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https://api.github.com/repos/huggingface/transformers/issues/12244 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12244/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12244/comments | https://api.github.com/repos/huggingface/transformers/issues/12244/events | https://github.com/huggingface/transformers/issues/12244 | 924,570,528 | MDU6SXNzdWU5MjQ1NzA1Mjg= | 12,244 | RoFormerTokenizerFast has a wrong result when setting "return_offsets_mapping=True" | {
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"@JaheimLee \r\n**uncomment** 取消注释 L44-L53\r\n##### this code slice normalized_string is too slow (6s) but test_alignement_methods can pass\r\n\r\nhttps://github.com/huggingface/transformers/blob/e43e11260ff3c0a1b3cb0f4f39782d71a51c0191/src/transformers/models/roformer/tokenization_utils.py#L43-L53\r\n\r\nIf we use... | 1,623 | 1,625 | 1,625 | NONE | null | I use roformer_chinese_char_base model, so there is no word-level problem. RoFormerTokenizerFast has this bug, but BertTokenizerFast doesn't. Here is the code:
```python
In [1]: from transformers import RoFormerTokenizerFast, BertTokenizerFast
In [2]: path = '/data/pretrained_models/roformer_chinese_char_base'
... | {
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"The main thing I'm uncertain about is how to handle unimplemented functionality. GPT-J uses the same tokenizer as GPT-2, so I removed the tokenizer definition. Is that correct, or no? Relatredly, there were many types of modeling that GPT-J was not designed for, and @finetuneanon's PR just deleted the boilerplate ... | 1,623 | 1,630 | 1,630 | CONTRIBUTOR | null | **This is a work-in-progress focused on reconciling styles and may break without warning. If you want to use GPT-J with the HF interface, you can do that by installing transformers from [here](https://github.com/finetuneanon/transformers/tree/gpt-j). The purpose of this PR is to make progress on converting that repo to... | {
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https://api.github.com/repos/huggingface/transformers/issues/12242 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12242/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12242/comments | https://api.github.com/repos/huggingface/transformers/issues/12242/events | https://github.com/huggingface/transformers/issues/12242 | 924,499,599 | MDU6SXNzdWU5MjQ0OTk1OTk= | 12,242 | Can't load tokenizer for 'imxly/t5-pegasus'. | {
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"The tokenizer specified for that model is `T5Tokenizer`, which is a sentencepiece-based tokenizer. However, the tokenizer file is `vocab.txt`, which is a BERT-like (WordPiece) file.\r\n\r\nThe T5 tokenizer expects as `spiece.model` file generated by the SentencePiece library, or a `tokenizer.json` file generated b... | 1,623 | 1,665 | 1,627 | NONE | null | when I use t5-pegasus on huggingface.co, What's the problem？
<img width="1589" alt="截屏2021-06-18 上午11 10 34" src="https://user-images.githubusercontent.com/12478408/122500741-e76d4f00-d025-11eb-839c-96f259c89af0.png">
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"Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.\r\nCould you ask your question on the [forum](https://discuss.huggingface.co) instead?\r\n\r\nThanks!"
] | 1,623 | 1,625 | null | NONE | null | Hello I would like to modify the encoder layers of the BERT model, to insert FC and ReLu layers.
This idea allows you to reproduce the use of [Squeeze-and-Excitation Networks](https://arxiv.org/abs/1709.01507)
How to use an nn.module class to handle encoder outputs?
Example:
```
import torch.nn as nn
from... | {
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https://api.github.com/repos/huggingface/transformers/issues/12240 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12240/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12240/comments | https://api.github.com/repos/huggingface/transformers/issues/12240/events | https://github.com/huggingface/transformers/pull/12240 | 924,441,685 | MDExOlB1bGxSZXF1ZXN0NjczMDgyNzIx | 12,240 | Depreciate pythonic Mish and support PyTorch 1.9 version of Mish | {
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"Done"
] | 1,623 | 1,624 | 1,624 | CONTRIBUTOR | null | This PR removes the old pure pythonic version of [Mish](https://arxiv.org/abs/1908.08681) and now enables support for the [PyTorch 1.9 Mish version](https://pytorch.org/docs/stable/generated/torch.nn.Mish.html#torch.nn.Mish). It also removes isolated references of the function where it is not used.
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https://api.github.com/repos/huggingface/transformers/issues/12239 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12239/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12239/comments | https://api.github.com/repos/huggingface/transformers/issues/12239/events | https://github.com/huggingface/transformers/pull/12239 | 924,412,382 | MDExOlB1bGxSZXF1ZXN0NjczMDU3ODk2 | 12,239 | [t5 doc] make the example work out of the box | {
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Fixes: https://github.com/huggingface/transformers/issues/12238
@patrickvonplaten
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https://api.github.com/repos/huggingface/transformers/issues/12238 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12238/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12238/comments | https://api.github.com/repos/huggingface/transformers/issues/12238/events | https://github.com/huggingface/transformers/issues/12238 | 924,408,103 | MDU6SXNzdWU5MjQ0MDgxMDM= | 12,238 | [doc] t5 incomplete example | {
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"A possible approach proposed here: https://github.com/huggingface/transformers/pull/12239"
] | 1,623 | 1,624 | 1,624 | CONTRIBUTOR | null | https://huggingface.co/transformers/model_doc/t5.html#training has:
```
input_ids = tokenizer('translate English to German: The house is wonderful.', return_tensors='pt').input_ids
labels = tokenizer('Das Haus ist wunderbar.', return_tensors='pt').input_ids
# the forward function automatically creates the correct d... | {
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https://api.github.com/repos/huggingface/transformers/issues/12237 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12237/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12237/comments | https://api.github.com/repos/huggingface/transformers/issues/12237/events | https://github.com/huggingface/transformers/issues/12237 | 924,405,169 | MDU6SXNzdWU5MjQ0MDUxNjk= | 12,237 | BART fine-tuning doesn't work and produces a fixed output for each input | {
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"Hi, \r\n\r\nfollowing up on this @patrickvonplaten and @patil-suraj ",
"Hey @sajastu,\r\n\r\nIt's pretty difficult for us to debug the script - from a first look, the hyperparameter settings look good to me. \r\nAn effective batch size of 8 (4 * 2) seems rather small to me, but you can see from your loss curves ... | 1,623 | 1,628 | 1,628 | NONE | null | I'm getting stuck on fine-tuning BART model on reddit-tifu dataset. When I use a pre-trained model of BART, for example, `bart-large-xsum` without finetuning, it works fine and produces sort of sensible output for each input, but as I start finetuning it with BART, it starts to predict irrelevant text for each given in... | {
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https://api.github.com/repos/huggingface/transformers/issues/12236 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12236/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12236/comments | https://api.github.com/repos/huggingface/transformers/issues/12236/events | https://github.com/huggingface/transformers/pull/12236 | 924,367,728 | MDExOlB1bGxSZXF1ZXN0NjczMDE4Njgw | 12,236 | [Flax] Add FlaxMBart | {
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"@patil-suraj Thank you a lot for your suggestions. I fixed the order of attention and normalization layers and some other minor bugs. Also added some additional copy statements.\r\n\r\nI also changed the `shift_tokens_right` method as this one looks to be different for the MBart models as they don't have a single ... | 1,623 | 1,625 | 1,625 | CONTRIBUTOR | null | # What does this PR do?
This PR adds flax implementation of MBart.
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md#st... | {
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https://api.github.com/repos/huggingface/transformers/issues/12235 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12235/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12235/comments | https://api.github.com/repos/huggingface/transformers/issues/12235/events | https://github.com/huggingface/transformers/issues/12235 | 924,305,889 | MDU6SXNzdWU5MjQzMDU4ODk= | 12,235 | can predict_with_generate (do_eval) work with sharded_ddp fairscale in 4.6.1+? | {
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"Can I ask whether we have any progress on the model prediction (text generation) during the training with fairscale? Thanks/ cc @stas00 ",
"most likely you'd want to ask @sgugger as I he did the fairscale integration. \r\n\r\nyou can ask me about the deepspeed integration if you try that instead.",
"`sharded_d... | 1,623 | 1,628 | 1,628 | NONE | null | In 4.5.0, sharded_ddp won't work with predict_with_generate in seq2seq or clm model training during the eval step. Wonder whether it can work in the latest version. | {
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https://api.github.com/repos/huggingface/transformers/issues/12234 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12234/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12234/comments | https://api.github.com/repos/huggingface/transformers/issues/12234/events | https://github.com/huggingface/transformers/issues/12234 | 924,247,702 | MDU6SXNzdWU5MjQyNDc3MDI= | 12,234 | Reconstructing Tokens from Bert Embedding? | {
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"Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.\r\nCould you ask your question on the [forum](https://discuss.huggingface.co) instead?\r\n\r\nThanks!"
