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https://api.github.com/repos/huggingface/transformers/issues/14253 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14253/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14253/comments | https://api.github.com/repos/huggingface/transformers/issues/14253/events | https://github.com/huggingface/transformers/pull/14253 | 1,042,795,531 | PR_kwDOCUB6oc4uAPE3 | 14,253 | [deepspeed] zero inference | {
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"Thanks a lot for the review and the suggestions, Sylvain. All addressed, please have another look at your convenience. Thank you."
] | 1,635 | 1,637 | 1,637 | CONTRIBUTOR | null | This PR extends HF/DS integration to support Deepspeed Zero inference. Now we don't need to waste gpu memory on allocating the optimizer/scheduler and then dropping them. And in some cases enabling what was not possible before - in case the user doesn't have the extra gpu memory and was getting OOM on inference.
Blo... | {
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https://api.github.com/repos/huggingface/transformers/issues/14252 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14252/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14252/comments | https://api.github.com/repos/huggingface/transformers/issues/14252/events | https://github.com/huggingface/transformers/issues/14252 | 1,042,756,423 | I_kwDOCUB6oc4-JzNH | 14,252 | Fast tokenizer converter leads to PanicException: no entry found for key | {
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"Hey @gchhablani,\r\n\r\nThanks a lot for the in-detail issue! Could we in a first step upload the slow tokenizer to verify that it works correctly? In a next step we can then convert it to a fast tokenizer ",
"Given that `mbart` has a very specific tokenization, we might have to add a new `tokenization_plbart.... | 1,635 | 1,646 | 1,646 | CONTRIBUTOR | null | I am working on adding PLBart's tokenizer. The tokenizer uses `sentencepiece.bpe.model` and is similar to MBart. Hence, to convert to fast tokenizer, I used the same converter - `MBartConverter` and modified it. The definition is as follows and can also be found [here](https://github.com/huggingface/transformers/blob/5... | {
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https://api.github.com/repos/huggingface/transformers/issues/14251 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14251/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14251/comments | https://api.github.com/repos/huggingface/transformers/issues/14251/events | https://github.com/huggingface/transformers/pull/14251 | 1,042,697,324 | PR_kwDOCUB6oc4t_8ph | 14,251 | Update Transformers to huggingface_hub >= 0.1.0 | {
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This PR updates the minimum version of huggingface_hub to 0.1.0 and makes all the simplifications related to `HfApi` methods being exposed as functions.
Note that some of the commands that relied on the old HfApi were failing since the switch a few versions ago but no issue was opened. Thi... | {
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https://api.github.com/repos/huggingface/transformers/issues/14250 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14250/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14250/comments | https://api.github.com/repos/huggingface/transformers/issues/14250/events | https://github.com/huggingface/transformers/pull/14250 | 1,042,605,571 | PR_kwDOCUB6oc4t_qED | 14,250 | Adding utilities to chunk large audio files and read directly from microphone | {
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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)... | 1,635 | 1,648 | 1,648 | CONTRIBUTOR | null | ------------
This PR and was slowly merged bits by bits (with sometimes major changes) into transformers.
Keeping it open for VAD chunking which is in this PR and not yet available in transormers
------------
- chunk_files, requires scipy only, relatively straightforward.
- vad_files, requires webrtcvad, will ch... | {
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This PR should fix the failing tests for Beit training in PyTorch 1.10+ (at least it does locally) | {
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https://api.github.com/repos/huggingface/transformers/issues/14248 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14248/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14248/comments | https://api.github.com/repos/huggingface/transformers/issues/14248/events | https://github.com/huggingface/transformers/issues/14248 | 1,042,594,215 | I_kwDOCUB6oc4-JLmn | 14,248 | TROCR custom dataset | {
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"Hi!\r\n\r\nThanks for your interest in using `VisionEncoderDecoderModel`.\r\n\r\nThe steps to proceed would be:\r\n1. train a new tokenizer on your custom text data, using [HuggingFace Tokenizers](https://github.com/huggingface/tokenizers). Could be a BPE (byte pair encoding) tokenizer for instance. Next, initiali... | 1,635 | 1,655 | 1,639 | NONE | null | Hi everyone
I would like to train a visionencoderdecoder on a custom dataset
Which I hope my decoder can decode different words from custom vocabulary
How can I train my own model without using any pretrained model
Thanks | {
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https://api.github.com/repos/huggingface/transformers/issues/14247 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14247/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14247/comments | https://api.github.com/repos/huggingface/transformers/issues/14247/events | https://github.com/huggingface/transformers/issues/14247 | 1,042,560,846 | I_kwDOCUB6oc4-JDdO | 14,247 | AttributeError: 'T5Config' object has no attribute 'output_scores' | {
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"@MariamDundua May I ask why you are using ```model_up.model.generate``` instead of just ```model_up.generate``` ?\r\nIt will be very helpful If you could share the colab link. 😄 ",
"@Atharva-Phatak Here is the link\r\n[github](https://github.com/MariamDundua/Mariam-Dundua/blob/master/t5_base_training_on_QA.ipy... | 1,635 | 1,636 | 1,636 | 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:4.12.2
- Platform: Google collab
- Python version:
- PyTorch version (GPU?): Tesla K80
- Tensorflow versio... | {
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https://api.github.com/repos/huggingface/transformers/issues/14246 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14246/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14246/comments | https://api.github.com/repos/huggingface/transformers/issues/14246/events | https://github.com/huggingface/transformers/pull/14246 | 1,042,540,553 | PR_kwDOCUB6oc4t_ckC | 14,246 | Add PushToHubCallback in main init | {
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This adds `PushToHubCallback` in the main init so it's easily imported. | {
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Fixes the test since the model was moved to the authors' org | {
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"Finished ci test and passed all.",
"Hey @ZIZUN, \r\n\r\nThanks for the PR! Do we have a fine-tuned checkpoint for `BartForTokenClassification`? I'm wondering how useful this architecture is",
"Hello @patrickvonplaten \r\nYes, I tried to finetune this architecture for the Korean NER dataset. The results are as ... | 1,635 | 1,638 | 1,636 | NONE | null | # What does this PR do?
+ Add BartForTokenClassification class for NER task
## Before submitting
- [x] Did you read the [contributor guideline]
- [x] Did you make sure to update the documentation with your changes?
- [x] Did you write any new necessary tests?
## Who can review?
Anyone in the community is f... | {
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"Hey @Jabb0, \r\n\r\nWhile `model.config.max_position_embeddings` says 514 is the maximum allowed # of position embeddings, the actual number is 512. One should rather look at:\r\n\r\n```python\r\nfrom transformers import RobertaTokenizer\r\ntok = RobertaTokenizer.from_pretrained(\"roberta-large\")\r\ntok.model_max... | 1,635 | 1,635 | 1,635 | 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: 4.11.3
- Platform: Linux-5.13.0-7614-generic-x86_64-with-glibc2.33
- Python version: 3.8.12
- PyTorch versio... | {
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https://api.github.com/repos/huggingface/transformers/issues/14242 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14242/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14242/comments | https://api.github.com/repos/huggingface/transformers/issues/14242/events | https://github.com/huggingface/transformers/issues/14242 | 1,042,273,364 | I_kwDOCUB6oc4-H9RU | 14,242 | CausalLMHead Models do not register head parameters. | {
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"This is because input- and output embeddings are tied (i.e. shared).\r\n\r\nBut this causes a lot of confusion, I know. Would be better indeed if these get included in the named parameters of a model. cc @LysandreJik ",
"Thanks for the explanation. Makes sense. I am nut sure including it in the named parameters ... | 1,635 | 1,639 | 1,639 | NONE | null | ## Environment info
- `transformers` version: 4.12.2
- Platform: Linux-5.4.0-87-generic-x86_64-with-glibc2.10
- Python version: 3.8.8
- PyTorch version (GPU?): 1.9.1+cu111 (True)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- Ja... | {
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https://api.github.com/repos/huggingface/transformers/issues/14241 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14241/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14241/comments | https://api.github.com/repos/huggingface/transformers/issues/14241/events | https://github.com/huggingface/transformers/pull/14241 | 1,042,265,756 | PR_kwDOCUB6oc4t-iBg | 14,241 | Fix of issue #13327: Wrong weight initialization for TF t5 model | {
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"This looks great! The only change I'd suggest is that we don't usually sign names on comments - there are a lot of contributors to this repo and it could get out of hand.",
"Looks good! Let me know when you're happy and I'll merge it.",
"You can merge it. I only saw your comment and didnt see you already pushe... | 1,635 | 1,635 | 1,635 | CONTRIBUTOR | null | # What does this PR do?
Fixes # 13327
## Who can review?
@patrickvonplaten
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https://api.github.com/repos/huggingface/transformers/issues/14240 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14240/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14240/comments | https://api.github.com/repos/huggingface/transformers/issues/14240/events | https://github.com/huggingface/transformers/pull/14240 | 1,042,112,566 | PR_kwDOCUB6oc4t-MwA | 14,240 | Add ImageGPT | {
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"I'm trying to use the notebook you linked, but I'm receiving an import error:\r\n\r\nImportError: cannot import name 'ImageGPTForCausalLM' from 'transformers' (/usr/local/lib/python3.7/dist-packages/transformers/__init__.py)",
"Hi @NielsRogge! I just realized the [original Image GPT architecture](https://github.... | 1,635 | 1,637 | 1,637 | CONTRIBUTOR | null | # What does this PR do?
