 869,365,108 | MDExOlB1bGxSZXF1ZXN0NjI0NzQzMjI5 | 11,481 | Fix checkpointing in SageMaker MP | {
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The merge of the two Trainers removed the call to `optimizer.state_dict()` being made only on `dp_rank` 0 processes. This PR adds it back. | {
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https://api.github.com/repos/huggingface/transformers/issues/11480 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11480/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11480/comments | https://api.github.com/repos/huggingface/transformers/issues/11480/events | https://github.com/huggingface/transformers/issues/11480 | 869,337,241 | MDU6SXNzdWU4NjkzMzcyNDE= | 11,480 | Error In Running Predictions for run_text_classification.py | {
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"Hi, thank you for the report! I'm examining it now and I'm hoping to push some updates to that script today.",
"I haven't been able to reproduce this issue, but I have a PR open to make modifications to the script. I'll let you know as soon as the updated version is available - would you be willing to check if t... | 1,619 | 1,626 | 1,626 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.5.0
- Platform: Windows-10-10.0.18362-SP0
- Python version: 3.8.0
- PyTorch version (GPU?): 1.7.1+cpu (Fal... | {
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https://api.github.com/repos/huggingface/transformers/issues/11479 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11479/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11479/comments | https://api.github.com/repos/huggingface/transformers/issues/11479/events | https://github.com/huggingface/transformers/issues/11479 | 869,315,391 | MDU6SXNzdWU4NjkzMTUzOTE= | 11,479 | [Docs] Add Caching Example For CI? | {
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"This was written by @julien-c so I'll let him reply on this :-)",
"This was written before we moved from S3 to our own Cloudfront-served repositories so we could also probably just remove that paragraph.",
"Interesting. Maybe it could _still_ be a good reminder as many folks would forget to do this (I know I m... | 1,619 | 1,619 | 1,619 | CONTRIBUTOR | null | From the [installation instructions](https://huggingface.co/transformers/installation.html#caching-models):
> If you expect to be downloading large volumes of models (more than 10,000) from huggingface.co (for instance through your CI setup, or a large-scale production deployment), please cache the model files on yo... | {
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https://api.github.com/repos/huggingface/transformers/issues/11478 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11478/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11478/comments | https://api.github.com/repos/huggingface/transformers/issues/11478/events | https://github.com/huggingface/transformers/issues/11478 | 869,045,753 | MDU6SXNzdWU4NjkwNDU3NTM= | 11,478 | [Flax] Add FlaxBart model | {
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"Wow this sounds awesome! Let me know if you need help! (I think we will need to look at the `generate()` function) together :-)",
"Hi @patrickvonplaten, as I indicated I've started working on `FlaxBart` which can be found on this branch https://github.com/stancld/transformers/tree/FlaxBart . So far, I've impleme... | 1,619 | 1,623 | 1,623 | CONTRIBUTOR | null | # 🚀 Feature request
It would be nice to implement Flax version of BART model.
## Motivation
Narrow the gap in support between encoder transformers (BERT, RoBERTa, ...) and encoder-decoder models (BART,...).
## Your contribution
I've been working on this now so I hope I will send a PR soon.
@patrickvo... | {
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https://api.github.com/repos/huggingface/transformers/issues/11477 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11477/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11477/comments | https://api.github.com/repos/huggingface/transformers/issues/11477/events | https://github.com/huggingface/transformers/pull/11477 | 869,016,026 | MDExOlB1bGxSZXF1ZXN0NjI0NDQ2ODM0 | 11,477 | Move integrations imports before any ML framework imports | {
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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)... | 1,619 | 1,622 | 1,622 | CONTRIBUTOR | null | ## Fixes
Current transformers breaks compatibility with comet_ml because it needs to be imported before any ML frameworks (such as torch). This PR simply moves the imports earlier in the flow.
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the cas... | {
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https://api.github.com/repos/huggingface/transformers/issues/11476 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11476/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11476/comments | https://api.github.com/repos/huggingface/transformers/issues/11476/events | https://github.com/huggingface/transformers/pull/11476 | 869,010,636 | MDExOlB1bGxSZXF1ZXN0NjI0NDQyNDI1 | 11,476 | Adding new argument `max_new_tokens` for generate. | {
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"@LysandreJik @patrickvonplaten\r\n\r\nForgot to add you for review, my bad."