] | 1,623 | 1,624 | 1,624 | NONE | null | Sorry if this was posted before but I couldn't it after a few searches.
My goal is to take a sentence, run it through BERT, perturb the contextualized embeddings from the output of BERT, and reconstruct the sentence text.
I'm currently using 'bert-base-uncased' as my tokenizer and model and a perturbed output tor... | {
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https://api.github.com/repos/huggingface/transformers/issues/12233 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12233/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12233/comments | https://api.github.com/repos/huggingface/transformers/issues/12233/events | https://github.com/huggingface/transformers/pull/12233 | 924,230,962 | MDExOlB1bGxSZXF1ZXN0NjcyODk4NzA3 | 12,233 | Add FlaxBigBird QuestionAnswering script | {
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"@patrickvonplaten, this PR is ready for review & merge (tested all the code after porting here).\r\n\r\nFailing test is unrelated to this PR.",
"Awesome merging for the sprint - we'll fix bugs on the go as it's under `research_projects` :-)"
] | 1,623 | 1,624 | 1,624 | CONTRIBUTOR | null | # What does this PR do?
This PR will add flax-bigbird QA script on `natural-questions` dataset.
## Who can review?
Anyone in the community is free to review the PR once the tests have passed.
@patrickvonplaten | {
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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: 4.7.0
- Platform: Linux-5.4.104+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.10
- PyTorch version ... | {
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https://api.github.com/repos/huggingface/transformers/issues/12231 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12231/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12231/comments | https://api.github.com/repos/huggingface/transformers/issues/12231/events | https://github.com/huggingface/transformers/issues/12231 | 924,171,779 | MDU6SXNzdWU5MjQxNzE3Nzk= | 12,231 | Batch inference runtime slows down for inputs with different length sentences | {
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"Pinging @NielsRogge as he might have an idea of what's going on with LUKE",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guide... | 1,623 | 1,632 | 1,632 | 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: 4.6.1
- Platform: Ubuntu 18.04.5 LTS
- Python version: 3.6.9
- PyTorch version (GPU?): 1.8.1
- Tensorflow v... | {
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https://api.github.com/repos/huggingface/transformers/issues/12230 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12230/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12230/comments | https://api.github.com/repos/huggingface/transformers/issues/12230/events | https://github.com/huggingface/transformers/pull/12230 | 924,139,176 | MDExOlB1bGxSZXF1ZXN0NjcyODE5NjA5 | 12,230 | Flax summarization script | {
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Adds Flax summarization example.
Beam search `generate` works like a charm on TPU, really fast! This makes it very easy and fast to use the `generate` in the eval loop. | {
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https://api.github.com/repos/huggingface/transformers/issues/12229 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12229/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12229/comments | https://api.github.com/repos/huggingface/transformers/issues/12229/events | https://github.com/huggingface/transformers/pull/12229 | 924,040,674 | MDExOlB1bGxSZXF1ZXN0NjcyNzMyODY1 | 12,229 | Add link to the course | {
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"Thank you 🤗 & @sgugger for doing this. \r\nJust so if anyone is looking for the direct link to videos: https://huggingface.co/course/"
] | 1,623 | 1,624 | 1,623 | COLLABORATOR | null | # What does this PR do?
This PR adds a link to the Hugging Face course on the first page of the documentation. | {
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https://api.github.com/repos/huggingface/transformers/issues/12228 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12228/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12228/comments | https://api.github.com/repos/huggingface/transformers/issues/12228/events | https://github.com/huggingface/transformers/pull/12228 | 924,023,465 | MDExOlB1bGxSZXF1ZXN0NjcyNzE4MDM4 | 12,228 | [Flax] FlaxAutoModelForSeq2SeqLM | {
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This PR adds `FlaxAutoModelForSeq2SeqLM`. | {
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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/12226 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12226/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12226/comments | https://api.github.com/repos/huggingface/transformers/issues/12226/events | https://github.com/huggingface/transformers/pull/12226 | 923,839,009 | MDExOlB1bGxSZXF1ZXN0NjcyNTU4NDMx | 12,226 | update desc for map in all examples | {
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Closes #11797. I've added the remaining the `desc` for `summarization`, `token-classification,` `translation`, `language-modeling ` and updated `requirements.txt` as well. I wasn't sure what to add in `desc` at some places so I've added `# not sure if it's right` comment there. Please let me ... | {
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https://api.github.com/repos/huggingface/transformers/issues/12225 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12225/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12225/comments | https://api.github.com/repos/huggingface/transformers/issues/12225/events | https://github.com/huggingface/transformers/issues/12225 | 923,758,495 | MDU6SXNzdWU5MjM3NTg0OTU= | 12,225 | Pegasus pretraining in fp16 results in NaN loss | {
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"Yeah, not sure to what extent it is feasible to prevent this as Pegasus was pretrained in `bfloat16` cc @stas00 ",
"But I'm pretraining a freshly initialized model, so I think the problem shouldn't be with the `bfloat16` casting",
"That's interesting. We have primarily debugged bf16-pretrained models that almo... | 1,623 | 1,626 | 1,626 | NONE | null | ## Environment info
`transformers` version: 4.5.1
- Platform: Linux-5.4.0-73-generic-x86_64-with-glibc2.29
- Python version: 3.8.5
- PyTorch version (GPU?): 1.4.0 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: yes
- Using distributed or parallel set-up in script?: no
### Who ... | {
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https://api.github.com/repos/huggingface/transformers/issues/12224 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12224/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12224/comments | https://api.github.com/repos/huggingface/transformers/issues/12224/events | https://github.com/huggingface/transformers/pull/12224 | 923,732,017 | MDExOlB1bGxSZXF1ZXN0NjcyNDY0Mzcz | 12,224 | Support for torch 1.9.0 | {
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"Shouldn't the fx tests be skipped correspondingly? I see the CI logs show that they all passed with 1.9.0 - how is that possible?",
"The `is_torch_fx_available` returns `False` as the versions aren't compatible. The tests for torch.fx require `is_torch_fx_available` to be `True` in order to run!\r\n\r\nYes, swit... | 1,623 | 1,623 | 1,623 | MEMBER | null | This PR adds support for torch 1.9.0. It upgrades the CPU CI to use torch 1.9.0, and the GPU CI to use PyTorch's 1.9.0 docker image to run tests.
As discussed with @michaelbenayoun, this puts a hard requirement on having a specific torch version for torch fx to be run. The idea is that:
- The torch fx support in `t... | {
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https://api.github.com/repos/huggingface/transformers/issues/12223 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12223/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12223/comments | https://api.github.com/repos/huggingface/transformers/issues/12223/events | https://github.com/huggingface/transformers/issues/12223 | 923,724,892 | MDU6SXNzdWU5MjM3MjQ4OTI= | 12,223 | Argument `never_split` not working on `AutoTokenizer` | {
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"Ah, I believe the fast tokenizers do not have the `never_split` option. In order to achieve this I would add the tokens to the vocabulary instead cc @n1t0 is there another way to handle this?\r\n\r\n```py\r\n>>> tokenizer.tokenize(\"lol that's funny\")\r\n['lo', '##l', 'that', \"'\", 's', 'funny']\r\n>>> tokenizer... | 1,623 | 1,627 | 1,627 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.6.1
- Platform: Linux-4.19.0-14-cloud-amd64-x86_64-with-debian-10.7
- Python version: 3.7.9
- PyTorch vers... | {
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"@Narsil Curious if you already observed improved performance through this mode? ",
"So small, not really worth it right now. (a few percent tops)\r\n\r\nMain roadblock is that the context manager does not exist in torch 1.7 which is still supported by transformers. (So enabling it would mean adding more logic in... | 1,623 | 1,628 | 1,628 | CONTRIBUTOR | null | # What does this PR do?
This won't work on torch==1.7.1 but does on >=1.8.1 (LTS).
Question is, should we enable this with a compatibility layer, or simply do nothing.
I think we need a bit of benchmarking to assess the value of this change first.