This PR adds [ImageGPT](https://openai.com/blog/image-gpt/), "Generative Pre-training from Pixels", by OpenAI. ImageGPT is to GPT2 what ViT is to BERT.
OpenAI released 3 variants (small, medium and large) more than a year ago. Models are on the hub: https://huggingface.co/models?other=imag... | {
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https://api.github.com/repos/huggingface/transformers/issues/14239 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14239/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14239/comments | https://api.github.com/repos/huggingface/transformers/issues/14239/events | https://github.com/huggingface/transformers/pull/14239 | 1,041,953,754 | PR_kwDOCUB6oc4t9rrD | 14,239 | Resolved TROCR Microsoft Large Printed Bug #14238 | {
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"Hmm. That's strange, check_code_quality fails.\r\n\r\nCan the mods guide me n how to improve that? CircleCI says :\r\n\r\n```\r\n#!/bin/bash -eo pipefail\r\nblack --check examples tests src utils\r\nwould reformat src/transformers/image_utils.py\r\nOh no! 💥 💔 💥\r\n1 file would be reformatted, 1139 files would b... | 1,635 | 1,641 | 1,641 | NONE | null | Original Image Output Size : (X,Y)
Original Std Dev and Mean Shape : (3,)
Reshaping the Image to Shape : (1,X,Y) solves the bug, which is implemented in the code!
# What does this PR do?
<!--
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https://api.github.com/repos/huggingface/transformers/issues/14238 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14238/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14238/comments | https://api.github.com/repos/huggingface/transformers/issues/14238/events | https://github.com/huggingface/transformers/issues/14238 | 1,041,949,771 | I_kwDOCUB6oc4-GuRL | 14,238 | Bug in Microsoft TROCR Large | {
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"Hi,\r\n\r\nThanks for spotting. The problem is that the image is grey-scale, meaning no color channels, and the normalize method defined in `image_utils.py` assumes 3 dimensions.\r\n\r\nYou can fix it by making sure the image has 3 dimensions, i.e. \r\n\r\n`image = Image.open(requests.get(url, stream=True).raw).co... | 1,635 | 1,665 | 1,639 | NONE | null | ## Environment info
- `transformers` version: 4.12.2
- Platform: Linux-5.11.0-1020-azure-x86_64-with-debian-bullseye-sid
- Python version: 3.7.11
- PyTorch version (GPU?): 1.10.0+cu102 (False)
- Tensorflow version (GPU?): 2.6.1 (False)
- Flax version (CPU?/GPU?/TPU?): 0.3.6 (cpu)
- Jax version: 0.2.24
- JaxLi... | {
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https://api.github.com/repos/huggingface/transformers/issues/14237 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14237/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14237/comments | https://api.github.com/repos/huggingface/transformers/issues/14237/events | https://github.com/huggingface/transformers/pull/14237 | 1,041,809,644 | PR_kwDOCUB6oc4t9OuV | 14,237 | enable bfloat16 support on t5 model for summarization | {
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"`torch.bfloat16` is not supported in `torch==1.4.0` (for example). Are you providing appropriate checks and backward compatibility with `torch` supported (AFAIK `transformers` support `torch>=1.1.0`)?",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this s... | 1,635 | 1,639 | 1,639 | NONE | null | # What does this PR do?
<!--
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/14236 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14236/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14236/comments | https://api.github.com/repos/huggingface/transformers/issues/14236/events | https://github.com/huggingface/transformers/pull/14236 | 1,041,797,344 | PR_kwDOCUB6oc4t9MW7 | 14,236 | Added an error when `temperature` is defined but `do_sample` is False. | {
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"@patrickvonplaten Added as an edit, not sure if it pinged you.",
"The test that fails has nothing to do with this change",
"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 ... | 1,635 | 1,638 | 1,638 | NONE | null | # What does this PR do?
This is to prevent the possibility that people think that setting a temperature is enough to get sampling behavior.
I found this confusing at first.
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case): No, but is kind... | {
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https://api.github.com/repos/huggingface/transformers/issues/14234 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14234/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14234/comments | https://api.github.com/repos/huggingface/transformers/issues/14234/events | https://github.com/huggingface/transformers/issues/14234 | 1,041,670,260 | I_kwDOCUB6oc4-FqB0 | 14,234 | Trainer bug in BertForQuestionAnswering when Pretrained model wasn't trained on NPS | {
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"If you just drop the `token_type_ids` key from your dataset, or replace them all by zeros, then the training will succeed, so this is not a bug in the `Trainer`, just a mistake in the processing of the dataset.",
"This issue has been automatically marked as stale because it has not had recent activity. If you th... | 1,635 | 1,639 | 1,639 | NONE | null | ## Environment info
`transformers` version: 4.12.2
- Platform: Windows-10-10.0.19041-SP0
- Python version: 3.8.5
- PyTorch version (GPU?): 1.10.0+cpu (False)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
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https://api.github.com/repos/huggingface/transformers/issues/14233 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14233/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14233/comments | https://api.github.com/repos/huggingface/transformers/issues/14233/events | https://github.com/huggingface/transformers/pull/14233 | 1,041,573,471 | PR_kwDOCUB6oc4t8kEl | 14,233 | Cl tohoku japanese roberta | {
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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)... | 1,635 | 1,645 | 1,645 | MEMBER | null | null | {
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https://api.github.com/repos/huggingface/transformers/issues/14232 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14232/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14232/comments | https://api.github.com/repos/huggingface/transformers/issues/14232/events | https://github.com/huggingface/transformers/pull/14232 | 1,041,411,639 | PR_kwDOCUB6oc4t8GYN | 14,232 | improving efficiency of mlflow metric logging | {
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"@sgugger , @jingyanwangms , @harshithapv , I've moved the PR to the original repository as suggested. A review would be great!"
] | 1,635 | 1,635 | 1,635 | CONTRIBUTOR | null | Signed-off-by: Walter Martin <wamartin@microsoft.com>
# What does this PR do?
This PR switches MLflow metric logging over to the more efficient log_metrics API, which logs in a batch.
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case)... | {
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https://api.github.com/repos/huggingface/transformers/issues/14231 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14231/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14231/comments | https://api.github.com/repos/huggingface/transformers/issues/14231/events | https://github.com/huggingface/transformers/pull/14231 | 1,041,181,032 | PR_kwDOCUB6oc4t7WDi | 14,231 | Re: Add Japanese RoBERTa Model | {
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"@LysandreJik I hope that CI runs this time.\r\nI will soon add missing documents 😄 ",
"Hey @butsugiri! For some reason the tests still didn't run, but I could push a branch and open a PR from my personal fork with your commits here: https://github.com/huggingface/transformers/pull/14233\r\n\r\nThis triggered th... | 1,635 | 1,644 | 1,644 | NONE | null | I have re-created PR as CI does not seem to trigger as expected.
The original PR is #13065
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https://api.github.com/repos/huggingface/transformers/issues/14230 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14230/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14230/comments | https://api.github.com/repos/huggingface/transformers/issues/14230/events | https://github.com/huggingface/transformers/issues/14230 | 1,041,175,830 | I_kwDOCUB6oc4-DxUW | 14,230 | CoNLL2003 ner_tags order mismatch between the dataset from HF and the pretrained model | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,635 | 1,643 | 1,643 | CONTRIBUTOR | null | @patrickvonplaten @dslim23
@dslim23 's pretrained models such as:
https://huggingface.co/dslim/bert-base-NER
have the following NER tag order baked in:
`"O", "B-MISC", "I-MISC", "B-PER", "I-PER", "B-ORG", "I-ORG", "B-LOC", "I-LOC"`
while the https://huggingface.co/datasets/conll2003 dataset has:
`O (0), B-PE... | {
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https://api.github.com/repos/huggingface/transformers/issues/14229 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14229/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14229/comments | https://api.github.com/repos/huggingface/transformers/issues/14229/events | https://github.com/huggingface/transformers/issues/14229 | 1,041,168,125 | I_kwDOCUB6oc4-Dvb9 | 14,229 | How can i add a Bi-LSTM layer on top of some model?like xlm_roberta | {
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"Hi,\r\n\r\nPlease ask training-related questions on our [forum](https://discuss.huggingface.co/) instead of here, as we'd like to keep Github issues for bugs/feature requests.\r\n\r\nThanks!"
