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see subject
### Who can help?
see subject
### Information
- [ ] The official example scripts
- [ ] My own modified scripts
### Tasks
- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)
### Reproduction
see subje... | {
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Fix type annotation error in DepthPro model image processor
Fixes #40235
@amyeroberts, @qubvel @stevhliu
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Request for the ability to train MXFP4 Quantized models.
### Motivation
Hello! I am currently trying to create a script that fine tunes GPT OSS 20B and wished to fine tune it on some of my own data.
<img width="851" height="29" alt="Image" src="https://github.com/user-attachments/assets/e0c9245... | {
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irrelevant
### Who can help?
_No response_
### Information
- [ ] The official example scripts
- [ ] My own modified scripts
### Tasks
- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)
### Reproduction
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"merged_at... | Fixes #40229
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
## Who can review?
@stevhliu
## Changes
- Corrected the typo for the deprecated flag `[docs]` and added the note for possible dependency issues.
- Updated the note fo... | {
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This PR fixes two critical bugs in the `transformers chat` CLI that prevent users from using chat:
### Issue 1: Chat CLI doesn't use GPU by default
**Problem**: The chat CLI was defaulting to CPU inference even when GPUs are available, leading to slow performance.
**Root Cause**: The ... | {
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any
### Who can help?
[here](https://github.com/huggingface/transformers/blob/main/setup.py#L154)
pytest is a test framework and pytest-* packages should be test dependencies, not run-time dependencies.
### Information
- [ ] The official example scripts
- [ ] My own modified scripts
### Tasks
-... | {
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Env output:
```
Instructions for updating:
Use `tf.config.list_physical_devices('GPU')` instead.
I0000 00:00:1755460445.899071 9198 gpu_device.cc:2019] Created device /device:GPU:0 with 94404 MB memory: -> device: 0, name: NVIDIA GH200 480GB, pci bus id: 0000:dd:00.0, compute capability: 9.0
Copy... | {
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"merged_at... | ### Summary ###
This PR updates the dataclasses dependency to only be installed for Python versions less than 3.7, since dataclasses became part of the Python standard library starting with Python 3.7.
### Changes ###
1. Modified setup.py to add python_version<'3.7' marker to the dataclasses dependency.
2. Upda... | {
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Currently this dependency is unconditional.
See https://pypi.org/project/dataclasses/
### Who can help?
_No response_
### Information
- [ ] The official example scripts
- [ ] My own modified scripts
### Tasks
- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- ... | {
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"merged_at... | # What does this PR do?
Returned tensors from the PixtralProcessor does not match the list in `model_input_names` (useful for inferring expected tensor keys).
## 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 [contr... | {
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"merged_at... | This PR adds a note under PreTrainedModel clarifying that seq2seq models
such as MarianMT, BART, and T5 accept either decoder_input_ids or
decoder_inputs_embeds, but not both. Passing both arguments raises a
ValueError.
This addresses issue #39542.
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Looking at current master code.
### Who can help?
@ArthurZucker
### Information
- [ ] The official example scripts
- [ ] My own modified scripts
### Tasks
- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)
### ... | {
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"merged_at... | # What does this PR do?
This pull request includes minor edits to the Transformers documentation:
- Adjusted formatting for clarity and readability
- Ensures consistency with existing documentation style
These changes are only documentation edits and do not affect any code.
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<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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- enable `load_best_model_at_end` when even if `save_strategy` is `best`
- beforehand, it doesn't show any error, but it doesn't load the best, but the last (because `self.state.best_global_step` wasn't updated)
- enable `metric_for_best_model` when `save_strategy` is `best`
- `metric_... | null | {
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This PR fixes an issue with incorrect masking behavior in the model.
The fix ensures that masked tokens are correctly handled during training and inference.