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"Maybe @n1t0 has an idea!",
"This is totally expected behavior. This tokenizer uses the same cleanup steps that were used in BERT, and this character is specifically removed.\r\n\r\nCf here on line 492:\r\nhttps://github.com/huggingface/transformers/blob/32dbb2d/src/transformers/models/bert/tokenization_bert.py#L... | 1,623 | 1,623 | 1,623 | NONE | null | ## Environment info
- `transformers` version: 4.5.1
- Platform: Linux-4.4.0-19041-Microsoft-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.5
- PyTorch version (GPU?): 1.8.1+cu102 (False)
- Tensorflow version (GPU?): 2.4.1 (False)
- 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/12220 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12220/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12220/comments | https://api.github.com/repos/huggingface/transformers/issues/12220/events | https://github.com/huggingface/transformers/issues/12220 | 923,635,462 | MDU6SXNzdWU5MjM2MzU0NjI= | 12,220 | [Trainer.py] tr_loss in trainer with distributed training | {
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"Since it's averaged over all the training mini-batches, it should be a good representation of the real training loss. I'd personally avoid any complexity and add a new reduce operation here, since a user can always evaluate on the training set to get the \"real\" training loss if they absolutely need to. Does that... | 1,623 | 1,623 | 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: 4.4, not very sure
- Platform: linux
- Python version: 3.7
- PyTorch version (GPU?): 1.7
- Tensorflow versi... | {
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https://api.github.com/repos/huggingface/transformers/issues/12219 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12219/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12219/comments | https://api.github.com/repos/huggingface/transformers/issues/12219/events | https://github.com/huggingface/transformers/pull/12219 | 923,570,044 | MDExOlB1bGxSZXF1ZXN0NjcyMzIyMjg5 | 12,219 | Enabling users to provide their own `stopping_criteria` + `logits_processor` to `generate`. | {
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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)... | 1,623 | 1,640 | 1,640 | CONTRIBUTOR | null | # What does this PR do?
Fixes #12118
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https://api.github.com/repos/huggingface/transformers/issues/12218 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12218/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12218/comments | https://api.github.com/repos/huggingface/transformers/issues/12218/events | https://github.com/huggingface/transformers/issues/12218 | 923,510,936 | MDU6SXNzdWU5MjM1MTA5MzY= | 12,218 | T5 model seq2seq text generation using word embeddings instead of token_ids does not work | {
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"Hey @jerry3chen, \r\n\r\nCan you post a fully reproducible code snippet so that I can take a look? :-)",
"Hi @patrickvonplaten,\r\n\r\nI will post some more detailed codes. But this is downstream task so it is probably not ideal to have all of the code.\r\nI will just post down all of the parts that involve the ... | 1,623 | 1,637 | 1,627 | NONE | null | Hi there,
I trained a MT5ForConditionalGeneration model. During training, I used my own embeddings for encoding (but default embeddings for decoding). However, when I try to generate output using generate function, it will give me an error message. I will post the code and error message in the following:
Here is ... | {
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https://api.github.com/repos/huggingface/transformers/issues/12217 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12217/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12217/comments | https://api.github.com/repos/huggingface/transformers/issues/12217/events | https://github.com/huggingface/transformers/pull/12217 | 923,384,401 | MDExOlB1bGxSZXF1ZXN0NjcyMTU1Njc5 | 12,217 | fix pt-1.9.0 `add_` deprecation | {
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"Can we had an import error in AdaFactor to error if the version is les than 1.5 then? It seems the code is only there.",
"Sure, I'm just not sure where we are at `transformers`-wise with minimal pt version, so it might be simpler to require pt-1.5+, but the suggestion you made works too for now.\r\n\r\nWould it ... | 1,623 | 1,623 | 1,623 | CONTRIBUTOR | null | This PR fixes a new pt-1.9.0 `add_` deprecation in several places.
The deprecation warnings:
```
UserWarning: This overload of add_ is deprecated:
add_(Number alpha, Tensor other)
Consider using one of the following signatures instead:
add_(Tensor other, *, Number alpha) (Triggered internally a... | {
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https://api.github.com/repos/huggingface/transformers/issues/12216 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12216/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12216/comments | https://api.github.com/repos/huggingface/transformers/issues/12216/events | https://github.com/huggingface/transformers/pull/12216 | 923,244,296 | MDExOlB1bGxSZXF1ZXN0NjcyMDI5NjYw | 12,216 | Fix blenderbot checkpoint convert codes. | {
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https://api.github.com/repos/huggingface/transformers/issues/12215 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12215/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12215/comments | https://api.github.com/repos/huggingface/transformers/issues/12215/events | https://github.com/huggingface/transformers/issues/12215 | 923,218,997 | MDU6SXNzdWU5MjMyMTg5OTc= | 12,215 | Missing PredictionHeadTransform for BertGenerationDecoder | {
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"SImilarly, `token_type_embeddings` is also missing for [BertGenerationEmbeddings](https://github.com/huggingface/transformers/blob/v4.6.0/src/transformers/models/bert_generation/modeling_bert_generation.py#L133).",
"This issue has been automatically marked as stale because it has not had recent activity. If you ... | 1,623 | 1,631 | 1,631 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.6.0
### Who can help
@LysandreJik
## Information
Model I am using (Bert, XLNet ...): Bert, BertForG... | {
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https://api.github.com/repos/huggingface/transformers/issues/12214 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12214/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12214/comments | https://api.github.com/repos/huggingface/transformers/issues/12214/events | https://github.com/huggingface/transformers/issues/12214 | 923,179,660 | MDU6SXNzdWU5MjMxNzk2NjA= | 12,214 | Getting 404 Client Error when loading BaptisteDoyen/camembert-base-xnli | {
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"There's a typo in your model identifier:\r\n```diff\r\n- BaptisteDoyen/camembert-base-xlni\r\n+ BaptisteDoyen/camembert-base-xnli\r\n```",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPle... | 1,623 | 1,627 | 1,627 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.6.1
- Platform: Linux-5.11.16-arch1-1-x86_64-with-glibc2.33
- Python version: 3.9.5
- PyTorch version (GPU... | {
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https://api.github.com/repos/huggingface/transformers/issues/12213 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12213/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12213/comments | https://api.github.com/repos/huggingface/transformers/issues/12213/events | https://github.com/huggingface/transformers/issues/12213 | 923,178,522 | MDU6SXNzdWU5MjMxNzg1MjI= | 12,213 | [Question] When pretraining a language model, can I choose to mask specific words? | {
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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)... | 1,623 | 1,627 | 1,627 | NONE | null | Hi there,
I apologize if this is answered anywhere. I need to pretrain a language model with some specific words masked. I was wondering if this is currently supported? Since language models are trained in an unsupervised way, I saw in the examples that the provided datasets don't need any labels. However, I was... | {
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https://api.github.com/repos/huggingface/transformers/issues/12212 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12212/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12212/comments | https://api.github.com/repos/huggingface/transformers/issues/12212/events | https://github.com/huggingface/transformers/issues/12212 | 923,126,639 | MDU6SXNzdWU5MjMxMjY2Mzk= | 12,212 | Clearer indication for overridden method in generation | {
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"Also putting this in the \"Fix generation docs\" task basket",
"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:... | 1,623 | 1,631 | null | NONE | null | The expectation for the `prepare_inputs_for_generation` function to be overridden can be made clearer by changing https://github.com/huggingface/transformers/blob/700cee344691afc41f68aa18fedea463b22f95f1/src/transformers/generation_utils.py#L369-L374
to raise a `NotImplementedError` that provides the information men... | {
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https://api.github.com/repos/huggingface/transformers/issues/12210 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12210/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12210/comments | https://api.github.com/repos/huggingface/transformers/issues/12210/events | https://github.com/huggingface/transformers/issues/12210 | 923,106,608 | MDU6SXNzdWU5MjMxMDY2MDg= | 12,210 | Better documentation for generation parameter defaults | {
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"Fine by me! I think it can just be stated at the beginning before each arg is documented.",
"Putting this is the \"Improve generation task basket\" so that this is handled once the generation docs are improved as well",
"This issue has been automatically marked as stale because it has not had recent activity. ... | 1,623 | 1,631 | null | MEMBER | null | # Generation default params documentation
It's very hard to follow how the generation parameters are set when running generation. When looking at the official function: https://github.com/huggingface/transformers/blob/700cee344691afc41f68aa18fedea463b22f95f1/src/transformers/generation_utils.py#L644 all parameters d... | {
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https://api.github.com/repos/huggingface/transformers/issues/12209 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12209/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12209/comments | https://api.github.com/repos/huggingface/transformers/issues/12209/events | https://github.com/huggingface/transformers/issues/12209 | 923,058,019 | MDU6SXNzdWU5MjMwNTgwMTk= | 12,209 | The kernel appears to have died. It will restart automatically. from transformers import pipeline | {
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"Could you share a colab with a reproducible code example so that we may take a look? Thank you!",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow t... | 1,623 | 1,627 | 1,627 | NONE | null | I am working on the Jupyter Notebook
With the code:
`from transformers import pipeline`
I get:
"The kernel appears to have died. It will restart automatically."