] | 1,635 | 1,635 | 1,635 | NONE | null | I'm using pytorch and I'm using the base pretrained bert to classify sentences for hate speech. I want to implement a Bi-LSTM layer that takes as an input all outputs of the latest transformer encoder from the bert model as a new model (class that implements nn.Module), and i got confused with the nn.LSTM parameters. | {
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https://api.github.com/repos/huggingface/transformers/issues/14228 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14228/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14228/comments | https://api.github.com/repos/huggingface/transformers/issues/14228/events | https://github.com/huggingface/transformers/issues/14228 | 1,041,076,174 | I_kwDOCUB6oc4-DY_O | 14,228 | input_ids is None when evaluating | {
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"I find that evaluating will run a bart encoder in advance, I add a self.input_ids = input_ids in the encoder, and then can obtain it easily. "
] | 1,635 | 1,691 | 1,635 | NONE | null | Information
=====
When evaluating model checkpoints, I find that input_ids passed to the model is None, but encoder_outputs are available instead. I'd like to obtain the value of input_ids, what should I do? Thanks.
To reproduce
=====
run the following command:
python run_summarization.py \
--model_name_... | {
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https://api.github.com/repos/huggingface/transformers/issues/14227 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14227/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14227/comments | https://api.github.com/repos/huggingface/transformers/issues/14227/events | https://github.com/huggingface/transformers/issues/14227 | 1,041,047,751 | I_kwDOCUB6oc4-DSDH | 14,227 | Can't access Huggingface page and cant download models from laptop. Can it be IP ban? | {
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"Hello! We don't IP ban. Could it be linked to your OS's DNS cache? cc @Pierrci ",
"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... | 1,635 | 1,703 | 1,639 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version: 4.3.3
- Platform: Darwin-20.6.0-x86_64-i386-64bit
- Python version: 3.7.9
- PyTorch version (GPU?): 1.9.0 (F... | {
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https://api.github.com/repos/huggingface/transformers/issues/14226 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14226/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14226/comments | https://api.github.com/repos/huggingface/transformers/issues/14226/events | https://github.com/huggingface/transformers/pull/14226 | 1,041,031,628 | PR_kwDOCUB6oc4t62qb | 14,226 | Fixing typo in error message. | {
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"@NielsRogge friendly ping."
] | 1,635 | 1,635 | 1,635 | CONTRIBUTOR | null | # What does this PR do?
<!--
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https://api.github.com/repos/huggingface/transformers/issues/14225 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14225/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14225/comments | https://api.github.com/repos/huggingface/transformers/issues/14225/events | https://github.com/huggingface/transformers/pull/14225 | 1,041,004,180 | PR_kwDOCUB6oc4t6w5m | 14,225 | ChunkPipeline (batch_size enabled on `zero-cls` and `qa` pipelines. | {
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"@LysandreJik I split this PR in 2, were 1 holds the ASR part, and this just enables `batch_size` for QA and zero-shot.\r\n\r\nIt has benefits, but also increases complexity of the overall code. Not 100% sure about this.",
"Ok thanks, this is a big PR, will review it in the coming days.",
"@LysandreJik I added ... | 1,635 | 1,640 | 1,640 | CONTRIBUTOR | null | # What does this PR do?
It enables `batch_size` on the two pipeline where it wasn't possible previously.
The main roadblock for these is that `preprocess` would already return tensors that would contain part of the `batch_size`, meaning we couldn't use `Pipeline.batch_size` independently of the processed data. Bo... | {
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https://api.github.com/repos/huggingface/transformers/issues/14224 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14224/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14224/comments | https://api.github.com/repos/huggingface/transformers/issues/14224/events | https://github.com/huggingface/transformers/pull/14224 | 1,041,003,177 | PR_kwDOCUB6oc4t6wsA | 14,224 | Tensor location is already handled | {
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# What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/14223 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14223/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14223/comments | https://api.github.com/repos/huggingface/transformers/issues/14223/events | https://github.com/huggingface/transformers/pull/14223 | 1,040,937,074 | PR_kwDOCUB6oc4t6iiQ | 14,223 | Fixing `image-segmentation` tests. | {
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<!--
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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)... | 1,635 | 1,676 | 1,642 | NONE | null | Hi, I followed the instructions to convert BART-LARGE-CNN model to ONNX here (https://github.com/huggingface/transformers/blob/master/docs/source/serialization.rst) using transformers.onnx script. The model was exported fine and I can run inference.
However, the results of the inference, from the 'last_hideen_state'... | {
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https://api.github.com/repos/huggingface/transformers/issues/14221 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14221/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14221/comments | https://api.github.com/repos/huggingface/transformers/issues/14221/events | https://github.com/huggingface/transformers/issues/14221 | 1,040,494,774 | I_kwDOCUB6oc4-BLC2 | 14,221 | Hidden states of BertForPreTraining (load from tf ckpt of google original bert) not exactly equal to the output of extract_features.py in google original bert | {
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"Hi,\r\n\r\nWould you mind elaborating an approximate range of the bias? Also, is the hidden states output of BertForPreTraining deterministic?\r\n\r\nIf the output is deterministic but slightly different than TensorFlow's output (the differences are smaller than roughly 1e-5), this is probably a normal behavior du... | 1,635 | 1,635 | 1,635 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version:
- Platform: ubuntu 20.04
- Python version: 3.8
- PyTorch version (GPU?): 4.10.2
- Tensorflow version (GPU?)... | {
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https://api.github.com/repos/huggingface/transformers/issues/14220 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14220/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14220/comments | https://api.github.com/repos/huggingface/transformers/issues/14220/events | https://github.com/huggingface/transformers/issues/14220 | 1,040,477,921 | I_kwDOCUB6oc4-BG7h | 14,220 | Model doc examples for GPT-j-6b are slightly misleading for the GPU context | {
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"Hi,\r\n\r\nThat's actually how any PyTorch model works, this is not really specific to GPT-J. If you want to run PyTorch models on GPU, you need to send both your model and data to the GPU. This is explained in the [PyTorch intro tutorial](https://pytorch.org/tutorials/beginner/blitz/cifar10_tutorial.html).\r\n\r\... | 1,635 | 1,639 | 1,639 | NONE | null | # 🚀 Feature request
The default example can provide a bit more info for GPU / CUDA users.
First part I got stuck on yesterday was selecting a device:
```python
# Model init + CUDA device
device = torch.device("cuda")
model = GPTJForCausalLM.from_pretrained("EleutherAI/gpt-j-6B", revision="float16", low_cpu... | {
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https://api.github.com/repos/huggingface/transformers/issues/14219 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14219/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14219/comments | https://api.github.com/repos/huggingface/transformers/issues/14219/events | https://github.com/huggingface/transformers/pull/14219 | 1,040,426,573 | PR_kwDOCUB6oc4t46iO | 14,219 | Raising exceptions instead of using assertions for few models | {
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- The PR addresses issue #12789 in a few transformer scripts.
- Didn't try to tinker a lot of the scripts for the same since it's my 1st PR
<!--
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https://api.github.com/repos/huggingface/transformers/issues/14218 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14218/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14218/comments | https://api.github.com/repos/huggingface/transformers/issues/14218/events | https://github.com/huggingface/transformers/issues/14218 | 1,040,384,788 | I_kwDOCUB6oc4-AwMU | 14,218 | "Size mismatch" when using the same type of model as pretraining during finetuning while "num_labels" is diffierent | {
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"We've recently added a new `ignore_mismatched_sizes` argument to the `from_pretrained` method, which can be set to `True` to ignore such runtime errors, and to be able to replace the head of an already fine-tuned model.\r\n\r\nYou can run it as follows:\r\n\r\n```\r\nfrom transformers import RobertaForSequenceClas... | 1,635 | 1,638 | 1,638 | NONE | null | Model - Roberta
The details of this issue are as follows:
Code used:
```
pretrain model and param: RobertaForSequenceClassification with num_labels=3
pretrain model saving method: model.save_pretrained(save_path)
finetune model and param: RobertaForSequenceClassification with num_labe... | {
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https://api.github.com/repos/huggingface/transformers/issues/14217 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14217/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14217/comments | https://api.github.com/repos/huggingface/transformers/issues/14217/events | https://github.com/huggingface/transformers/issues/14217 | 1,040,384,084 | I_kwDOCUB6oc4-AwBU | 14,217 | the results of run_glue_no_trainer.py are different from those reported in the paper | {
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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)... | 1,635 | 1,638 | 1,638 | NONE | null | ## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
Don't forget to fill out the missing fields in that output! -->
- `transformers` version:
- Platform: ubuntu 18
- Python version: 3.6
- PyTorch version (GPU?): 1.6
- Tensorflow version (GPU?):
- ... | {
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https://api.github.com/repos/huggingface/transformers/issues/14216 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14216/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14216/comments | https://api.github.com/repos/huggingface/transformers/issues/14216/events | https://github.com/huggingface/transformers/pull/14216 | 1,040,368,307 | PR_kwDOCUB6oc4t4v5f | 14,216 | Fix generation docstring | {
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"Thank you!"
] | 1,635 | 1,635 | 1,635 | CONTRIBUTOR | null | # What does this PR do?
As mentioned in this [comment](https://github.com/huggingface/transformers/issues/14206#issuecomment-955607275), the `add_prefix_space` argument is not available in `GPT2TokenizerFast.__call__` but `GPT2Tokenizer.__call__`.