] | 1,619 | 1,622 | 1,622 | CONTRIBUTOR | null | # What does this PR do?
This is a proposal to add a new argument `max_new_tokens` to `generate`.
This include a `MaxNewTokensCriteria` that enables callers that don't
know about the token length ahead (like pipelines callers) to manage
more easily the length of their generated output.
`max_length` is a hard to... | {
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https://api.github.com/repos/huggingface/transformers/issues/11475 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11475/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11475/comments | https://api.github.com/repos/huggingface/transformers/issues/11475/events | https://github.com/huggingface/transformers/pull/11475 | 869,009,087 | MDExOlB1bGxSZXF1ZXN0NjI0NDQxMTU3 | 11,475 | Experimental symbolic tracing feature with torch.fx for BERT, ELECTRA and T5 | {
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"Let's also:\r\n1. add some basic usage doc - we can start with just docstring\r\n2. add one test for one of the models, polish it and then see how to replicate it for other models.",
"My understanding was that this is experimental and as we start using this side of library we will generalize and improve things. ... | 1,619 | 1,635 | 1,621 | MEMBER | null | # What does this PR do?
This PR provides a function called "symbolic_trace" which enables symbolic tracing for models of the library using the new and still experimental torch.fx feature. Our models can't be symbolically traces directly using `torch.fx`, so this is wrapper function that overcomes various issues.
... | {
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https://api.github.com/repos/huggingface/transformers/issues/11474 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11474/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11474/comments | https://api.github.com/repos/huggingface/transformers/issues/11474/events | https://github.com/huggingface/transformers/issues/11474 | 868,929,696 | MDU6SXNzdWU4Njg5Mjk2OTY= | 11,474 | can not import mbart and mT5 modeling file | {
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"Could you please post more details and a code snippet? \r\n\r\nTo import a modeling use\r\n```python\r\nfrom transformers.models.mbart import modeling_mbart\r\n```"
] | 1,619 | 1,619 | 1,619 | NONE | null | @patrickvonplaten
ImportError: cannot import name 'modeling_mbart'
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https://api.github.com/repos/huggingface/transformers/issues/11473 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11473/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11473/comments | https://api.github.com/repos/huggingface/transformers/issues/11473/events | https://github.com/huggingface/transformers/issues/11473 | 868,926,721 | MDU6SXNzdWU4Njg5MjY3MjE= | 11,473 | Can not import modeling_mbart | {
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"Please follow the issue template."
] | 1,619 | 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:
- Platform:
- Python version:
- PyTorch version (GPU?):
- Tensorflow version (GPU?):
- Using GPU in script... | {
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https://api.github.com/repos/huggingface/transformers/issues/11472 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11472/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11472/comments | https://api.github.com/repos/huggingface/transformers/issues/11472/events | https://github.com/huggingface/transformers/pull/11472 | 868,880,559 | MDExOlB1bGxSZXF1ZXN0NjI0MzMyMTY2 | 11,472 | Update min versions in README and add Flax | {
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This PR adapts the minimum versions of each backend (PyTorch was still at 1.0 and TensorFlow at 2.0), removes mention of TensorFlow 2.0 to just say TensorFlow (I think it's safe now!) and adds Jax as an official backend since we have worked the API a bit more.