Can someone explain to me what I have to do to fix this? I have already installed tensorflow and transformers. | {
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https://api.github.com/repos/huggingface/transformers/issues/12208 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12208/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12208/comments | https://api.github.com/repos/huggingface/transformers/issues/12208/events | https://github.com/huggingface/transformers/pull/12208 | 923,048,579 | MDExOlB1bGxSZXF1ZXN0NjcxODUzNDcy | 12,208 | AutoTokenizer: infer the class from the tokenizer config if possible | {
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This PR adds the functionality to load a tokenizer with `AutoTokenizer.from_pretrained` after saving it locally (without saving the model config in the same folder).
To do this, the proper tokenizer class is saved in `tokenizer_config.json` and the `AutoTokenizer.from_pretrained` method wi... | {
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https://api.github.com/repos/huggingface/transformers/issues/12207 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12207/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12207/comments | https://api.github.com/repos/huggingface/transformers/issues/12207/events | https://github.com/huggingface/transformers/pull/12207 | 923,036,791 | MDExOlB1bGxSZXF1ZXN0NjcxODQyODY4 | 12,207 | Pipeline update & tests | {
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https://api.github.com/repos/huggingface/transformers/issues/12206 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12206/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12206/comments | https://api.github.com/repos/huggingface/transformers/issues/12206/events | https://github.com/huggingface/transformers/pull/12206 | 923,022,712 | MDExOlB1bGxSZXF1ZXN0NjcxODMwMzYy | 12,206 | Add TFHubertModel | {
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"Hey @will-rice,\r\n\r\nWow that was quick! :D Can you remove the [WIP] whenever the PR is ready for review? :-)",
"One thing that's different from the PyTorch version is I couldn't use the copy comments because I added the type to the config arguments in Wav2Vec2. If I retained the copy comments it would overwri... | 1,623 | 1,625 | 1,625 | CONTRIBUTOR | null | # What does this PR do?
This PR adds the TFHubert Model.
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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/12205 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12205/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12205/comments | https://api.github.com/repos/huggingface/transformers/issues/12205/events | https://github.com/huggingface/transformers/pull/12205 | 922,902,435 | MDExOlB1bGxSZXF1ZXN0NjcxNzIyNzI5 | 12,205 | [Docs] fixed broken link | {
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"Thanks again!"
] | 1,623 | 1,623 | 1,623 | CONTRIBUTOR | null | # What does this PR do?
Fixes #12200
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md#start-contributing-pull-request... | {
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https://api.github.com/repos/huggingface/transformers/issues/12204 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12204/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12204/comments | https://api.github.com/repos/huggingface/transformers/issues/12204/events | https://github.com/huggingface/transformers/pull/12204 | 922,863,707 | MDExOlB1bGxSZXF1ZXN0NjcxNjg4MTIx | 12,204 | (#12203) Fix blenderbot checkpoint convert codes. | {
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https://api.github.com/repos/huggingface/transformers/issues/12203 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12203/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12203/comments | https://api.github.com/repos/huggingface/transformers/issues/12203/events | https://github.com/huggingface/transformers/issues/12203 | 922,862,638 | MDU6SXNzdWU5MjI4NjI2Mzg= | 12,203 | blenderbot checkpoint convert script has bug. | {
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"Now I have almost fixed the bug. I will PR soon."
] | 1,623 | 1,623 | 1,623 | CONTRIBUTOR | null | - error
- original parlai checkpoint
- so, we should fix codes like below.
```pytho... | {
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https://api.github.com/repos/huggingface/transformers/issues/12202 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12202/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12202/comments | https://api.github.com/repos/huggingface/transformers/issues/12202/events | https://github.com/huggingface/transformers/issues/12202 | 922,709,925 | MDU6SXNzdWU5MjI3MDk5MjU= | 12,202 | Training in google colab with TPU using TFTrainer fails with | {
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"Hi! We're trying to move away from using TFTrainer for TensorFlow and instead train models with the native Keras API. We have a full example using the Keras approach here: https://github.com/huggingface/transformers/tree/master/examples/tensorflow/text-classification\r\n\r\nTraining on TPU with this example works ... | 1,623 | 1,630 | 1,629 | NONE | null | ## Environment info
- `transformers` version: 4.6.1
- Platform: Linux-5.4.104+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.10
- PyTorch version (GPU?): 1.8.1+cu101 (False)
- Tensorflow version (GPU?): 2.5.0 (False)
- Using GPU in script?: Using TPU
- Using distributed or parallel set-up in script?: I... | {
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https://api.github.com/repos/huggingface/transformers/issues/12201 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12201/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12201/comments | https://api.github.com/repos/huggingface/transformers/issues/12201/events | https://github.com/huggingface/transformers/issues/12201 | 922,684,254 | MDU6SXNzdWU5MjI2ODQyNTQ= | 12,201 | ValueError: char_to_token() is not available when using Python based tokenizers ; XLNetTokenizer and encodings.char_to_token bug ; | {
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"Why are you not using the fast tokenizer? The error message tells you that the feature `char_to_token` is not available for the slow (i.e. python) tokenizers because nobody has implemented it yet.",
"@cronoik , I ran the same with Fast Tokenizer (XLNetTokenizerFast) on \"xlnet-base-cased\" , although char_to_to... | 1,623 | 1,653 | 1,624 | 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: 4.6.1
- Platform: Windows
- Python version: 3.8.8
- PyTorch version (GPU?): 1.8.1 , GPU enabled
- Tensorflo... | {
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https://api.github.com/repos/huggingface/transformers/issues/12200 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12200/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12200/comments | https://api.github.com/repos/huggingface/transformers/issues/12200/events | https://github.com/huggingface/transformers/issues/12200 | 922,675,185 | MDU6SXNzdWU5MjI2NzUxODU= | 12,200 | [Docs] Broken Link in the Benchmarks.rst | {
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"Don't hesitate to submit a PR with a fix!"
] | 1,623 | 1,623 | 1,623 | CONTRIBUTOR | null | ## Issue info
In the documentation at [Benchmarks page](https://huggingface.co/transformers/benchmarks.html) the last link is broken due to the reordering of examples folders
It is
```
With the new `benchmark` tools, it is easier than ever to share your benchmark results with the community
:prefix_link:`here ... | {
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https://api.github.com/repos/huggingface/transformers/issues/12199 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12199/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12199/comments | https://api.github.com/repos/huggingface/transformers/issues/12199/events | https://github.com/huggingface/transformers/pull/12199 | 922,582,895 | MDExOlB1bGxSZXF1ZXN0NjcxNDQwMjYx | 12,199 | [WIP] TensorFlow variant of DataCollatorForLanguageModeling. | {
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"Thanks a lot for your PR!\r\n\r\nBefore I review more in detail, could you provide an example of use of this API? Data-collators are very PyTorch-ic so I want to make sure this is something that can actually be used in TensorFlow without too many contorsions.",
"> Thanks a lot for your PR!\r\n> \r\n> Before I re... | 1,623 | 1,632 | 1,632 | CONTRIBUTOR | null | Co-authored-by: Dalton Walker <dalton_walker@icloud.com>
# What does this PR do?
We didn't see any support for TensorFlow within the DataCollatorForLanguageModeling data class. Integrating directly with TensorFlow seems useful for TensorFlow users and avoids the necessity for tensor conversion.