Therefore, this PR fixes this error by switching the fast tokeniz... | {
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https://api.github.com/repos/huggingface/transformers/issues/14215 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14215/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14215/comments | https://api.github.com/repos/huggingface/transformers/issues/14215/events | https://github.com/huggingface/transformers/issues/14215 | 1,040,330,357 | I_kwDOCUB6oc4-Ai51 | 14,215 | Shapes mismatch triggered at modeling_flax_utils | {
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"cc @patil-suraj ",
"It seems to work with `flax==0.3.5`.\r\nMy guess is that weights are now being squeezed. Maybe need to reupload a new checkpoint?\r\nActually here a shape of (512,) seems to make more sense than (1,1,1,512)",
"Do we know which commit in Flax is responsible for this bug?",
"> It seems to w... | 1,635 | 1,636 | 1,636 | NONE | null | Good day,
while using the MiniDalle repo at:
https://github.com/borisdayma/dalle-mini/issues/99
we are suddenly getting this error which was not happening before:
"Trying to load the pretrained weight for ('decoder', 'mid', 'attn_1', 'norm', 'bias') failed: checkpoint has shape (1, 1, 1, 512) which is incompatibl... | {
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https://api.github.com/repos/huggingface/transformers/issues/14214 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14214/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14214/comments | https://api.github.com/repos/huggingface/transformers/issues/14214/events | https://github.com/huggingface/transformers/issues/14214 | 1,040,294,452 | I_kwDOCUB6oc4-AaI0 | 14,214 | Can't load tokenizer for 'facebook/hubert-base-ls960' | {
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"Hey @harrypotter90,\r\n\r\nNote that `facebook/hubert-base-ls960` is just the pretrained model and therefore does not have a tokenizer yet. You can create one yourself as shown in this blog post: https://huggingface.co/blog/fine-tune-wav2vec2-english\r\n\r\n",
"Thanks for the clarification @patrickvonplaten. The... | 1,635 | 1,664 | 1,638 | 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: 4.12.2
- Platform: Mac
- Python version: 3.7
- PyTorch version (GPU?): 1.9
- Tensorflow version (GPU?): No
... | {
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"cc @michaelbenayoun ",
"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/bl... | 1,635 | 1,638 | 1,638 | NONE | null | Here:
https://github.com/huggingface/transformers/blob/9fc1951711e5377ffa1f06614ca37d4d5ad281a8/src/transformers/utils/fx.py#L307
there's a copy by reference which is problematic because you append values to `shape`.
You should make it a copy by value, e.g. by adding the following line right after:
``
shape = s... | {
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https://api.github.com/repos/huggingface/transformers/issues/14212 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14212/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14212/comments | https://api.github.com/repos/huggingface/transformers/issues/14212/events | https://github.com/huggingface/transformers/pull/14212 | 1,039,799,581 | PR_kwDOCUB6oc4t3LaF | 14,212 | Update Seq2Seq QA example script to use SQuAD metric. | {
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"In the extractive method, the logits are used to score the outputs but for generative there isn't any value we can define to rank it because the sentence is already generated. So I suppose we can just use one feature per example.",
"It looks like GitHub does not like your rebase and is showing a diff with ~200 f... | 1,635 | 1,636 | 1,636 | CONTRIBUTOR | null | # What does this PR do?
<!--
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Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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https://api.github.com/repos/huggingface/transformers/issues/14211 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14211/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14211/comments | https://api.github.com/repos/huggingface/transformers/issues/14211/events | https://github.com/huggingface/transformers/pull/14211 | 1,039,727,066 | PR_kwDOCUB6oc4t28XE | 14,211 | Add a condition for checking labels | {
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This PR adds stability by checking whether it has labels before returning it in `prediction_step` of `Seq2SeqTrainer`
There is a similar condition in [`prediction_step` of `Trainer`](https://github.com/huggingface/transformers/blob/master/src/transformers/trainer.py#L2460-L2465)
```python
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https://api.github.com/repos/huggingface/transformers/issues/14210 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14210/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14210/comments | https://api.github.com/repos/huggingface/transformers/issues/14210/events | https://github.com/huggingface/transformers/issues/14210 | 1,039,701,274 | I_kwDOCUB6oc49-JUa | 14,210 | Add `inference_mode` back to `image_segmentation` | {
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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)... | 1,635 | 1,638 | 1,638 | 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! -->
This hotfix: https://github.com/huggingface/transformers/pull/14204 could be superseeded with superior fix that would keep `inference_mode`... | {
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https://api.github.com/repos/huggingface/transformers/issues/14209 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14209/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14209/comments | https://api.github.com/repos/huggingface/transformers/issues/14209/events | https://github.com/huggingface/transformers/pull/14209 | 1,039,548,755 | PR_kwDOCUB6oc4t2XEZ | 14,209 | Fix pipeline tests env and fetch | {
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This PR fixes two things:
- changing `pipelines/base.py` should run all pipeline tests in the test fetcher
- the pipelines test do not install the `timm` extra dependency, and thus skip the image segmentation tests. | {
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https://api.github.com/repos/huggingface/transformers/issues/14208 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14208/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14208/comments | https://api.github.com/repos/huggingface/transformers/issues/14208/events | https://github.com/huggingface/transformers/issues/14208 | 1,039,541,013 | I_kwDOCUB6oc499iMV | 14,208 | [QuestionGeneration] RuntimeError: Integer division of tensors using div or / is no longer supported | {
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"oups, I guess we are all colliding here \r\nhere is the related change 3months ago that removed the // operator because of torch working.\r\nhttps://github.com/huggingface/transformers/pull/13013\r\n\r\nmy 2 cents is that implicit operator are kind of broken\r\n\r\nI feel like https://github.com/StevenTang1998 pus... | 1,635 | 1,654 | 1,638 | NONE | null | ## Environment info
- `transformers` version: 4.12.0
- Platform: Linux-5.4.0-88-generic-x86_64-with-debian-buster-sid
- Python version: 3.7.10
- PyTorch version (GPU?): 1.6.0 (True)
- Tensorflow version (GPU?): 2.6.0 (False)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxL... | {
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https://api.github.com/repos/huggingface/transformers/issues/14207 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14207/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14207/comments | https://api.github.com/repos/huggingface/transformers/issues/14207/events | https://github.com/huggingface/transformers/pull/14207 | 1,039,528,493 | PR_kwDOCUB6oc4t2S06 | 14,207 | [GPT2] Add lm_attention_mask as a optional argument | {
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"Thanks for the comments! I don't like `causal_mask` as the whole point is to pass a non causal mask, nor `language_model_mask` because all models here are language models, and doesn't says much about this variable ... \r\n\r\nSome suggestions:\r\n - attention_layer_mask \r\n - key_query_mask\r\n - others ?",
"> ... | 1,635 | 1,651 | 1,645 | CONTRIBUTOR | null | # What does this PR do?
We provide a new optional argument in order to pass down a mask that should be applied on attention layers. As the naming conflicts with `attention_mask` (which is use to determine which ones are pad values see https://huggingface.co/transformers/v3.1.0/glossary.html#attention-mask).
Conte... | {
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https://api.github.com/repos/huggingface/transformers/issues/14206 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14206/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14206/comments | https://api.github.com/repos/huggingface/transformers/issues/14206/events | https://github.com/huggingface/transformers/issues/14206 | 1,039,446,321 | I_kwDOCUB6oc499LEx | 14,206 | Does the 'bad_words_ids' argument in the "generate function" works? | {
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"Hey @alvinwatner,\r\n\r\nTo prevent bad words from occurring in the middle of generated texts, you'll need to add a prefix space to every bad word so that the tokenized bad words e.g. `save` will be `['Ġsave']` instead of `['save']`, which matches GPT2's outputs.\r\n\r\nThis can be done by setting `add_prefix_spac... | 1,635 | 1,649 | 1,640 | 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: 4.12.0
- Platform: Linux-5.4.104+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.12
- PyTorch version... | {
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https://api.github.com/repos/huggingface/transformers/issues/14205 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14205/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14205/comments | https://api.github.com/repos/huggingface/transformers/issues/14205/events | https://github.com/huggingface/transformers/issues/14205 | 1,039,356,515 | I_kwDOCUB6oc4981Jj | 14,205 | Add option to not load pretrained weights in `AutoModel.from_pretrained()` | {
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"It's just `AutoModel.from_config(AutoConfig.from_pretrained(\"model_name))` no?",
"Yes. But it requires if-else, and I don't like that. 🙃",
"I personally think the API with `from_pretrained` and `from_config` is nice and quite flexible. Adding a second way of doing the same thing looks like it would complicat... | 1,635 | 1,635 | 1,635 | CONTRIBUTOR | null | # 🚀 Feature request
Add option to not load pretrained weights in `AutoModel.from_pretrained()`
analogous to `pretrained=` in `timm.create_model(model_name, pretrained=True/False)`
## Motivation
code like this can be simplified
https://github.com/huggingface/transformers/blob/4469010c1be3a94f74d64484970514... | {
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https://api.github.com/repos/huggingface/transformers/issues/14204 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14204/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14204/comments | https://api.github.com/repos/huggingface/transformers/issues/14204/events | https://github.com/huggingface/transformers/pull/14204 | 1,039,320,093 | PR_kwDOCUB6oc4t1n6L | 14,204 | Fixing image segmentation with inference mode. | {
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"Fine with this solution, but a better one might actually to disable all those:\r\n\r\n```python\r\n if torch.isinf(hidden_states.clone()).any() or torch.isnan(hidden_states.clone()).any():\r\n clamp_value = torch.finfo(hidden_states.dtype).max - 1000\r\n hidden_states = torch.clamp(hid... | 1,635 | 1,635 | 1,635 | CONTRIBUTOR | null | # What does this PR do?