Fixes #11422 | {
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"Not to impede this PR, just wanted to add that this comment might be of importance for future work in this area: https://github.com/pytorch/pytorch/issues/29523#issuecomment-831390099\r\n\r\nAnd the whole issue: https://github.com/pytorch/pytorch/issues/29523\r\n\r\nI wonder if our side needs/should support that `... | 1,619 | 1,655 | 1,620 | MEMBER | null | 🚨🚨🚨 **Breaking seeded model initialization** 🚨🚨🚨
As explained below this PR breaks seeded model initialization by default. To ensure the exact same model initialization as before, use:
```python
torch.manual_seed(seed)
model = BertForSequenceClassification.from_pretrained("bert-base-cased", _fast_init=Fal... | {
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https://api.github.com/repos/huggingface/transformers/issues/11470 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11470/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11470/comments | https://api.github.com/repos/huggingface/transformers/issues/11470/events | https://github.com/huggingface/transformers/pull/11470 | 868,774,517 | MDExOlB1bGxSZXF1ZXN0NjI0MjQzODE5 | 11,470 | [FlaxRoberta] Add FlaxRobertaModels & adapt run_mlm_flax.py | {
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<!--
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/11469 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11469/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11469/comments | https://api.github.com/repos/huggingface/transformers/issues/11469/events | https://github.com/huggingface/transformers/issues/11469 | 868,761,536 | MDU6SXNzdWU4Njg3NjE1MzY= | 11,469 | Train GPT2 with Trainer & TrainingArguments using/specifying attention_mask | {
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"Hi there,\r\n\r\nIf your dataset or collator returns the `attention_mask`, then you don't need to pass it separately. With `Trainer`, all the input that you want to pass to model's `forward` should be returned by the dataset/collator and it will be passed to `model.forward` by `Trainer`.",
"Thank you very much f... | 1,619 | 1,622 | 1,622 | NONE | null | Hi, I'm using Trainer & TrainingArguments to train GPT2 Model, but it seems that this does not work well.
My datasets have the ids of the tokens of my corpus and the mask of each text, to indicate where to apply the attention:
```
Dataset({
features: ['attention_mask', 'input_ids', 'labels'],
num_rows:... | {
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https://api.github.com/repos/huggingface/transformers/issues/11468 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11468/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11468/comments | https://api.github.com/repos/huggingface/transformers/issues/11468/events | https://github.com/huggingface/transformers/issues/11468 | 868,680,007 | MDU6SXNzdWU4Njg2ODAwMDc= | 11,468 | binary classification does not work with a large amount of data | {
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"It won't be possible for us to answer issues with another library. Also please use the forum to such [questions](https://discuss.huggingface.co/). Thank you!",
"Thank you for your answer.\r\n\r\nI asked this question here because the simple transformers are working on the transformers library. It is just an inte... | 1,619 | 1,622 | 1,622 | NONE | null | I'm trying to use binary classification, and I used a code like Minimal Start code in the simpletransformers.ai. I can get f1, tp> 0 with a small sample of my data (around 200K rows), but surprisingly, when I'm trying to apply the model to a whole dataset (2.6M rows) or less (500K rows), the evaluation of the model is ... | {
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1. As a follow up to #11462, finish correcting places where the tuple is mentioned instead of the model object.
2. You must import `AutoModel` as well as `TFAutoModel` for the tutorial to run correctly.
3. Cleaned up some language for readability.
@sgugger | {
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"Thanks a lot for catching this Patrick! I corrected this for BART and mBART."
] | 1,619 | 1,619 | 1,619 | MEMBER | null | # What does this PR do?
Few doc fixes for `decoder_input_ids` in s2s models.
Fixes #11357
Thanks, @shyrma for spotting this! | {
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"This can be achieved by just doing `model = AutoModelForSeq2SeqLM.from_config(config)` when the checkpoint is not None. I don't believe it will be much faster however as your analysis in #9205 pointed out to the random initialization as being the bottleneck.",
"> This can be achieved by just doing model = AutoMo... | 1,619 | 1,622 | null | CONTRIBUTOR | null | This is similar to what was discussed in https://github.com/huggingface/transformers/issues/9205, which proposed not to random init weights on `from_pretrained`, but this time it's about resume - currently we load pretrained weights and immediately drop them on resume from checkpoint in Trainer.
To solve this we, fo... | {
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https://api.github.com/repos/huggingface/transformers/issues/11464 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11464/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11464/comments | https://api.github.com/repos/huggingface/transformers/issues/11464/events | https://github.com/huggingface/transformers/issues/11464 | 868,350,690 | MDU6SXNzdWU4NjgzNTA2OTA= | 11,464 | [DeepSpeed] ZeRO-Infinity integration: getting started and issues | {
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"Hi @stas00, is it normal for zero3 training to take a while to get started?\r\n\r\nI haven't put in any time to investigating yet, but I updated transformers and deepspeed to the latest masters just to see if I could get them working. My simple training script (derived from the summarization example) works fine wi... | 1,619 | 1,690 | 1,622 | CONTRIBUTOR | null | [DeepSpeed ZeRO-Infinity](https://arxiv.org/abs/2104.07857) HF Integration is now available in the master branch of `transformers`. Here is a quick getting started/what's new post.