This PR adds a ... | {
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https://api.github.com/repos/huggingface/transformers/issues/12198 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12198/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12198/comments | https://api.github.com/repos/huggingface/transformers/issues/12198/events | https://github.com/huggingface/transformers/pull/12198 | 922,568,134 | MDExOlB1bGxSZXF1ZXN0NjcxNDI3MzEx | 12,198 | Enabling AutoTokenizer for HubertConfig. | {
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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 with a d... | {
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https://api.github.com/repos/huggingface/transformers/issues/12197 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12197/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12197/comments | https://api.github.com/repos/huggingface/transformers/issues/12197/events | https://github.com/huggingface/transformers/issues/12197 | 922,558,528 | MDU6SXNzdWU5MjI1NTg1Mjg= | 12,197 | XLM-RoBERTa MLM Trainer not saving 'sentencepiece.bpe.model' file | {
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"Without seeing your training script, it's impossible to diagnose what went wrong. I just tried a `tokenizer.save_pretrained(...)` with this model and I get all the files.",
"Hey @sgugger, thanks for the quick reply! I was making a very stupid mistake(typo) and haven't noticed it until now.\r\nI was using 'robert... | 1,623 | 1,623 | 1,623 | NONE | null | ## Environment info (Colab)
- `transformers` version: 4.7.0.dev0
- Platform: Linux-5.4.104+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.10
- PyTorch version (GPU?): 1.8.1+cu101 (True)
- Tensorflow version (GPU?): 2.5.0 (True)
- Using GPU in script?: Yes
- Using distributed or parallel set-up in scrip... | {
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https://api.github.com/repos/huggingface/transformers/issues/12196 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12196/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12196/comments | https://api.github.com/repos/huggingface/transformers/issues/12196/events | https://github.com/huggingface/transformers/issues/12196 | 922,525,627 | MDU6SXNzdWU5MjI1MjU2Mjc= | 12,196 | Where I can find official pretrained weights of SOP in Albert and NSP in Bert? | {
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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)... | 1,623 | 1,631 | 1,631 | NONE | null | Hi Guys,
I was checking for the pre-trained weights ( 2 layer classifier ) of ```SOP``` in ```Albert``` and ```NSP``` in ```Bert```.
Seems like it is initializing randomly every time.
Can we have the official weights loaded here or is it not available from official models?
Can anyone clarify please.
Thanks... | {
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https://api.github.com/repos/huggingface/transformers/issues/12195 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12195/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12195/comments | https://api.github.com/repos/huggingface/transformers/issues/12195/events | https://github.com/huggingface/transformers/issues/12195 | 922,508,786 | MDU6SXNzdWU5MjI1MDg3ODY= | 12,195 | Batched pipeline for NER | {
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"This has been asked many times before, see #11244. However, the corresponding PR was not merged, see [this comment](https://github.com/huggingface/transformers/pull/11251#pullrequestreview-637488364) for the reason."
] | 1,623 | 1,623 | 1,623 | NONE | null | Hi,
Is there a way to run batches with NER Pipeline rather than just one example?
Thanks. | {
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https://api.github.com/repos/huggingface/transformers/issues/12194 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12194/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12194/comments | https://api.github.com/repos/huggingface/transformers/issues/12194/events | https://github.com/huggingface/transformers/issues/12194 | 922,461,868 | MDU6SXNzdWU5MjI0NjE4Njg= | 12,194 | LayoutXLM not loaded | {
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"LayoutXLM is not yet supported by the AutoModel API. You can probably plug it into a `LayoutLMTokenizer` and a `LayoutLMForTokenClassification`. ",
"I had already tried that, but did not work.\r\n```\r\nmodel_name=\"microsoft/layoutxlm-base\"\r\ntokenizer = LayoutLMTokenizer.from_pretrained(model_name)\r\n```\r... | 1,623 | 1,627 | 1,627 | NONE | null | I am trying to use [layoutxlm model](https://huggingface.co/microsoft/layoutxlm-base), but I get the following error when loading either the tokenizer or the model with respectively `AutoTokenizer.from_pretrained("microsoft/layoutxlm-base")` or `AutoModelForTokenClassification.from_pretrained("microsoft/layoutxlm-base"... | {
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https://api.github.com/repos/huggingface/transformers/issues/12193 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12193/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12193/comments | https://api.github.com/repos/huggingface/transformers/issues/12193/events | https://github.com/huggingface/transformers/issues/12193 | 922,451,939 | MDU6SXNzdWU5MjI0NTE5Mzk= | 12,193 | Cannot import RobertaPreTrainedModel | {
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I tried with both transformers 3.5.1 and 4.6.1.
### Who can help
Maybe @julien-c since they contributed RoBERTa.
## Information
I want to derive my own class from RobertaPreTrainedModel, but I cannot import that class like I can import e.g. BertPreTrainedModel or AlbertPreTrainedModel. More... | {
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https://api.github.com/repos/huggingface/transformers/issues/12192 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12192/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12192/comments | https://api.github.com/repos/huggingface/transformers/issues/12192/events | https://github.com/huggingface/transformers/pull/12192 | 922,287,278 | MDExOlB1bGxSZXF1ZXN0NjcxMTgyNDU4 | 12,192 | Marian tatoeba conversion update | {
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"cc @patrickvonplaten who did the conversion",
"Hey @Traubert,\r\n\r\nThanks a lot for adapting the conversion script! Could you maybe post a link to a Marian Tatoeba model so that I can try it out? \r\n",
"I'll fix the issues you mentioned, and I think the output needs to be made a bit neater by omitting some ... | 1,623 | 1,632 | 1,632 | CONTRIBUTOR | null | # What does this PR do?
The Helsinki-NLP / Tatoeba NMT models have gone through various
architectural changes, and the old conversion code fails on them. This
commit is something of a rewrite to remedy this, in particular parsing
supplied yaml files rather than README.md files. It needs to be looked
at by someon... | {
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This PR updates the SageMaker documentation. It moves the overview to the bottom of the site, since it will grow. It also adds the Vision Transformer example. | {
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"you can try this:\r\ntokenizer.decode(tokenizer.encode('I 🙁 hate ☹️ to 😣 see 😖 this 😫 fail 😩 , 🥺 pls 😢 help 😭 me 😤'))\r\n\r\nIf the tokenizer successfully decodes back to origin emojis then yes! Your tokenizer can encode emojis.\r\nIn this case, you use distillroberta tokenizer which use BPE (Radford et a... | 1,623 | 1,626 | 1,626 | NONE | null | Hi, I am working on a dataset with emojis. I found that the BERT tokenizer doesn't support emojis, and we have to manually add them and train their embeddings (#7648). But the RoBERTa tokenizer seems to identify emojis on tokenization as the following code:
```Python3
tokenizer = AutoTokenizer.from_pretrained('distil... | {
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"from [https://github.com/huggingface/transformers/blob/master/src/transformers/generation_utils.py](url)\r\nrow 369-374:\r\n`\r\ndef prepare_inputs_for_generation(self, input_ids: torch.LongTensor, **kwargs) -> Dict[str, Any]: \r\n return {\"input_ids\": input_ids}\r\n`\r\nMaybe haven't a new way... | 1,623 | 1,627 | 1,627 | NONE | null | Hi,
I am working with the T5ConditionalGeneration for sequence generation. I am wondering that for autoregressively decoding outputs with the _generate()_ function, is there a way to decode a sequence from by feeding an intermediate layer input (such as _encoder_outputs_ or _input_embeds_) as opposed to the _input_i... | {
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https://api.github.com/repos/huggingface/transformers/issues/12188 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12188/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12188/comments | https://api.github.com/repos/huggingface/transformers/issues/12188/events | https://github.com/huggingface/transformers/issues/12188 | 921,979,144 | MDU6SXNzdWU5MjE5NzkxNDQ= | 12,188 | TextDatasetForNextSentencePrediction does not seem to contain truncate function unlike LineByLineWithSOPTextDataset | {
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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)... | 1,623 | 1,627 | 1,627 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.6.1
- Platform: Ubuntu 20.04.2 LTS
- Python version: 3.8.5
- PyTorch version (GPU?): 1.8.1 (Yes)
- Tensor... | {
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https://api.github.com/repos/huggingface/transformers/issues/12187 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12187/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12187/comments | https://api.github.com/repos/huggingface/transformers/issues/12187/events | https://github.com/huggingface/transformers/pull/12187 | 921,924,048 | MDExOlB1bGxSZXF1ZXN0NjcwODU4OTc0 | 12,187 | Clean push to hub API | {
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This PR reworks the way the push to hub API works by avoiding cloning in a temporary directory, copying the files saved then pushing, by creating and cloning the repo first, then saving the object and lastly pushing it to the hub. The general commands does not bring any major breaking change ... | {
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https://api.github.com/repos/huggingface/transformers/issues/12186 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12186/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12186/comments | https://api.github.com/repos/huggingface/transformers/issues/12186/events | https://github.com/huggingface/transformers/pull/12186 | 921,801,996 | MDExOlB1bGxSZXF1ZXN0NjcwNzUwMjIz | 12,186 | [WIP] Flax XLM | {
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"Hey @asvskartheek \r\n\r\nGreat to see that you started working on `FlaxXLM`! Feel free to ping me and @patrickvonplaten if you have any questions! Happy to help :)",
"Hey @patil-suraj , thanks for offering to help. Is there a general guide or a series of standard steps that can follow while porting models to F... | 1,623 | 1,627 | 1,627 | NONE | null | # What does this PR do?