Fixes #40214
Motivation
Previously, the masking logic led to unintended behavior, which could cause incorrect attention patterns... | {
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- `transformers` version: 4.55.0.dev0
- Platform: macOS-15.6-arm64-arm-64bit
- Python version: 3.12.2
- Huggingface_hub version: 0.34.3
- Safetensors version: 0.5.3
- Accelerate version: 1.9.0
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (accelerator?): 2.7.1 (... | {
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https://api.github.com/repos/huggingface/transformers/issues/40218 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/40218/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/40218/comments | https://api.github.com/repos/huggingface/transformers/issues/40218/events | https://github.com/huggingface/transformers/pull/40218 | 3,327,049,525 | PR_kwDOCUB6oc6j7huE | 40,218 | Fix #40067: Add dedicated UMT5 support to GGUF loader (config, tokenizer, test) | {
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"merged_at... | ### PR Description
### Problem
**Fixes #40067**
UMT5EncoderModel.from_pretrained() fails when loading GGUF files, defaulting to T5 configuration and producing the warning:
```
You are using a model of type t5 to instantiate a model of type umt5. This is not supported for all configurations of models and can ... | {
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# Environment: (Google Colab)
Python 3.11.13
torch==2.6.0+cu124
transformers==4.55.2
bitsandbytes==0.47.0
peft==0.17.0
accelerate==1.10.0
numpy==1.26.4
scipy==1.14.1
GPU
NVIDIA L4
Driver Version: 550.54.15
CUDA Version: 12.4
Model Quantized with QLoRA
# Dataset:
Train Dataset... | {
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Adds a check for MPS availability for training BF16 `torch_dtype=torch.bfloat16`
<!-- Remove if not applicable -->
Fixes #39935
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [con... | {
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Closes https://github.com/huggingface/transformers/issues/36978
- Maintains full API compatibility with slow processor
- Includes comprehensive tests and documentation updates
- All 76 tests pass with pr... | {
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When using **chunked attention** with **left padding**, the first chunk may contain fewer valid tokens than `chunk_size`, which introduces a distribution mismatch between training and inference.
Since training typically uses right padding or no padding, the model never sees a chunk where most po... | {
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As the title says, change checkpoints to the official facebook ones.
Feel free to merge without me as I'll be off, Cc @ArthurZucker @Cyrilvallez @ydshieh. | {
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Fix more typos | {
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Some of the unit tests are still failing, need to debug. | {
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@ArthurZucker, @Rocketknight1
I'm also working on the attention_interface version here #40211, but having this fixed will help in deb... | {
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This PR implements a fast PyTorch image processor for ViViT (`VivitImageProcessorFast`) that extends the existing `BaseImageProcessorFast` class. The new processor provides optimized image processing capabilities specifically designed for video understanding tasks using the ViViT model.
#... | null | {
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Follow up to #36627 (issue #36626) where that PR misdiagnosed the underlying issue. The reason it wouldn't save is that the output_dir didn't exist yet because it was created in the checkpoint/optimizer save method. This fixes the issue by moving the checkpoint dir creation to the top.
Ad... | null | {
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Add support for context parallel in the Trainer | {
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Fix more pylint warnings.
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I installed the environment to run gpt-oss-20b using the following command:
> uv pip install --pre vllm==0.10.1+gptoss \
--extra-index-url https://wheels.vllm.ai/gpt-oss/ \
--extra-index-url https://download.pytorch.org/whl/nightly/cu128 \
--index-strategy unsafe-best-match
My GPU is 5090... | {
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This will use a custom pytest where we replace
> raise SystemExit(pytest.console_main())
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Add DeepseekV3ForSequenceClassification for DeepseekV3 models following generic practice
Testing:
Tested with single-node option, loss curve and AUC are all expected with no issue.
- All testes passed
- make fixup passed
Fixes #40199
## Before submitting
- [ ] This PR fixes ... | {
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Hello,
Thanks for your efforts, greatly appreciated. I was wondering when will you add support for a sequence classification for Deepseek v3.
### Motivation
This would be extremely helpful for the tiny model of Deepseek v3 which uses the same class as the original model.
### Your contribution
. | {
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Without it, it would inherit the one from Cache, and fail because `self.layers` does not exist in `EncoderDecoderCache` | {
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A warning is raised on conflict, ensuring users notice any override
# What does this PR do?
I note that current transformer use ... | {
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Copy-and-paste the text below in your GitHub issue and FILL OUT the two last points.
- `transformers` version: 4.54.0
- Platform: Linux-6.8.0-64-generic-x86_64-with-glibc2.35
- Python version: 3.10.18
- Huggingface_hub version: 0.34.4
- Safetensors version: 0.6.2
- Accelerate version: 1.10.0
- Accele... | {
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"merged_at... | # What does this PR do?