ZeRO-Infinity extends ZeRO-3 by extending CPU Offload with NVMe Offload, enabling training even bigger models. And it adds various other... | {
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"> This won't work sadly, for two reasons.\r\n> \r\n> 1. First, everything in the `__dict__` of the config gets serialized when one uses `config.self_pretrained()` (which is called by `model.from_pretrained`) so any other model downloaded from the hub with a checkpoint saved after this is merged will get this attri... | 1,619 | 1,619 | 1,619 | CONTRIBUTOR | null | Skip `_init_weights` for pretrained models since they get immediately replaced by pretrained weights. This leads to a much faster startup for huge models.
Fixes: https://github.com/huggingface/transformers/issues/9205
@sgugger, @patrickvonplaten | {
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https://api.github.com/repos/huggingface/transformers/issues/11462 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11462/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11462/comments | https://api.github.com/repos/huggingface/transformers/issues/11462/events | https://github.com/huggingface/transformers/pull/11462 | 868,309,116 | MDExOlB1bGxSZXF1ZXN0NjIzODU0NjE2 | 11,462 | update QuickTour docs to reflect model output object | {
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"I might need some help or tips with figuring out why styling check CI is failing. I tried to debug but it is not clear to me what is wrong",
"Thanks, @sgugger that worked",
"Thank *you* for the fixes :-)"
] | 1,619 | 1,619 | 1,619 | CONTRIBUTOR | null | Currently, the [Quick tour](https://huggingface.co/transformers/quicktour.html#) docs shows model output as tuples when you print them out. In the current version of 🤗, the user sees an object that inherits from the `ModelOutput` class. Yes, you can still access this object as a tuple, but this might be confusing fo... | {
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https://api.github.com/repos/huggingface/transformers/issues/11461 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11461/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11461/comments | https://api.github.com/repos/huggingface/transformers/issues/11461/events | https://github.com/huggingface/transformers/issues/11461 | 868,295,660 | MDU6SXNzdWU4NjgyOTU2NjA= | 11,461 | T5-large FP16 produces nan in loss | {
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"I see nans creeping in at the T5Attention in decoder. I didn't find any inf or nan in either hidden_states or key_value_states but the computed values of both key_states and value_states have nan's",
"> FP16 mode shouldn't produce nan in loss.\r\n\r\nWhy do you believe this to be the case? This model was trained... | 1,619 | 1,622 | 1,622 | NONE | null | ## Environment info
- `transformers` version: 4.6.0.dev0, commit hash: 5e04d7086803ae4a3892f4082f2835a756592c2c
- Platform: Linux-4.15.0-1071-azure-x86_64-with-debian-buster-sid
- Python version: 3.7.3
- PyTorch version (GPU?): 1.8.1+cu111 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in sc... | {
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https://api.github.com/repos/huggingface/transformers/issues/11460 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11460/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11460/comments | https://api.github.com/repos/huggingface/transformers/issues/11460/events | https://github.com/huggingface/transformers/issues/11460 | 868,211,301 | MDU6SXNzdWU4NjgyMTEzMDE= | 11,460 | support batch-sampler in trainer | {
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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)... | 1,619 | 1,622 | 1,622 | NONE | null | # 🚀 Feature request
Hi
Currently Trainer class only supports sampler, but not batch-sampler, (the sampling strategies based on batches, which are a group of samplers in torch), if a user wants to use batch-sampler, currently Trainer class introduces unwanted bugs, but not setting epoch for this type of samplers. ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11459 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11459/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11459/comments | https://api.github.com/repos/huggingface/transformers/issues/11459/events | https://github.com/huggingface/transformers/issues/11459 | 868,191,568 | MDU6SXNzdWU4NjgxOTE1Njg= | 11,459 | extending metric_for_best_model to a list of strings | {
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"This could be added indeed. Note that there is already a workaround: when defining your `compute_metrics` function, you can add a new field with this average:\r\n```\r\ndef compute_metrics(eval_preds):\r\n # Your previous metric computation\r\n metrics[\"combined\"] = (metrics[\"accuracy\"] + metrics[\"f1\"]... | 1,619 | 1,690 | 1,622 | NONE | null | # 🚀 Feature request