This PR will add XLM in Flax/Jax
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"note that this can ultimately be in `huggingface_hub` rather than here (but it's great to be able to experiment with this here)",
"Yes we were talking about it with @LysandreJik, probably for after the upcoming release!"
] | 1,623 | 1,623 | 1,623 | COLLABORATOR | null | # What does this PR do?
This PR leverages `pyaml` to avoid writing yaml manually, as suggested by @julien-c . | {
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https://api.github.com/repos/huggingface/transformers/issues/12184 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12184/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12184/comments | https://api.github.com/repos/huggingface/transformers/issues/12184/events | https://github.com/huggingface/transformers/pull/12184 | 921,755,707 | MDExOlB1bGxSZXF1ZXN0NjcwNzEwNTE0 | 12,184 | Temporarily deactivate torchhub test | {
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This PR removes the torch hub test for now, as it seems there is a problem with the torch hub for now. Will investigate more tomorrow if need be. | {
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https://api.github.com/repos/huggingface/transformers/issues/12183 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12183/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12183/comments | https://api.github.com/repos/huggingface/transformers/issues/12183/events | https://github.com/huggingface/transformers/issues/12183 | 921,743,321 | MDU6SXNzdWU5MjE3NDMzMjE= | 12,183 | Inconsistency between GPTNeo and GPT2 config classes | {
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"Seconding this.\r\n\r\nLast month I swapped out GPT-2 for GPT-Neo in a [project](https://github.com/nostalgebraist/nostalgebraist-autoresponder/), and these differences made it more difficult to adapt my existing code.",
"Hi @leogao2 and @nostalgebraist, thanks for opening an issue! You're correct that the way t... | 1,623 | 1,631 | 1,631 | CONTRIBUTOR | null | The config classes for GPTNeo and GPT2 have a bunch of differences that are seemingly unnecessary. This makes it harder for downstream users to write code that depends on accessing these attributes. See below:
![image](https://user-images.githubusercontent.com/54557097/122113739-bbf92300-cddf-11eb-9ac6-a0ea1a30055b.... | {
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https://api.github.com/repos/huggingface/transformers/issues/12182 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12182/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12182/comments | https://api.github.com/repos/huggingface/transformers/issues/12182/events | https://github.com/huggingface/transformers/issues/12182 | 921,640,396 | MDU6SXNzdWU5MjE2NDAzOTY= | 12,182 | KeyError: 'labels' during Distilling Zero Shot Classification | {
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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)... | 1,623 | 1,660 | null | NONE | null | EDIT: I confirmed that this happens with the example script as it is, so no other changes are required to reproduce this.
## 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! -->
- `transform... | {
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https://api.github.com/repos/huggingface/transformers/issues/12181 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12181/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12181/comments | https://api.github.com/repos/huggingface/transformers/issues/12181/events | https://github.com/huggingface/transformers/pull/12181 | 921,611,837 | MDExOlB1bGxSZXF1ZXN0NjcwNTg5NzYx | 12,181 | Temporarily deactivate torch-scatter while we wait for new release | {
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"Requested the binary build:\r\nhttps://github.com/rusty1s/pytorch_scatter/issues/224\r\n",
"well, you can also change to `torch==1.8.1` and keep everything else the same.",
"That's a better alternative, let me update.",
"sorry, I meant `pip install torch==1.8.1` - torch-scatter doesn't have 1.8.1 - it's 1.8.... | 1,623 | 1,623 | 1,623 | MEMBER | null | Torch 1.9.0 just landed, incompatible with torch-scatter installed with version 1.8.0. While we wait for torch-scatter binaries compatible with 1.9.0 to be released, deactivating the torch-scatter-based tests.
cc @patrickvonplaten @sgugger @NielsRogge | {
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https://api.github.com/repos/huggingface/transformers/issues/12180 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12180/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12180/comments | https://api.github.com/repos/huggingface/transformers/issues/12180/events | https://github.com/huggingface/transformers/issues/12180 | 921,586,300 | MDU6SXNzdWU5MjE1ODYzMDA= | 12,180 | Can't run 124M using transformers | {
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"Do you have a reproducible code example, or a colab notebook? What is your environment as requested in the issue template? Did you try with a forward slash?",
"> Do you have a reproducible code example, or a colab notebook? What is your environment as requested in the issue template? Did you try with a forward s... | 1,623 | 1,627 | 1,627 | NONE | null | I have downloaded gpt 124M on my local machine and i was able to run the interactivesample.py that was provided by them
But when i try to load 124M using transformers, i get following error:
_OSError: Can't load config for 'models\124M'. Make sure that:
- 'models\124M' is a correct model ... | {
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"Hello, it seems there are a lot of changes in your PR. If you think this isn't the case, do you mind closing this and opening a new PR so that we may see the correct diff? Also feel free to ping @Rocketknight1 and @sgugger for review",
"Will do! We had some issues with git but we can clean it up and resubmit."
] | 1,623 | 1,623 | 1,623 | CONTRIBUTOR | null | Co-authored-by: Dalton Walker <dalton_walker@icloud.com>
# What does this PR do?
We didn't see any support for TensorFlow within the DataCollatorForLanguageModeling data class. Integrating directly with TensorFlow seems useful for TensorFlow users and avoids the necessity for tensor conversion.
This PR adds a ... | {
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"Hey @sven-h yes this is a known issue, same as https://github.com/huggingface/transformers/issues/11249.\r\n\r\nFrom this thread:\r\n\r\n> If you disable the memory tracker (pass in skip_memory_metrics=True into your TrainingArguments) then you will no longer get the pickling error. In the next transformers releas... | 1,623 | 1,623 | 1,623 | NONE | null | I currently face the problem that with recent versions of the transformers library (issue starting at version 4.5.0)
the hyperparameter search with ray tune runs into a serialization issue described below.
## Environment info
- `transformers` version: 4.5.0
- Platform: Linux-4.19.0-16-amd64-x86_64-with-glibc2.1... | {
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https://api.github.com/repos/huggingface/transformers/issues/12176 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12176/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12176/comments | https://api.github.com/repos/huggingface/transformers/issues/12176/events | https://github.com/huggingface/transformers/pull/12176 | 921,341,404 | MDExOlB1bGxSZXF1ZXN0NjcwMzU4MTM2 | 12,176 | Update conversion of Tatoeba marian models | {
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"Oops, this PR depends on merging a pull request to Tatoeba which hasn't happened yet. Closing for now."
] | 1,623 | 1,623 | 1,623 | CONTRIBUTOR | null | # What does this PR do?
The Helsinki-NLP / Tatoeba NMT models have gone through various
architectural changes, and the old conversion code fails on them. This
commit is something of a rewrite to remedy this, in particular parsing
supplied yaml files rather than README.md files. It needs to be looked
at by someon... | {
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"Hello! We don't have CI running with pytorch lightning so we would recommend opening an issue on their repository.\r\n\r\nDid you try a TPU training with the `Trainer` that comes with `transformers`? It should work fine on 8 cores.",
"Hello @LysandreJik, thanks for replying! \r\n\r\nYes, `🤗/Trainer` works perfe... | 1,623 | 1,627 | 1,627 | NONE | null | ## Environment info
- `transformers` version: 4.6.1
- Platform: Linux-5.4.104+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.10
- PyTorch version (GPU?): 1.8.1+cu101 (False)
- Tensorflow version (GPU?): 2.5.0 (False)
- Using GPU in script?: False
- Using distributed or parallel set-up in script?: False... | {
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https://api.github.com/repos/huggingface/transformers/issues/12174 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12174/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12174/comments | https://api.github.com/repos/huggingface/transformers/issues/12174/events | https://github.com/huggingface/transformers/issues/12174 | 921,311,804 | MDU6SXNzdWU5MjEzMTE4MDQ= | 12,174 | Pretrained XLM model with TLM objective generates nonsensical predictions | {
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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)... | 1,623 | 1,627 | 1,627 | NONE | null | Hi, I want to use the [`xlm-mlm-tlm-xnli15-1024`](https://huggingface.co/xlm-mlm-tlm-xnli15-1024) pretrained model, which is the XLM model trained with the auxiliary Translation Language Modeling (TLM) objective.