Currently, trying to print `EncoderDecoderCache` instances results in an error:
> AttributeError: 'EncoderDecoderCache' object has no attribute 'layers'
This PR fixes the error. It adds a couple of tests for `repr`s of cache instances. The tests are not exhaustive but focus on the cache... | {
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"merged_at... | # What does this PR do?
As per the title. Fixes https://github.com/huggingface/transformers/issues/39977
Inheriting from `ABC` would result in this kind of errors when using fsdp: `TypeError: __class__ assignment: 'FSDPQwen2ForTokenClassification' object layout differs from 'Qwen2ForTokenClassification'`.
As hav... | {
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https://api.github.com/repos/huggingface/transformers/issues/40190 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/40190/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/40190/comments | https://api.github.com/repos/huggingface/transformers/issues/40190/events | https://github.com/huggingface/transformers/pull/40190 | 3,324,853,383 | PR_kwDOCUB6oc6j0fMY | 40,190 | Add GptOssForTokenClassification for GPT-OSS models | {
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"merged_at... | # What does this PR do?
Add GptOssForTokenClassification for GPT-OSS models following generic practice
Testing:
Tested with single-node option, loss curve and AUC are all expected with no issue.
- All testes passed
- make fixup passed
Fixes #40189
## Before submitting
- [ ] This PR fixes a typo or... | {
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Support token classification with GPT-OSS models
### Motivation
Let GPT-OSS models dealing with token classification problems more efficiently
### Your contribution
PR submission | {
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transformers ==4.55.2 on A100, python=3.10
### Who can help?
_No response_
### Information
- [x] The official example scripts
- [ ] My own modified scripts
### Tasks
- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details b... | {
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- `transformers` version: 4.53.3
- Platform: Linux-6.8.0-1033-aws-x86_64-with-glibc2.35
- Python version: 3.11.9
- Huggingface_hub version: 0.32.2
- Safetensors version: 0.4.3
- Accelerate version: 1.6.0
- Accelerate config: not found
- DeepSpeed version: not installed
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"merged_at... | # What does this PR do?
Fixes #40111
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#create-a-pull-request),
Pu... | {
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"merged_at... | # What does this PR do?
I was getting the following warning when training with `stable_adamw` and `decouple_lr=True`, even though the `TrainingArguments.weight_decay` was set to a different value.
```
optimi/optimizer.py:41: UserWarning: You are using weight_decay=0.01 which is potentially high for decouple_lr=Tru... | {
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I do not have a POC, it's happening in a project I am working on.
```
return self.uncompiled_model.generate(
File "/root/.pyenv/versions/3.10.13/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 120, in decorate_context
return func(*args, **kwargs)
File "/root/.pyenv/versions/3... | {
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"merged_at... | …t; fix decoder start token and masks; resolves wrong ONNX output for OPUS en-ar (ref #40122)
# What does this PR do?
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# Fix ESM `token_dropout` crash when using `inputs_embeds` instead of `input_ids`
## Description
This PR fixes an issue in the ESM model where calling `forward` with `inputs_embeds` (and no `input_ids`) would trigger an `AttributeError` in the `token_dropout` logic:
```
AttributeError: 'bool' objec... | {
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"merged_at... | # Enable native mxfp4 training support for GPT-OSS models
Fixes #40170
## What does this PR do?
This PR adds the foundational infrastructure to enable native mxfp4 training for GPT-OSS models, addressing the issue where users currently must convert 4-bit weights to bfloat16 for training (using 4X more memory)... | null | {
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There are SLURM examples in your docs e.g. https://github.com/huggingface/transformers/blob/31b6e6e1dac0d32f74ec5cd6b3c1868534ccd7b5/docs/source/en/deepspeed.md
but I am a [SkyPilot](https://docs.skypilot.co/en/latest/docs/index.html) user and would like to have those as well.
### Motivation
... | null | {
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* Updated `_check_and_adjust_attn_implementation` to set the attention implementation to `kernels-community/flash-attn` when FlashAttention2 is requested but not available, ensuring seamless fallback and proper kernel registration.
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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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Allows saving gpt_oss after it was trained. You can also save a mxfp4 model.
```python
import torch
import gc
from transformers import Mxfp4Config, GptOssForCausalLM, AutoTokenizer
model_name = "hf-internal-testing/gpt-oss-20b-bf16"
loaded_model = GptOssForCausalLM.from_pretrained(
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Fix some typos in comments.