Hi
Currently ` metric_for_best_model(:obj:`str`, `optional`) ` only covers one metric, for some datasets like MRPC, one have several metrics, like accuracy/F1 or like in STSB both pearson/spearman, and user might need to choose the best based on average on all metrics, it could be helpful to ha... | {
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https://api.github.com/repos/huggingface/transformers/issues/11458 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11458/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11458/comments | https://api.github.com/repos/huggingface/transformers/issues/11458/events | https://github.com/huggingface/transformers/issues/11458 | 868,153,133 | MDU6SXNzdWU4NjgxNTMxMzM= | 11,458 | "Is next sentence" pre-training task availability for Language Modeling scripts | {
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"Related issues: https://github.com/huggingface/transformers/issues/1622, https://github.com/huggingface/transformers/issues/2898 and https://github.com/huggingface/transformers/issues/2166\r\n\r\nHowever, example scripts are made to be very understandable and very easy to tweak, so modifying them to include the ne... | 1,619 | 1,674 | 1,622 | CONTRIBUTOR | null | # 🚀 Feature request
BERT was trained on 2 pretraining tasks. The scripts [here ](https://github.com/huggingface/transformers/tree/master/examples/pytorch/language-modeling) in the repo for language modeling only provide scripts for masked language modeling.
Is there any specific reason for this?
I was hoping ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11457 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11457/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11457/comments | https://api.github.com/repos/huggingface/transformers/issues/11457/events | https://github.com/huggingface/transformers/issues/11457 | 868,097,181 | MDU6SXNzdWU4NjgwOTcxODE= | 11,457 | Can this `@slow` annotation be removed at barthez tokenizer test= | {
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"No it is intended as slow. The Barthez tokenizer fast tokenizer takes forever to load from the slow one sadly, which is why we marked those tests are slow. To be able to remove that, we must first create a small sentencepiece model that is compatible with Barthez (it is using the real tokenizer checkpoint right no... | 1,619 | 1,620 | 1,619 | CONTRIBUTOR | null | Here is a `@slow` annotation that can be removed IMO.
Otherwise maybe write a comment why it is tagged as slow?
https://github.com/huggingface/transformers/blob/bc2571e61c985ec82819cf01ad038342771c94d0/tests/test_tokenization_barthez.py#L27
I can provide a PR. | {
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https://api.github.com/repos/huggingface/transformers/issues/11456 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11456/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11456/comments | https://api.github.com/repos/huggingface/transformers/issues/11456/events | https://github.com/huggingface/transformers/issues/11456 | 867,961,856 | MDU6SXNzdWU4Njc5NjE4NTY= | 11,456 | Perturb Hidden-State in Encoder-Decoder Models | {
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"Hi @vin-nag \r\n\r\nIf you want to directly pass `hidden_states` then you could do it this way\r\n\r\n```python\r\nmodel = EncoderDecoderModel.from_pretrained(\"google/roberta2roberta_L-24_gigaword\")\r\ntok = AutoTokenizer.from_pretrained(\"google/roberta2roberta_L-24_gigaword\")\r\n\r\narticle = \"\"\"australian... | 1,619 | 1,660 | 1,619 | NONE | null | Hi All,
I'm fairly new at using huggingface - so I apologize if this is answered in the documentation. I've looked around and don't think this has been asked before. I'm trying to perturb and use the hidden-state of an encoder-decoder model on the summarization task.
More specifically, I'd like to
1. Get a f... | {
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https://api.github.com/repos/huggingface/transformers/issues/11455 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11455/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11455/comments | https://api.github.com/repos/huggingface/transformers/issues/11455/events | https://github.com/huggingface/transformers/issues/11455 | 867,890,495 | MDU6SXNzdWU4Njc4OTA0OTU= | 11,455 | Unable to use custom dataset: AttributeError: 'list' object has no attribute 'keys' | {
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"This is really weird. Could you print a few items of your Dataset? The error means that they are not dictionaries containing `\"input_ids\"` but they certainly seem to be.\r\n\r\nAlso note that since you already have applied padding in your preprocessing, you can use the `default_data_collator`, but the code shoul... | 1,619 | 1,620 | 1,620 | NONE | null | What am I doing wrong?