I want to give a translation pair to the model, mask some words in one of the sentences and then get ... | {
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https://api.github.com/repos/huggingface/transformers/issues/12173 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12173/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12173/comments | https://api.github.com/repos/huggingface/transformers/issues/12173/events | https://github.com/huggingface/transformers/pull/12173 | 921,266,049 | MDExOlB1bGxSZXF1ZXN0NjcwMjkzMjY2 | 12,173 | Use a released version of optax rather than installing from Git. | {
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ago)
# What does this PR do?
Update the version of Optax we depend on in Flax examples' requirement.py to the latest released version.
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks ... | {
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"Hi,\r\n\r\ncould you please ask this question on the [forum](https://discuss.huggingface.co/) rather than here? We like to keep Github issues for bugs/feature requests.\r\n\r\nThanks!",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be ... | 1,623 | 1,627 | 1,627 | NONE | null | Hi all, thank you so much for the wonderful service.
I have some doubts regarding the training details for MM-Imdb dataset.
Are the image encoder's and tokenizer's embeddings fine-tuned during training on MM-Imdb dataset? If not, can you suggest a way to do it or refer any material for help?
Is there a way to ... | {
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<!--
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"In HuggingFace Transformers, models typically output a dictionary. You can access the feature vector by getting the `pooler_output` key of that dictionary (assuming you're using `ViTModel`). It's a tensor of shape `(batch_size, hidden_size)`, so in case you're only providing a single image, and you're using the ba... | 1,623 | 1,638 | 1,623 | NONE | null | # 🚀 Feature request
## Motivation
I would like to see an example of using Vision Transformer just for feature extraction, get the feature vector, before the classification part of the neural network as can be done with tensorflow hub
https://www.tensorflow.org/hub/common_signatures/images?hl=en#image_feature_... | {
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"Would PR https://github.com/huggingface/transformers/pull/11119 help with your use-case?",
"> Would PR #11119 help with your use-case?\r\n\r\nIndeed, thanks!"
] | 1,623 | 1,623 | 1,623 | COLLABORATOR | null | In our research group we all have user accounts on a server where we each run our own experiments (Ubuntu behind the scenes). By default, everyone is downloading `transformers` models to their own home directory. Let's say we have 20 researchers, that might mean that we have 20 duplicates of "bert-base-cased" on the se... | {
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"Hello! What is your tokenizer? Is it a WordPiece-based tokenizer, or a Byte-level BPE-based tokenizer like the original one from RoBERTa?",
"Hi @LysandreJik, thanks for your reply and sorry that I'm just seeing this now. My tokenizer is a byte-level BPE-based tokenizer. ",
"Hi @LysandreJik, let me know if you ... | 1,623 | 1,672 | 1,625 | 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
- Python version: 3.8.5
- 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/12167 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12167/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12167/comments | https://api.github.com/repos/huggingface/transformers/issues/12167/events | https://github.com/huggingface/transformers/issues/12167 | 921,081,237 | MDU6SXNzdWU5MjEwODEyMzc= | 12,167 | ViT for resolution beyond 224x224 support | {
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"One would need to interpolate the pre-trained position embeddings. You can see how this is done in the original implementation [here](https://github.com/google-research/vision_transformer/blob/00883dd691c63a6830751563748663526e811cee/vit_jax/checkpoint.py#L224).\r\n\r\nYou can find a PyTorch implementation of that... | 1,623 | 1,631 | 1,623 | NONE | null | When the resolution changes, the size of position embedding of ViTModel also changes, which makes ```from_pretrained``` method not working.
So, how can I use ViT with a different resolution like 64x64? | {
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https://api.github.com/repos/huggingface/transformers/issues/12166 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12166/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12166/comments | https://api.github.com/repos/huggingface/transformers/issues/12166/events | https://github.com/huggingface/transformers/pull/12166 | 920,970,190 | MDExOlB1bGxSZXF1ZXN0NjcwMDQwMjA2 | 12,166 | [testing] ensure concurrent pytest workers use a unique port for torch.dist | {
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https://api.github.com/repos/huggingface/transformers/issues/12165 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12165/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12165/comments | https://api.github.com/repos/huggingface/transformers/issues/12165/events | https://github.com/huggingface/transformers/issues/12165 | 920,906,056 | MDU6SXNzdWU5MjA5MDYwNTY= | 12,165 | Documentation for tiny-gpt2 in transformers/examples/pytorch | {
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"It is randomly initialized and trained for 2 steps. So basically it can only be used for prototyping."
] | 1,623 | 1,623 | 1,623 | NONE | null | # 🚀 Documentation request
The **tiny-gpt2** transformer model is great for fast prototyping, but it seems sparsely documented on the Huggingface hub: https://huggingface.co/sshleifer/tiny-gpt2
## Motivation
It would be helpful if users knew basic info about how tiny-gpt2 was trained. Is it the same corpus as ... | {
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https://api.github.com/repos/huggingface/transformers/issues/12164 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12164/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12164/comments | https://api.github.com/repos/huggingface/transformers/issues/12164/events | https://github.com/huggingface/transformers/issues/12164 | 920,895,018 | MDU6SXNzdWU5MjA4OTUwMTg= | 12,164 | [testing] concurrent dist tests fail when using the same master_port | {
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"Would it be helpful to extract the tests that use the same port with a custom decorator, and run them in a separate `run` directive with `-n 1`?",
"That is a possibility too, see the simple proposed solution https://github.com/huggingface/transformers/pull/12166 - perhaps to try first."
] | 1,623 | 1,623 | 1,623 | CONTRIBUTOR | null | The failing `tests/extended/test_trainer_ext.py::TestTrainerExt::test_run_seq2seq_ddp` on multi-gpu slow runner happens because of concurrency of `-n 2` on push (it's `-n 1` on scheduled), so we end up with 2 dist tests running at the same time and clashing on ending up using the same default port used by `torch.distri... | {
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https://api.github.com/repos/huggingface/transformers/issues/12163 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12163/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12163/comments | https://api.github.com/repos/huggingface/transformers/issues/12163/events | https://github.com/huggingface/transformers/issues/12163 | 920,819,951 | MDU6SXNzdWU5MjA4MTk5NTE= | 12,163 | Missing code for predicting custom labels in Bert | {
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"Hi,\r\n\r\nTokenizers in HuggingFace Transformers don't take care of padding labels (this should be done by the user). You can only provide text to a tokenizer, and it will turn them into `input_ids`, `attention_mask` and `token_type_ids`. The `tokenize_and_align_labels` function will take care of labeling each to... | 1,623 | 1,686 | 1,627 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.6.1
- Platform: MacOS 10.15.7
- Python version: 3.8
- PyTorch version (GPU?): 1.8.1 No GPU
- Tensorflow v... | {
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https://api.github.com/repos/huggingface/transformers/issues/12162 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12162/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12162/comments | https://api.github.com/repos/huggingface/transformers/issues/12162/events | https://github.com/huggingface/transformers/pull/12162 | 920,762,663 | MDExOlB1bGxSZXF1ZXN0NjY5ODYzNjI0 | 12,162 | Add video links to the documentation | {
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This PR leverages some videos of the course and adds them to our documentation. | {
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https://api.github.com/repos/huggingface/transformers/issues/12161 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12161/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12161/comments | https://api.github.com/repos/huggingface/transformers/issues/12161/events | https://github.com/huggingface/transformers/pull/12161 | 920,709,515 | MDExOlB1bGxSZXF1ZXN0NjY5ODE4MjY2 | 12,161 | consistent nn. and nn.functional: part 5 docs | {
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```
# deal with torch.nn
perl -pi -e 's|^(\s*)import torch\n|$1from torch import nn\n$1import torch\n|' `grep -Ilr torch.nn docs`
find docs -type f -regextyp... | {
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https://api.github.com/repos/huggingface/transformers/issues/12160 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12160/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12160/comments | https://api.github.com/repos/huggingface/transformers/issues/12160/events | https://github.com/huggingface/transformers/pull/12160 | 920,705,079 | MDExOlB1bGxSZXF1ZXN0NjY5ODE0NDk0 | 12,160 | [Jax Slow Circle CI] Don't close PR | {
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"Thanks for the tip @stas00 ! \r\n\r\nI'll push to the PR every 24h to have a background circle ci test - eventually we should think about a better solution here",
"You can crontab an empty git push to trigger CI, e.g.:\r\n```\r\ncd transformers-flax-cron\r\ngit commit --allow-empty -m \"Trigger CI\"\r\ngit push\... | 1,623 | 1,626 | 1,626 | MEMBER | null | # What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this w... | {
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https://api.github.com/repos/huggingface/transformers/issues/12159 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12159/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12159/comments | https://api.github.com/repos/huggingface/transformers/issues/12159/events | https://github.com/huggingface/transformers/issues/12159 | 920,701,728 | MDU6SXNzdWU5MjA3MDE3Mjg= | 12,159 | Can't run QA fine-tune for bert/albert in distributed way | {
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"@sgugger @philschmid ",
"Could you confirm #11872 fixes it?",
"> Could you confirm #11872 fixes it?\r\n\r\nyeah, confirmed, closing issue."