<!--
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https://api.github.com/repos/huggingface/transformers/issues/14203 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14203/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14203/comments | https://api.github.com/repos/huggingface/transformers/issues/14203/events | https://github.com/huggingface/transformers/pull/14203 | 1,039,229,130 | PR_kwDOCUB6oc4t1Vc0 | 14,203 | Intel OpenVINO backend (inference only) | {
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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)... | 1,635 | 1,638 | 1,638 | NONE | null | # What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/14202 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14202/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14202/comments | https://api.github.com/repos/huggingface/transformers/issues/14202/events | https://github.com/huggingface/transformers/pull/14202 | 1,039,205,456 | PR_kwDOCUB6oc4t1Qm9 | 14,202 | Fix the write problem in trainer.py comment | {
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https://api.github.com/repos/huggingface/transformers/issues/14201 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14201/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14201/comments | https://api.github.com/repos/huggingface/transformers/issues/14201/events | https://github.com/huggingface/transformers/issues/14201 | 1,039,086,129 | I_kwDOCUB6oc497zIx | 14,201 | Couldn't reproduce DistilBERT downstream tasks performance on SQuAD dataset. | {
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"The `run_qa.py` script is very general, to be used by any `xxxForQuestionAnswering` model. To reproduce the results of a specific paper, you may need to tweak the hyperparameters, such as number of epochs, learning rate, batch size.",
"I see, thanks! @NielsRogge \r\n\r\nMay I get the recommended hyperparameters ... | 1,635 | 1,638 | 1,638 | NONE | null | Hi,
I tried the DIstilBERT finetuning (script path: transformers/examples/tensorflow/question-answering) for QuestionAnswering downstream task without changing any code, and this is my command:
`
python3 run_qa.py --model_name_or_path distilbert-base-uncased --output_dir output --dataset_name squad --do_train -... | {
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https://api.github.com/repos/huggingface/transformers/issues/14200 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14200/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14200/comments | https://api.github.com/repos/huggingface/transformers/issues/14200/events | https://github.com/huggingface/transformers/issues/14200 | 1,038,855,429 | I_kwDOCUB6oc49660F | 14,200 | Trainer batch size auto scaling | {
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"I am very nervous about adding that kind of feature of auto scaling to the Trainer. Note that the `_is_oom` test for instance will catch way more CUDA errors than the OOM: haivng the wrong number of labels in your model will trigger an error with `CUBLAS_STATUS_ALLOC_FAILED` on most environments.\r\n\r\nIn a note... | 1,635 | 1,638 | 1,638 | CONTRIBUTOR | null | # 🚀 Feature request
Since `Trainer` handles both batch_size and gradient_accumulation_steps it seems like it could detect some out-of-memory situations and handle those scenarios automatically.
## Motivation
I've been experimenting with model search (model_type, vocab_size, num_hidden_layers, hidden_size) and... | {
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https://api.github.com/repos/huggingface/transformers/issues/14199 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14199/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14199/comments | https://api.github.com/repos/huggingface/transformers/issues/14199/events | https://github.com/huggingface/transformers/issues/14199 | 1,038,855,253 | I_kwDOCUB6oc4966xV | 14,199 | run_t5_mlm_flax.py | {
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"I haven't tested it, but it should run as it is on single-host multi-gpu.\r\nYou just need to install jax version compatible with your cuda installation, for which you can find the instructions [here](https://github.com/google/jax#pip-installation-gpu-cuda)",
"Using 't5-small' tokenizer is wrong we should use ju... | 1,635 | 1,658 | 1,641 | NONE | null | Hi! @patil-suraj which arg to use for run_t5_mlm_flax.py to run on multiple gpus? | {
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https://api.github.com/repos/huggingface/transformers/issues/14198 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14198/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14198/comments | https://api.github.com/repos/huggingface/transformers/issues/14198/events | https://github.com/huggingface/transformers/pull/14198 | 1,038,825,176 | PR_kwDOCUB6oc4t0B6x | 14,198 | use functional interface for softmax in attention | {
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"Probably it's an attention thing. :) ",
"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/huggingfac... | 1,635 | 1,638 | 1,638 | CONTRIBUTOR | null | There are several instances of (ab)using the PyTorch modular interface to compute softmax where it would be more natural to use the functional interface. This patch changes the occurrences I found.
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https://api.github.com/repos/huggingface/transformers/issues/14197 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14197/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14197/comments | https://api.github.com/repos/huggingface/transformers/issues/14197/events | https://github.com/huggingface/transformers/pull/14197 | 1,038,665,213 | PR_kwDOCUB6oc4tzf52 | 14,197 | Fix EncoderDecoderModel docs | {
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Updates the docs of the EncoderDecoderModel classes, as a follow-up of #14139. | {
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https://api.github.com/repos/huggingface/transformers/issues/14196 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14196/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14196/comments | https://api.github.com/repos/huggingface/transformers/issues/14196/events | https://github.com/huggingface/transformers/issues/14196 | 1,038,657,673 | I_kwDOCUB6oc496KiJ | 14,196 | [T5v1_1] Add lm model pretrained models as well | {
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"FYI @TevenLeScao @craffel @VictorSanh ",
"https://huggingface.co/models?other=t5-lm-adapt"
] | 1,635 | 1,635 | 1,635 | MEMBER | null | Reminder to @patrickvonplaten to add all [LM-Adapted: t5.1.1.lm100k checkpoitns](https://github.com/google-research/text-to-text-transfer-transformer/blob/main/released_checkpoints.md#lm-adapted-t511lm100k) to the hub. | {
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https://api.github.com/repos/huggingface/transformers/issues/14195 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14195/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14195/comments | https://api.github.com/repos/huggingface/transformers/issues/14195/events | https://github.com/huggingface/transformers/issues/14195 | 1,038,621,038 | I_kwDOCUB6oc496Blu | 14,195 | Help training TrOCR | {
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"You're in luck, I just uploaded a notebook showcasing how to fine-tune TrOCR on a custom dataset.\r\n\r\nYou can find it here: https://github.com/NielsRogge/Transformers-Tutorials/blob/master/TrOCR/Fine_tune_TrOCR_on_IAM_Handwriting_Database_using_Seq2SeqTrainer.ipynb\r\n\r\nRegarding documentation, this can be fo... | 1,635 | 1,707 | 1,638 | NONE | null | Hello,
Thank you for your hard work on the repo.
I want to train the newly added TrOCR for my use case on my dataset.
I am a little confused on how to proceed.
https://huggingface.co/transformers/training.html
The finetuning tutorial seems to be geared towards strictly NLP models.
Am I missing something? ... | {
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https://api.github.com/repos/huggingface/transformers/issues/14194 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14194/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14194/comments | https://api.github.com/repos/huggingface/transformers/issues/14194/events | https://github.com/huggingface/transformers/issues/14194 | 1,038,612,043 | I_kwDOCUB6oc495_ZL | 14,194 | AttributeError: 'str' object has no attribute 'squeeze' | {
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"That code can't work since Transformers v4\r\n```\r\n# Call the model and get the logits\r\nlogits, = model(tensor)\r\n```\r\nyou need to do\r\n```\r\n# Call the model and get the logits\r\nlogits = model(tensor).logits\r\n```\r\n",
"This issue has been automatically marked as stale because it has not had recent... | 1,635 | 1,638 | 1,638 | NONE | null | Hello guys, I am new to Hugging Face. I was running it on my Ubuntu 18, in Jupyter notebook.
I was running the example case (tutorial) for the https://huggingface.co/neuraly/bert-base-italian-cased-sentiment model. But I get this error:
```
---------------------------------------------------------------------------
... | {
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https://api.github.com/repos/huggingface/transformers/issues/14193 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14193/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14193/comments | https://api.github.com/repos/huggingface/transformers/issues/14193/events | https://github.com/huggingface/transformers/pull/14193 | 1,038,579,507 | PR_kwDOCUB6oc4tzOLv | 14,193 | Adding support for `truncation` parameter on `feature-extraction` pipeline. | {
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"Can you also include `padding` as well? Since we're extracting features, I'd like to be able to specify both padding and truncation strategies. Thanks! @Narsil ",
"Padding for pipelines is something, I would like to keep orthogonal to business logic (See https://github.com/huggingface/transformers/pull/13724).\r... | 1,635 | 1,635 | 1,635 | CONTRIBUTOR | null | Fixes #14183
# What does this PR do?
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https://api.github.com/repos/huggingface/transformers/issues/14192 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14192/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14192/comments | https://api.github.com/repos/huggingface/transformers/issues/14192/events | https://github.com/huggingface/transformers/pull/14192 | 1,038,470,201 | PR_kwDOCUB6oc4ty3SL | 14,192 | Add audio-classification benchmarking results | {
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"Nice!"