I encode data with
```
model_name = "dbmdz/bert-base-italian-uncased"
tokenizer = AutoTokenizer.from_pretrained(model_name, do_lower_case = True)
def encode_data(texts):
return tokenizer.batch_encode_plus(
texts,
add_special_tokens=True,
... | {
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https://api.github.com/repos/huggingface/transformers/issues/11454 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11454/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11454/comments | https://api.github.com/repos/huggingface/transformers/issues/11454/events | https://github.com/huggingface/transformers/issues/11454 | 867,880,128 | MDU6SXNzdWU4Njc4ODAxMjg= | 11,454 | cannot import name 'set_seed' from 'transformers' | {
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"Try the following code:\r\n`from transformers.trainer_utils import set_seed`\r\nLet me know if it works!",
"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... | 1,619 | 1,622 | 1,622 | NONE | null | i run with transformers==4.5.1 and get the following error:
do you know how to resolve this issue?
thanks | {
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https://api.github.com/repos/huggingface/transformers/issues/11453 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11453/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11453/comments | https://api.github.com/repos/huggingface/transformers/issues/11453/events | https://github.com/huggingface/transformers/pull/11453 | 867,839,513 | MDExOlB1bGxSZXF1ZXN0NjIzNDQ0MDQ0 | 11,453 | Give each hub test a different repo name | {
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To reduce flakiness in the tests using the hub and be able to investigate failures more closely, this PR gives them each one different namespace. | {
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https://api.github.com/repos/huggingface/transformers/issues/11452 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11452/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11452/comments | https://api.github.com/repos/huggingface/transformers/issues/11452/events | https://github.com/huggingface/transformers/issues/11452 | 867,663,561 | MDU6SXNzdWU4Njc2NjM1NjE= | 11,452 | wav2vec2 doesn't work with torch.distributed.launch & multi GPU | {
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"## Error messages in short\r\n### Warning\r\n```\r\nUserWarning: Using a non-full backward hook when the forward contains multiple autograd Nodes is deprecated and will be removed in future versions. This hook will be missing some grad_input. Please use register_full_backward_hook to get the documented behavior.\r... | 1,619 | 1,705 | 1,625 | 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: 4.6.0.dev0
- Platform: Linux-4.15.0-140-generic-x86_64-with-debian-buster-sid
- Python version: 3.7.9
- PyTo... | {
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"Hi @AdrianNunez \r\n\r\nCould you post the for of the `input_ids` and `labels`. As explained in the [docs](https://huggingface.co/transformers/model_doc/mbart.html#training-of-mbart), mBART expects `input_ids` and `labels` in a certain format. \r\n\r\n`labels` are prepared with the format `ids [eos, tgt_lang_code]... | 1,619 | 1,622 | 1,622 | NONE | null | ## Environment info
- `transformers` version: 4.5.1
- Platform: Linux-3.10.0-1062.9.1.el7.x86_64-x86_64-with-centos-7.7.1908-Core
- Python version: 3.6.8
- PyTorch version (GPU?): 1.7.1+cu101 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: No
- Using distributed or parallel set-up ... | {
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https://api.github.com/repos/huggingface/transformers/issues/11450 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11450/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11450/comments | https://api.github.com/repos/huggingface/transformers/issues/11450/events | https://github.com/huggingface/transformers/pull/11450 | 867,609,482 | MDExOlB1bGxSZXF1ZXN0NjIzMjU0NzQw | 11,450 | [Black] Pin Version | {
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"After discussion with @lhoestq & @sgugger, upgrading is the better option => so merge https://github.com/huggingface/transformers/pull/11442",
"Shouldn't we close this ?"
] | 1,619 | 1,619 | 1,619 | MEMBER | null | Pin black until repo will be re-style with black 21.4b0. | {
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"Thank you for the feedback! "
] | 1,619 | 1,619 | 1,619 | CONTRIBUTOR | null | # What does this PR do?
Clarifies the description of the `is_split_into_words` argument which is used in the tokenizers.