] | 1,623 | 1,623 | 1,623 | 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: HEAD detached at v4.6.1
- Platform: Docker, AWS
- Python version: Python 3.8.5
- PyTorch version (GPU?): 1.... | {
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https://api.github.com/repos/huggingface/transformers/issues/12158 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12158/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12158/comments | https://api.github.com/repos/huggingface/transformers/issues/12158/events | https://github.com/huggingface/transformers/issues/12158 | 920,698,473 | MDU6SXNzdWU5MjA2OTg0NzM= | 12,158 | Pretraining for TFWav2Vec2 | {
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TFWav2Vec2 needs the pretraining implementation like the PyTorch [version](https://huggingface.co/transformers/master/model_doc/wav2vec2.html#wav2vec2forpretraining)
## Motivation
Users of the TensorFlow model will most likely want to be able to do pretraining just like with Pytorch.
#... | {
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https://api.github.com/repos/huggingface/transformers/issues/12157 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12157/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12157/comments | https://api.github.com/repos/huggingface/transformers/issues/12157/events | https://github.com/huggingface/transformers/pull/12157 | 920,677,887 | MDExOlB1bGxSZXF1ZXN0NjY5NzkxNDI3 | 12,157 | Add course banner | {
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"Merging so the image is online and I can then adjust the width if necessary."
] | 1,623 | 1,623 | 1,623 | COLLABORATOR | null | # What does this PR do?
This PR adds a course banner in the main README, looking like this:
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https://api.github.com/repos/huggingface/transformers/issues/12156 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12156/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12156/comments | https://api.github.com/repos/huggingface/transformers/issues/12156/events | https://github.com/huggingface/transformers/pull/12156 | 920,662,162 | MDExOlB1bGxSZXF1ZXN0NjY5Nzc4MDc3 | 12,156 | [style] consistent nn. and nn.functional: part 4 `examples` | {
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"> You have changes in two png files here too, which is weird. \r\n\r\nWhoah! Found some secret stenography embeddings! :)\r\n\r\nProbably got triggered by `s|(?<!\\w)F\\.|nn.functional.|g`\r\n\r\nThank you for noticing, @sgugger - will fix it up!\r\n\r\n> Not sure if we really need to apply this to the research p... | 1,623 | 1,623 | 1,623 | CONTRIBUTOR | null | This concludes the work on https://github.com/huggingface/transformers/issues/11600 with normalizing `examples` using fully automated:
```
# deal with torch.nn
perl -pi -e 's|^(\s*)import torch\n|$1from torch import nn\n$1import torch\n|' `grep -Ilr torch.nn examples`
find examples -type f -exec perl -X -pi -e 's... | {
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"> It looks like you have changes in two test fixtures, is that intended?\r\n\r\nOh, I was studying `git diff` and missed the binary change - thank you for noticing it, @sgugger - fixed. "
] | 1,623 | 1,623 | 1,623 | CONTRIBUTOR | null | Continuing https://github.com/huggingface/transformers/pull/12124 this PR takes care of `tests` - a slight variation of the automated code:
```
# deal with torch.nn
perl -pi -e 's|^(\s*)import torch\n|$1from torch import nn\n$1import torch\n|' `grep -Ilr torch.nn tests`
find tests -type f -exec perl -X -pi -e 's{... | {
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https://api.github.com/repos/huggingface/transformers/issues/12154 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12154/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12154/comments | https://api.github.com/repos/huggingface/transformers/issues/12154/events | https://github.com/huggingface/transformers/pull/12154 | 920,655,089 | MDExOlB1bGxSZXF1ZXN0NjY5NzcxODMz | 12,154 | [Flax] Fix flax pt equivalence tests | {
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<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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```
# deal with torch.nn
perl -pi -e 's|^import torch\n|from torch import nn\nimport torch\n|' `grep -Ilr torc... | {
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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)... | 1,623 | 1,627 | 1,627 | MEMBER | null | The first part of the Hugging Face Course is finally out!
Come learn how the :hugs: Ecosystem works :partying_face: : Transformers, Tokenizers, Datasets, Accelerate, the Model Hub!
Share with your friends who want to learn NLP, it's free!
Come join us at https://hf.co/course
Students following this course... | {
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https://api.github.com/repos/huggingface/transformers/issues/12151 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12151/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12151/comments | https://api.github.com/repos/huggingface/transformers/issues/12151/events | https://github.com/huggingface/transformers/issues/12151 | 920,472,474 | MDU6SXNzdWU5MjA0NzI0NzQ= | 12,151 | do_normalize set to True by default for WAV2VEC tokenizer | {
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"cc @patrickvonplaten ",
"Hey @Lhemamou, the parameter `do_normalize` is overwritten by the model's config: https://huggingface.co/facebook/wav2vec2-base-960h/blob/main/feature_extractor_config.json",
"Thanks @patrickvonplaten, it solved the issue ! :) . Nonetheless, in the code from [documentation](https://hug... | 1,623 | 1,626 | 1,626 | NONE | null | ## Environment info
- `transformers` version: 4.6.1
- Platform: macOS-11.2.3-x86_64-i386-64bit
- Python version: 3.8.2
- PyTorch version (GPU?): 1.8.1 (False)
- Tensorflow version (GPU?): 2.4.1 (False)
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No
### Who can help
@Lysandre... | {
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https://api.github.com/repos/huggingface/transformers/issues/12150 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12150/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12150/comments | https://api.github.com/repos/huggingface/transformers/issues/12150/events | https://github.com/huggingface/transformers/pull/12150 | 920,420,900 | MDExOlB1bGxSZXF1ZXN0NjY5NTczMTM0 | 12,150 | Flax T5 | {
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"Exceptionally merging already given the time constraint of the Flax/JAX community week announcement. \r\n@patil-suraj @sgugger, I would be very happy if you could nevertheless take a look after merge so that I can correct suggestions in a follow-up PR before the next transformers release.",
"Is a jax/flax byT5 p... | 1,623 | 1,624 | 1,624 | CONTRIBUTOR | null | # What does this PR do?
This PR will add T5 in Flax/Jax.
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md#start-contri... | {
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https://api.github.com/repos/huggingface/transformers/issues/12149 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12149/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12149/comments | https://api.github.com/repos/huggingface/transformers/issues/12149/events | https://github.com/huggingface/transformers/issues/12149 | 920,325,933 | MDU6SXNzdWU5MjAzMjU5MzM= | 12,149 | Feature request for encoding more than one pair of texts | {
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] | open | false | null | [] | [] | 1,623 | 1,623 | null | CONTRIBUTOR | null | # 🚀 Feature request
Currently, tokenizer may take only inputs like [['text_0', 'text_1']], would be beneficially to expand is as
[['text_0', 'text_1', ..., 'text_n']]
## Motivation
This would open a convenient way to deal with a new set of processing tasks.
## Your contribution
Don't have any. | {
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https://api.github.com/repos/huggingface/transformers/issues/12148 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/12148/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/12148/comments | https://api.github.com/repos/huggingface/transformers/issues/12148/events | https://github.com/huggingface/transformers/pull/12148 | 920,274,189 | MDExOlB1bGxSZXF1ZXN0NjY5NDQ3ODI0 | 12,148 | [Flax] fix error message | {
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Fix error message. | {
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Fixes #12105, improves some more docs and removes some unused variables in `modeling_detr.py`. | {
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Before:
```py
>>> from transformers import Speech2TextProcessor
>>> processor =Speech2TextProcessor.from_pretrained("facebook/s2t-small-librispeech-asr")
```
```out
Traceback (most recent call last):
File "<input>", line 1, in <module>
Attribut... | {
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"merged_at... |
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