] | 1,635 | 1,635 | 1,635 | MEMBER | null | # What does this PR do?
Adds results for DistilHuBERT and SEW to the audio classification example results | {
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https://api.github.com/repos/huggingface/transformers/issues/14191 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14191/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14191/comments | https://api.github.com/repos/huggingface/transformers/issues/14191/events | https://github.com/huggingface/transformers/pull/14191 | 1,038,466,401 | PR_kwDOCUB6oc4ty2e0 | 14,191 | Fix SEW-D implementation differences | {
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"@LysandreJik - would be nice if we could merge this before the release. Without this PR we are getting significant differences in the output logits between orginial SEW-D and our SEW-D version (up to 5e0)."
] | 1,635 | 1,635 | 1,635 | MEMBER | null | # What does this PR do?
This sets the default activation function for SEW-D to `gelu_python` and the `layer_norm_eps` of the DeBERTa layer to `1e-7` to reproduce the model more closely.
cc @LysandreJik | {
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https://api.github.com/repos/huggingface/transformers/issues/14190 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14190/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14190/comments | https://api.github.com/repos/huggingface/transformers/issues/14190/events | https://github.com/huggingface/transformers/pull/14190 | 1,038,447,949 | PR_kwDOCUB6oc4tyyoa | 14,190 | [GPTJ] enable common tests and few fixes | {
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"@patil-suraj For the specific issue of `resize_token_embeddings` on gptj (#14107), I got it to work by changing two methods in modeling_gptj.py below. I'm not sure this is right because the model needs to train 2 epochs to get a good result whereas I almost always need just 1 epoch with other model types (gpt-2, g... | 1,635 | 1,635 | 1,635 | MEMBER | null | # What does this PR do?
Currently, GPTJ does not run common tests because its testes class does not subclass `ModelTesterMixin, GenerationTesterMixin`. This PR enables common tests for GPTJ and fixes a few things along the way.
I've run the slow tests manually and verified that they pass.
Thanks a lot, @sgugger... | {
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https://api.github.com/repos/huggingface/transformers/issues/14189 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14189/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14189/comments | https://api.github.com/repos/huggingface/transformers/issues/14189/events | https://github.com/huggingface/transformers/issues/14189 | 1,038,349,366 | I_kwDOCUB6oc494_Q2 | 14,189 | T5-v1.1 loss go to nan when fp16 training was enabled | {
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"Linked PR https://github.com/huggingface/transformers/pull/10956",
"To be honest, I think we should just not do T5 training in fp16...cc @stas00 \r\n\r\nRelated issues https://github.com/huggingface/transformers/issues/10830",
" As suggested by Lysandre, @Liangtaiwan please check if this PR helps: https://git... | 1,635 | 1,645 | 1,635 | CONTRIBUTOR | null | ## Environment info
I test in two different environments. One is my native env, one is nvidia container pytorch_21.09.
For more details, please refer https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes/rel_21-09.html#rel_21-09
- `transformers` version: 4.11.3
- Platform: Arch Linux 5.14.14-arch1... | {
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https://api.github.com/repos/huggingface/transformers/issues/14188 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14188/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14188/comments | https://api.github.com/repos/huggingface/transformers/issues/14188/events | https://github.com/huggingface/transformers/issues/14188 | 1,038,321,045 | I_kwDOCUB6oc4944WV | 14,188 | [Flax] Add Flax implementation of `BlenderbotSmallModel` | {
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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)... | 1,635 | 1,638 | 1,638 | CONTRIBUTOR | null | # 🚀 Feature request
Add Flax implementation of `BlenderbotSmall` models.
## Motivation
Improve the level of Flax/Jax support.
## Your contribution
I'll be happy to do it once the problems in #13633 will be resolved and the PR will be merged.
@patrickvonplaten | {
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https://api.github.com/repos/huggingface/transformers/issues/14187 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14187/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14187/comments | https://api.github.com/repos/huggingface/transformers/issues/14187/events | https://github.com/huggingface/transformers/issues/14187 | 1,038,295,883 | I_kwDOCUB6oc494yNL | 14,187 | ValueError when converting dialogpt to onnx format | {
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"Gently pinging @michaelbenayoun here",
"Gently pinging @lewtun here",
"Thanks for the ping! Will take a look :)",
"Hey @qiuxia-alone, thank you for raising this issue! The ONNX export API was overhauled in `transformers` v4.9.0 ([link](https://github.com/huggingface/transformers/releases/tag/v4.9.0)), and si... | 1,635 | 1,641 | 1,641 | NONE | null | ## Environment info
- `transformers` version: 4.9.2
- Platform: Darwin-20.5.0-x86_64-i386-64bit
- Python version: 3.7.11
- PyTorch version (GPU?): 1.9.0 (False)
- Tensorflow version (GPU?): 2.2.0 (False)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not ins... | {
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https://api.github.com/repos/huggingface/transformers/issues/14186 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14186/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14186/comments | https://api.github.com/repos/huggingface/transformers/issues/14186/events | https://github.com/huggingface/transformers/pull/14186 | 1,038,111,776 | PR_kwDOCUB6oc4txsLf | 14,186 | Replace assertions with RuntimeError exceptions | {
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Contributes towards fixing issue #12789
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://github.com/huggingfa... | {
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"Sure, that's possible.\r\n\r\nYou can tokenize your entire dataset using the tokenizer, then save it to disk using the `save_to_disk` method as explained in the [docs](https://huggingface.co/docs/datasets/package_reference/main_classes.html?highlight=save_to_disk#datasets.Dataset.save_to_disk).\r\n\r\nSmall examp... | 1,635 | 1,638 | 1,638 | NONE | null | It takes a lot of time to tokenize my dataset, is there a way to save it and load it?
Let's say I'm using the IMDB toy dataset, How to save the `inputs` object?
```
from datasets import load_dataset
raw_datasets = load_dataset("imdb")
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrai... | {
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https://api.github.com/repos/huggingface/transformers/issues/14184 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14184/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14184/comments | https://api.github.com/repos/huggingface/transformers/issues/14184/events | https://github.com/huggingface/transformers/issues/14184 | 1,037,966,413 | I_kwDOCUB6oc493hxN | 14,184 | Argument 'filter_value' for the _get_logits_warper function | {
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"This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.\n\nPlease note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md)... | 1,635 | 1,640 | 1,640 | NONE | null | # 🚀 Feature request
In generation_utils, when sampling (i.e. `is_sample_gen_mode = True`), add the argument `"filter_value"` to `_get_logits_warper` function call.
[https://github.com/huggingface/transformers/blob/3187228206cce052c5df0a8643fe85d2fd50e6a0/src/transformers/generation_utils.py#L1004](https://github... | {
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https://api.github.com/repos/huggingface/transformers/issues/14183 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14183/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14183/comments | https://api.github.com/repos/huggingface/transformers/issues/14183/events | https://github.com/huggingface/transformers/issues/14183 | 1,037,918,773 | I_kwDOCUB6oc493WI1 | 14,183 | Pipeline feature extraction: tensor size mismatch | {
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"I'm pretty sure that's the problem. I managed to reproduce with something like this:\r\n```\r\n# debug\r\n predict_text = \"this \" * 1000\r\n print(predict_text)\r\n outputs = feature_extractor(predict_text, padding=\"longest\", truncation=TruncationStrategy.ONLY_FIRST)\r\n```\r\n\r\nI get `RuntimeError:... | 1,635 | 1,636 | 1,635 | NONE | null | ## Environment info
I'm using pipelines for the first time with feature extraction, it seems to work fine for my toy samples that I used to debug the code. However, when I started running with some real data, I got the following stack trace:
```
File "../../models//text_embeddings_feature_extraction.py", line 21... | {
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https://api.github.com/repos/huggingface/transformers/issues/14182 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14182/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14182/comments | https://api.github.com/repos/huggingface/transformers/issues/14182/events | https://github.com/huggingface/transformers/pull/14182 | 1,037,857,556 | PR_kwDOCUB6oc4tw36N | 14,182 | Add BigBird/BigBird Pegasus to models exportable with ONNX | {
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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)... | 1,635 | 1,638 | 1,638 | NONE | null | This PR adds BigBird and BigBird Pegasus to models exportable with ONNX and also adds them in test_onnx_v2.py
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https://api.github.com/repos/huggingface/transformers/issues/14181 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14181/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14181/comments | https://api.github.com/repos/huggingface/transformers/issues/14181/events | https://github.com/huggingface/transformers/pull/14181 | 1,037,829,536 | PR_kwDOCUB6oc4twyLD | 14,181 | [modeling_utils] respect original dtype in _get_resized_lm_head | {
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The fix is identical to:
https://github.com/huggingface/transformers/blob/232822f36d49598e68e152a9ca0a6d90be6f54b5/src/transformers/modeling_utils.py#L792-L794
The probl... | {
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https://api.github.com/repos/huggingface/transformers/issues/14180 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14180/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14180/comments | https://api.github.com/repos/huggingface/transformers/issues/14180/events | https://github.com/huggingface/transformers/pull/14180 | 1,037,573,818 | PR_kwDOCUB6oc4tv9e0 | 14,180 | Generalize problem_type to all sequence classification models | {
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"Relevant to #13370 "
] | 1,635 | 1,635 | 1,635 | COLLABORATOR | null | # What does this PR do?