Closes #11333
## 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](htt... | {
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"In some places I think \"activation checkpointing\" is referred to as \"gradient checkpointing\". The former sounds more logical as it's activations that aren't being saved. So it's https://pytorch.org/docs/stable/checkpoint.html.\r\n\r\nIt should be already there, as you can see the `GPTNeoModel` has it setup:\r... | 1,619 | 1,619 | 1,619 | NONE | null | Working on a script which uses `GPTNeoForCausalLM` as the model object. As I understand it, gradient checkpointing requires checkpointing every layer. How do I change `GPTNeoForCausalLM` to incorporate gradient checkpointing, given that it doesn't show the layers explicitly but rather uses
```
self.transformer = GPTN... | {
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"My issue is quite similar to #10756 ",
"Hi! I believe you're using XLM models/tokenizers with XLM-R checkpoints. Have you tried using `XLMRobertaTokenizer` and `XLMRobertaLMHeadModel` instead?\r\n\r\nYou're also trying to load a BERT checkpoint in an XLM tokenizer, this won't work. If you want to load any check... | 1,619 | 1,655 | 1,619 | NONE | null | - `transformers` version: 4.5.1
- Platform: Linux-4.19.112+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.10
- PyTorch version (GPU?): 1.8.1+cu101 (False)
- Tensorflow version (GPU?): 2.4.1 (False)
Models I am using are **RoBERTa** (xlm-roberta-large) and **BERT** (bert-base-multilingual-cased)
##... | {
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"deepspeed doesn't work with `autocast`, it has its own way of dealing with mixed precision, if you look in the `trainer.py` it's carefully bypassed. \r\n\r\ndoes the problem go away if you remove `autocast`?",
"@stas00 Thank you for your reply!\r\nWhen I deleted `autocast` and ran it, I got the error `RuntimeEr... | 1,619 | 1,623 | 1,623 | NONE | null | ## Environment info
- `transformers` version: 4.5.1
- Platform: Linux-4.15.0-140-generic-x86_64-with-debian-buster-sid
- Python version: 3.7.9
- PyTorch version (GPU?): 1.8.1 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: <2,4>
- Using distributed or parallel set-up in script?: ... | {
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"@sgugger \r\n\r\n> is it possible to add a fast version of the tokenizer?\r\n\r\nYes, will add the fast version as well.\r\n\r\n\r\n> why are there two classes for the vision model and the text model? They have the exact same forward, so we should only have one class IMO.\r\n\r\nAdded two versions so that one coul... | 1,619 | 1,630 | 1,620 | MEMBER | null | # What does this PR do?
This PR adds the [CLIP](https://github.com/openai/CLIP) model.
CLIP is a multi-modal vision+language model which uses a transformer model for encoding both the images and text.
- The model here is designed such that both `CLIPTextModel` and `CLIPVisionModel` can be loaded independently,... | {
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# What does this PR do?
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"Please give us the whole command you are running as we can't reproduce without it.\r\nAre you properly setting the seed? Depending on the seed used, the results differ a lot on MRPC, since it's a tiny dataset. This is known and there have been [published papers](https://arxiv.org/pdf/2002.06305.pdf) on this.",
"... | 1,619 | 1,619 | 1,619 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.5.0
- Platform: linux
- Python version: 3.8
- PyTorch version (GPU?): 1.8
- Tensorflow version (GPU?): - ... | {
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"Closing this PR in favor of https://github.com/huggingface/transformers/pull/11450"
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<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.5.1
- Platform: Linux-4.18.0-147.el8.x86_64-x86_64-with-Ubuntu-16.04-xenial
- Python version: 3.7.10
- PyT... | {
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https://api.github.com/repos/huggingface/transformers/issues/11440 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/11440/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/11440/comments | https://api.github.com/repos/huggingface/transformers/issues/11440/events | https://github.com/huggingface/transformers/issues/11440 | 867,321,669 | MDU6SXNzdWU4NjczMjE2Njk= | 11,440 | Feedback whilst resuming | {
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"This has been fixed by #11324. If you use a source install, you will be able to use (or in this case see) this feature :-)"
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Add some sort of progress bar during resumption of training from a checkpoint
## Motivation
I resumed training from a checkpoint mid-way through a 100 Epoch training. The progress bar sat on zero for quite some time, and I could see CPU activity but no GPU's were active. Eventually the pro... | {
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This PR will enable `BigBirdForQuestionAnswering` to return pooler output. This can be useful for the tasks involving predicting category along with answer eg: [Natural Questions dataset](https://huggingface.co/datasets/natural_questions)
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