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It's possible torch 2.8 causing much more `Too long without output` on CircleCI jobs. | {
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"merged_at... | The chat template docs were split into multiple parts and also refactored in recent PRs. The result is quite messy in some cases, and several examples are incomplete, or the text is misleading. I only noticed when I tried to refer to the docs while writing the `gpt-oss` template and realized that in many cases the text... | {
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As the title says, this seems to be more and more relevant for downstream libraries, namely vLLM Cc @hmellor
It's another attribute to think about when contributing a new fast image processor, but as this one is tested for, no choice but to add it correctly 😉. Maybe we should add this kin... | {
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Rename DINOv3ViT -> Dinov3Vit, DINOv3 -> Dinov3
cc @ArthurZucker
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The Hugging Face community needs you! 🫵
The `GPT-OSS` model was recently added using `mxfp4` weights. These 4-bit weights are tiny and highly performant on H100/B100/50xx GPUs, but we only have kernels for **forward** passes. This means that users can't train `GPT-OSS` unless they convert the w... | null | {
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"merged_at... | All other occurrences in the docs use lowercase. (https://github.com/search?q=repo%3Ahuggingface%2Ftransformers%20translation_XX_to_YY&type=code)
Also, using uppercase doesn't work: tested with "translation_EN_to_FR" which doesn't work and instead returns: `ValueError: The task does not provide any default models f... | {
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- `transformers` version: 4.48.1
- Platform: Linux-5.14.0-503.40.1.el9_5.x86_64-x86_64-with-glibc2.34
- Python version: 3.10.18
- Huggingface_hub version: 0.34.4
- Safetensors version: 0.6.2
- Accelerate version: 1.10.0
- Accelerate config: not found
- PyTorch version (GPU?): 2.5.1 (False)
- Tensorf... | {
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- transformers version: 4.52.4
- Platform: Linux-5.14.0-503.23.2.el9_5.x86_64-x86_64-with-glibc2.34
- Python version: 3.12.4
- Huggingface_hub version: 0.33.1
- Safetensors version: 0.5.3
- Accelerate version: not installed
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch ver... | {
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to see if this could reduce
https://app.circleci.com/pipelines/github/huggingface/transformers/141243/workflows/d61ac0c2-3205-433f-a744-a045664e6a05/jobs/1869761 | {
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This is what I have in mind. Happy to hear some suggestion if any.
(I will have a few methods to patch in my todo list) | {
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https://api.github.com/repos/huggingface/transformers/issues/40163 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/40163/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/40163/comments | https://api.github.com/repos/huggingface/transformers/issues/40163/events | https://github.com/huggingface/transformers/pull/40163 | 3,322,044,102 | PR_kwDOCUB6oc6jrL5T | 40,163 | :rotating_light: [`Flash Attention`] Fix sliding window size | {
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"merged_at... | Fixes #39408
This issue will occur especially during the prefill phase when sliding window < prefill size. Newer cache refactors automatically remove kvs beyond the window so inference would/should have been less affected. Small script to show the effects:
```python
import torch
from transformers import AutoToken... | {
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https://api.github.com/repos/huggingface/transformers/issues/40162 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/40162/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/40162/comments | https://api.github.com/repos/huggingface/transformers/issues/40162/events | https://github.com/huggingface/transformers/pull/40162 | 3,321,924,242 | PR_kwDOCUB6oc6jq0G- | 40,162 | fix to avoid modifying a view in place | {
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When using `tp_auto` on `GptOssModel`, I got the following
```
RuntimeError: Output 0 of _ToTorchTensorBackward is a view and is being modified inplace. This view was created inside a custom Function (or because an input was returned as-is) and the autograd logic to handle view+inplace wo... | {
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https://api.github.com/repos/huggingface/transformers/issues/40161 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/40161/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/40161/comments | https://api.github.com/repos/huggingface/transformers/issues/40161/events | https://github.com/huggingface/transformers/pull/40161 | 3,321,848,464 | PR_kwDOCUB6oc6jqkXr | 40,161 | [FA2] Fix it finally - revert fa kwargs preparation | {
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Preparing the fa kwargs in advance is currently useless as it's being recomputed anyway. And worst, it actually break things, see following explanation.