This PR makes each sequence classification model use the `problem_type` attribute of the config and infer a default coming from the labels when it's not set.
Deberta implemented its own loss, apparently dealing with one-hot encoded labels, which we keep when `problem_type` is None for back... | {
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https://api.github.com/repos/huggingface/transformers/issues/14179 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14179/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14179/comments | https://api.github.com/repos/huggingface/transformers/issues/14179/events | https://github.com/huggingface/transformers/issues/14179 | 1,037,569,285 | I_kwDOCUB6oc492A0F | 14,179 | one of the variables needed for gradient computation has been modified by an inplace operation | {
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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)... | 1,635 | 1,638 | 1,638 | NONE | null | It occured when i forward a bert model twice and backward loss.
```
RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation: [torch.cuda.LongTensor [1, 20]] is at version 4; expected version 3 instead. Hint: the backtrace further above shows the operation that fail... | {
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https://api.github.com/repos/huggingface/transformers/issues/14178 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14178/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14178/comments | https://api.github.com/repos/huggingface/transformers/issues/14178/events | https://github.com/huggingface/transformers/pull/14178 | 1,037,462,000 | PR_kwDOCUB6oc4tvlwr | 14,178 | [Pipelines] Fix ASR model types check | {
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"Was there any real failure or just a warning ?\r\nIf warning it's fine, if failure we need a tests (model type checking should not be a hard error anyway)",
"@Narsil just a warning in the logs, the model was loading fine"
] | 1,635 | 1,635 | 1,635 | MEMBER | null | # What does this PR do?
This changes `list` to `dict` in the ASR pipeline's `check_model_type()`.
Previously, a list was passed to the checker, so the model name extraction was never preformed [here](https://github.com/huggingface/transformers/blob/8ddbfe975264a94f124684a138a2a5ca89a2bd0d/src/transformers/pipeline... | {
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https://api.github.com/repos/huggingface/transformers/issues/14177 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14177/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14177/comments | https://api.github.com/repos/huggingface/transformers/issues/14177/events | https://github.com/huggingface/transformers/pull/14177 | 1,037,423,653 | PR_kwDOCUB6oc4tvd2P | 14,177 | Add more missing models to models/__init__.py | {
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"Could you fix the issues it generates? You should see them locally with `make quality`",
"> Could you fix the issues it generates? You should see them locally with `make quality`\r\n\r\nSure, will do later. ",
"The issues are fixed - I leave Hugging Face to double check with the original model authors if the r... | 1,635 | 1,635 | 1,635 | COLLABORATOR | null | # What does this PR do?
After #14151, I just checked if there are other missing models - and added them in this PR.
There will be some issues showing up that are previously undetected.
## Who can review?
@sgugger @LysandreJik | {
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"cc @kssteven418 ",
"{ \r\n \"_name_or_path\": \"kssteven/ibert-roberta-base\", \r\n \"architectures\": [ \r\n \"IBertForSequenceClassification\" \r\n ], \r\n \"attention_probs_dropout_prob\": 0.1, ... | 1,635 | 1,645 | 1,638 | NONE | null | ### Pretrained the IBert
I want to test IBERT's, and I have done exactly what is said in https://huggingface.co/kssteven/ibert-roberta-base. For the quantization part, when I set quant_mode to true and run the evaluation again, I get a much low accuracy model. What am I doing wrong? | {
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https://api.github.com/repos/huggingface/transformers/issues/14175 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14175/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14175/comments | https://api.github.com/repos/huggingface/transformers/issues/14175/events | https://github.com/huggingface/transformers/pull/14175 | 1,037,361,278 | PR_kwDOCUB6oc4tvRCD | 14,175 | [Gradient checkpointing] Enable for Deberta + DebertaV2 + SEW-D | {
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<!--
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https://api.github.com/repos/huggingface/transformers/issues/14174 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14174/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14174/comments | https://api.github.com/repos/huggingface/transformers/issues/14174/events | https://github.com/huggingface/transformers/pull/14174 | 1,037,344,825 | PR_kwDOCUB6oc4tvNp4 | 14,174 | Add DistilHuBERT | {
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"Feel free to merge after fixing the last tests"
] | 1,635 | 1,635 | 1,635 | MEMBER | null | # What does this PR do?
This adds the DistilHuBERT conversion script and integration tests.
Paper: [DistilHuBERT: Speech Representation Learning by Layer-wise Distillation of Hidden-unit BERT](https://arxiv.org/abs/2110.01900)
The original `s3prl` implementation and weights: https://github.com/s3prl/s3prl/tree... | {
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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!",
"This issue has been automatically marked as stale because it has not had recent activity. If you think this stil... | 1,635 | 1,638 | 1,638 | NONE | null | In [language_modeling](https://github.com/huggingface/transformers/tree/master/examples/flax/language-modeling) examples, there is an script to train a T5 model for a language. I would like to know how can I use or change this script to train a bilingual language for X and Y languages? Is it possible to do if via this ... | {
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https://api.github.com/repos/huggingface/transformers/issues/14172 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14172/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14172/comments | https://api.github.com/repos/huggingface/transformers/issues/14172/events | https://github.com/huggingface/transformers/pull/14172 | 1,037,229,454 | PR_kwDOCUB6oc4tu2BU | 14,172 | Clarify QA examples | {
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It clarifies a bit the difference between the various example scripts for question-answering. It also removes some of the things related to the legacy scripts (which were still included in the README) to the legacy folder.
Related to #14170 | {
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"Issue is related to the missing projection layer, resolved by https://github.com/huggingface/transformers/pull/14158"
] | 1,635 | 1,635 | 1,635 | MEMBER | null | To reproduce:
```python
#!/usr/bin/env python3
from transformers import AutoModelForCTC
import torch
model = AutoModelForCTC.from_pretrained("asapp/sew-small-100k", mask_time_prob=0.2).train()
model(torch.tensor([10000 * [1.0]]))
``` | {
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https://api.github.com/repos/huggingface/transformers/issues/14170 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14170/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14170/comments | https://api.github.com/repos/huggingface/transformers/issues/14170/events | https://github.com/huggingface/transformers/issues/14170 | 1,037,084,604 | I_kwDOCUB6oc490Ke8 | 14,170 | The pytorch example question-answering/run_qa_beam_search.py do not work | {
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"> @arfon @pvl @vanpelt @karthikrangasai\r\n\r\nUnsure why I received a ping here. Any clues people of Hugging Face?",
"> Unsure why I received a ping here. Any clues people of Hugging Face?\r\nGithub suggest you to me, If you cansusggest someone else, I can change. \r\n",
"@sgugger and @NielsRogge should be a... | 1,635 | 1,635 | 1,635 | NONE | null | ## Environment info
- `transformers` version: git+https://github.com/huggingface/transformers
- Platform:
- Python version: 3.8
- PyTorch version (GPU?): 1.10.0
- Using GPU in script?: yes
### Who can help
@pvl @vanpelt @NielsRogge @sgugger
Models:
- T5: gsarti/it5-base
- encoder-decoder models... | {
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https://api.github.com/repos/huggingface/transformers/issues/14169 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14169/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14169/comments | https://api.github.com/repos/huggingface/transformers/issues/14169/events | https://github.com/huggingface/transformers/pull/14169 | 1,036,904,027 | PR_kwDOCUB6oc4ttzX- | 14,169 | Torch 1.10 | {
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"As a side note. I'm excited that label smoothing is now integrated into cross entropy! https://pytorch.org/docs/stable/generated/torch.nn.CrossEntropyLoss.html\r\n\r\nExcited to replace my current implementation with this.",
"@anton-l @patrickvonplaten @Narsil there's the following error when passing to torch 1.... | 1,635 | 1,635 | 1,635 | MEMBER | null | Authorize torch 1.10 | {
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"I don't think this is the right way to fix it: the docstring you have written is great, but it should be added in the base sequence classification docstring, as all models with a sequence classification head should accept `problem_type`. I will fix the models that do not deal with it and then you can amend your PR... | 1,635 | 1,638 | 1,638 | CONTRIBUTOR | null | # What does this PR do?
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"Sounds good!"
] | 1,635 | 1,635 | 1,635 | MEMBER | null | Torch 1.10 introduced a change in the way gelu is computed, resulting in a 1e-9 to 1e-10 difference in results.
This checks that the results are close enough. | {
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This PR fixes two minor typographical issues
1 - a typo in an example speech recognition script that misstates which columns is missing from the input data
2 - a typo in the modelcard.py function that explains when some field is missing from a dataset
## Before submitting
- [X] This PR ... | {
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"yo, you probably meant to tag @patrickvonplaten :) ",
"Oops! Thanks!",
"Thank you, Thomas!\r\n\r\nI haven't had a chance to confirm that it's truly identical. Perhaps someone could do it since I won't be able to do that now.\r\n\r\nBut a question how are we going to deal with backward compatibly if we are remo... | 1,635 | 1,635 | 1,635 | CONTRIBUTOR | null | # What does this PR do?
Remove `n_ctx` from configs as it's just a duplicate for `n_positions`.
GPTJ was left unchanged because it has a linear layer that depends on `n_ctx`. I'm unclear why, is it a bug and the author meant `n_embed`?
- GPTJ: https://github.com/huggingface/transformers/blob/master/src/transfor... | {
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"Hello @banyous! The pipeline can be configured to use any model on the hub that works with this task. If the current model isn't working well for you, I invite you to take a look at the different models on the model hub and select one that fits your use-case: https://huggingface.co/models",
"Thanks @LysandreJik ... | 1,635 | 1,640 | 1,640 | NONE | null | Hi, I am using Hugging-face pipeline for the sentiment analysis task, which gives me Positive/Negative sentiment along with a confidence score. In my case, I need three outputs (Positive/Neutral/Negative). The problem is that hugging-face is giving me high confidence score even with neutral sentences (such as : 'He hav... | {
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https://api.github.com/repos/huggingface/transformers/issues/14163 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14163/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14163/comments | https://api.github.com/repos/huggingface/transformers/issues/14163/events | https://github.com/huggingface/transformers/pull/14163 | 1,036,452,483 | PR_kwDOCUB6oc4tsVuV | 14,163 | LayoutLMv2 functionality. | {
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"Hi,\r\n\r\nThis is actually not the implementation, I see you just added text to a README file. If you want to add `LayoutLMv2ForMaskedLM`, you should implement it in `modeling_layoutlmv2.py` which can be found [here](https://github.com/huggingface/transformers/blob/master/src/transformers/models/layoutlmv2/modeli... | 1,635 | 1,638 | 1,638 | NONE | null | Support for new LayoutLMv2 as discussed in this issue: https://github.com/huggingface/transformers/issues/14160.
Namely, the addition of `LayoutLMv2ForMaskedLM`, which adds a language modeling head on top of the base model to replicate the first pre-training objective in the original paper. | {
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https://api.github.com/repos/huggingface/transformers/issues/14162 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14162/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14162/comments | https://api.github.com/repos/huggingface/transformers/issues/14162/events | https://github.com/huggingface/transformers/issues/14162 | 1,036,449,979 | I_kwDOCUB6oc49xvi7 | 14,162 | Decoding Large Audio Files Using Wav2Vec2ForCTC Model | {
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"Hi @farisalasmary!\r\n\r\nUnfortunately, there's no good way to use Wav2Vec-type models on large audio clips. Since it uses a bidirectional transformer as a context encoder, you can't feed hidden states between sequences, like in the autoregressive models.\r\nBut if you split the input into chunks with some additi... | 1,635 | 1,663 | 1,637 | NONE | null | ERROR: type should be string, got "\r\nhttps://discuss.huggingface.co/t/decding-large-audio-files-using-wav2vec2forctc-model/11097\r\n\r\nI’ve been working on Wav2Vec2ForCTC model for a while. I used to have small audio files, i.e., audio files with relatively short durations (~ 1 min). When I tested the model on a large file (~ 14 mins), the model could not handle it in GPU, so, I shifted to use CPU. I notices that it used more than 200 GB of RAM to decode! I’ve tried to split the audio file into smaller audio files and use hidden states to link them together while decoding each segment but I could not find a way to feed the hidden states of the current audio file to the next audio file for the model to use it while decoding!\r\n\r\nAny ideas or suggestions?\r\n@patrickvonplaten, @anton-l\r\n" | {
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https://api.github.com/repos/huggingface/transformers/issues/14161 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14161/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14161/comments | https://api.github.com/repos/huggingface/transformers/issues/14161/events | https://github.com/huggingface/transformers/pull/14161 | 1,036,305,621 | PR_kwDOCUB6oc4tr2cv | 14,161 | [Speech Recognition] - Distributed training: Make sure vocab file removal and creation don't interfer | {
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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/14160 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14160/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14160/comments | https://api.github.com/repos/huggingface/transformers/issues/14160/events | https://github.com/huggingface/transformers/issues/14160 | 1,036,253,198 | I_kwDOCUB6oc49w_gO | 14,160 | Support for new LayoutLMv2 in Auto Classes (specifically AutoModelForMaskedLM) | {
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"As the authors did not release any pretraining code, we did not implement a `LayoutLMv2ForMaskedLM`, as LayoutLMv2 was actually pre-trained on 3 tasks:\r\n\r\n* Masked Visual-Language Modeling\r\n* Text-Image Alignment\r\n* Text-Image Matching\r\n\r\nOf course, we could add a `LayoutLMv2ForMaskedLM`, which adds a ... | 1,635 | 1,638 | 1,638 | NONE | null | # 🚀 Feature request
I am trying to finetune a LayoutLMv2 language model on my dataset using the Auto Class functionality, namely AutoModelForMaskedLM. However, it does not support this model. (https://huggingface.co/transformers/model_doc/auto.html#automodelformaskedlm)
## Motivation
It is hard to develop a ... | {
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https://api.github.com/repos/huggingface/transformers/issues/14159 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14159/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14159/comments | https://api.github.com/repos/huggingface/transformers/issues/14159/events | https://github.com/huggingface/transformers/issues/14159 | 1,036,241,283 | I_kwDOCUB6oc49w8mD | 14,159 | run_speech_recognition_ctc.py throwing error when using own dataset | {
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"Hey @peterhanlon,\r\n\r\nThanks for the issue. In your case it seems like you have the dataset already more or less processed, so that the script won't work out of the box. \r\n\r\nYou will have to adapt the beginning of the script so that it removes all data preprocessing code and simply loads your processed data... | 1,635 | 1,638 | 1,638 | NONE | null | ## Environment info
- `transformers` version: 4.12.0.dev0
- Platform: Linux-5.4.0-1055-aws-x86_64-with-glibc2.10
- Python version: 3.8.12
- PyTorch version (GPU?): 1.10.0+cu102 (True)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
... | {
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https://api.github.com/repos/huggingface/transformers/issues/14158 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14158/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14158/comments | https://api.github.com/repos/huggingface/transformers/issues/14158/events | https://github.com/huggingface/transformers/pull/14158 | 1,036,206,500 | PR_kwDOCUB6oc4trhbc | 14,158 | Add SEW CTC models | {
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This adds the conversion steps and bugfixes to support finetuned SEW and SEW-D checkpoints (https://github.com/asappresearch/sew#asr-model-fine-tuned-on-librispeech-train-clean-100h)
## TODO
- [ ] Add model cards with code examples and WER results
- [x] Update unsupervised models' weight... | {
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"The above script runs in like 5 minutes on a single GPU for reproducibility. ",
"Sorry, I left out an important part: I'm using `huggingface_hub` version `'0.0.19'`.",
"Seems like it's something that should be fixed on the `huggingface_hub` side at a first glance. cc @LysandreJik ",
"Running `git lfs prune` ... | 1,635 | 1,636 | 1,636 | MEMBER | 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: 4.12.0.dev0
- Platform: Linux-5.3.0-64-generic-x86_64-with-glibc2.10
- Python version: 3.8.10
- PyTorch vers... | {
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"cc @sgugger ",
"I think this is because you are not using the logger from the transformers library but a new logger. If you replace `__name__` by `\"transformers\"` it should work.",
"> I think this is because you are not using the logger from the transformers library but a new logger. If you replace `__name__... | 1,635 | 1,635 | 1,635 | NONE | null | I define my own callback class and want to log some info every `print_step`. However, the `logger.info` statement doesn't work when training. If modifying `logger.info` to `print`, it prints the content correctly. But if I set `gradient_accumulation_steps` greater than `1`, it will print `gradient_accumulation_steps` ... | {
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https://api.github.com/repos/huggingface/transformers/issues/14155 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/14155/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/14155/comments | https://api.github.com/repos/huggingface/transformers/issues/14155/events | https://github.com/huggingface/transformers/pull/14155 | 1,036,102,266 | PR_kwDOCUB6oc4trLNm | 14,155 | Include Keras tensor in the allowed types | {
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"@sergiovalmac looks like all the CI tests are passing except the code quality, let me run that one for you!",
"@sergiovalmac tests passing now, merge whenever you're happy with the PR!",
"Brilliant! Thank you very much! Please could you merge it? It says that only those with write access can merge PRs.",
"Ah... | 1,635 | 1,635 | 1,635 | CONTRIBUTOR | null | Includes Keras tensor in the allowed types. This allows propagating symbolic `keras.Input` tensors through the models' `call` method. This way we can convert any HF (subclass) model into a functional model.
@Rocketknight1
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"follo... | [] | 1,635 | 1,635 | 1,635 | MEMBER | null | # What does this PR do?
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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)... | 1,635 | 1,638 | 1,638 | NONE | null | hi ALL,
I notice that there is a script for train distilbert on PyTorch([Link](https://github.com/huggingface/transformers/blob/master/examples/research_projects/distillation/train.py)), is there same code for TF2.x for reference?
Thanks a lot. | {
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