When `_flash_attention_forward` is called, the following paths are taken inside the function:
```python
# Contains at least one padd... | {
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but some usages of `F` remained unchanged, breaking CI ([example](https://app.circleci.com/pipelines/github/huggingface/transformers/142032/workflows/d0770631-92... | {
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Some models have empty `config.head_dim` so we now check if the value is not None instead of setting it to `None` | {
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"merged_at... | # What does this PR do?
This PR fixes a bug in the `list_repo_templates` function where network connectivity issues would cause the entire function to crash instead of gracefully falling back to local files.
## Problem
When used without an internet connection, the function raised:
```
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"merged_at... | # What does this PR do?
These tests were meant to be skipped as well but they aren't run always so I missed them the last time. And not they appear on CI as flaky 🙃
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This ensures that the naming is always the same across MoEs | null | {
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# What does this PR do?
Translated the `t5.md` file of the documentation to Korean.
Thank you in advance for your review.
Part of https://github.com/huggingface/transformers/issues/20179
## Before reviewing
- [x] Check for missi... | null | {
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- `transformers` version: 4.55.0
- Platform: Linux-5.15.0-1032-oracle-x86_64-with-glibc2.35
- Python version: 3.12.3
- Huggingface_hub version: 0.34.3
- Safetensors version: 0.6.1
- Accelerate version: 1.10.0
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output of `transforms env` :
- `transformers` version: 4.55.0
- Platform: Linux-6.14.0-1012-gcp-x86_64-with-glibc2.39
- Python version: 3.12.3
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"merged_at... | This PR adds a beginner-friendly model card for `bert-base-uncased` under `docs/source/model_cards/`.
Includes:
- Model description (plain language)
- Usage example
- Intended use & limitations
- Resources and references
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#40002 cause Flash-Attention2 unavailable on Ascend NPU, **the core reason is package `flash-attn` unavailable on Ascend NPU, even can not be installed**, current implementation will cause **ImportError** on Ascend NPU.
This PR is committed for fixing this problem, remove redundant `apply_... | {
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This PR implements a fast PyTorch image processor for VitPose (`VitPoseImageProcessorFast`) that extends the existing `BaseImageProcessorFast` class. The new processor provides optimized image processing capabilities specifically designed for pose estimation tasks using the VitPose model.
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- Update utils.py: fix nan
- Suggested in https://github.com/huggingface/transformers/pull/40093/commits/7e230e5464705e6e235aec47d8a7312a3404ba15
@ArthurZucker @zucchini-nlp
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"merged_at... | Resolves #36978
Adds fast image processor for Aria model using PyTorch operations.
- Full implementation with image splitting and patching support
- Same outputs as slow processor
- All linting checks pass | {
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"merged_at... | Resolves #36978
This PR adds a fast image processor for the Aria model using PyTorch operations instead of PIL/numpy for better performance.
## Implementation
- Full PyTorch/torchvision implementation of Aria's image preprocessing
- Maintains all Aria-specific features (image splitting, patching, custom resolutions)
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Vision Transformer with Mixture of Experts (ViT-MoE) is an efficient scaling approach for vision transformers that replaces dense feedforward layers with sparse mixture of experts.
This architecture enables scaling model capacity while keeping per-token computation roughly constant, achieving be... | {
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As per the title. It fixes the initialization of the Cache that changed after all the cache refactors | {
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"merged_at... | As `torch` and `transformers` already support multiple devices("cuda", "xpu" etc) as their built-in devices, maybe it's a good time to extend model doc examples to a device-agnostic one rather than binding to "cuda". I am add a `infer_device` API in utils to automatically detect available device in runtime.
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"merged_at... | # What does this PR do?
All of them except 1 have been failing in disguise from a long-time, because they would get skipped in the middle of the for loop, before they would actually fail 🙃🥵
Only flaubert started failing recently, which was only skipped before. But since torchscript has been dropped and is no lon... | {
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"merged_at... | # What does this PR do?
Fixes a couple of bugs introduced in the implementation of EfficientLoFTR.
Adds a cross attention bug introduced by the authors which makes the weights dependant on (see https://github.com/zju3dv/MatchAnything/issues/26)
## Who can review?
@qubvel
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Fix after https://github.com/huggingface/transformers/pull/39797 - function does not expect the device anymore | {
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