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https://api.github.com/repos/huggingface/transformers/issues/38732 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38732/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38732/comments | https://api.github.com/repos/huggingface/transformers/issues/38732/events | https://github.com/huggingface/transformers/pull/38732 | 3,133,823,288 | PR_kwDOCUB6oc6Z356e | 38,732 | [llava] fix integration tests with Siglip | {
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"merged_at... | # What does this PR do?
Fixes https://github.com/huggingface/transformers/pull/38722#issuecomment-2958809929
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# What does this PR do?
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In the [v4.52.1 release](https://github.com/huggingface/transformers/releases/tag/v4.52.1) of the transformers library, PR #37033 @zucchini-nlp introduced a bug by renaming the class PaliGemmaForConditionalGeneration(PaliGemmaPreTrainedModel, GenerationMixin) to class PaliGemmaModel(PaliGemm... | {
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The following PRs were cherry-picked from this branch:
- #38529 , which led to conflicts on `qwen3` and `xglm`
- #38698
- #38697
- #38581
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This PR clarifies the type of `num_items_in_batch` + better docstring | {
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https://api.github.com/repos/huggingface/transformers/issues/38727 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38727/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38727/comments | https://api.github.com/repos/huggingface/transformers/issues/38727/events | https://github.com/huggingface/transformers/issues/38727 | 3,133,267,691 | I_kwDOCUB6oc66wd7r | 38,727 | KV Cache Bug in Iterative generation | {
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According to the code in [here](https://huggingface.co/docs/transformers/kv_cache#iterative-generation), i can use such code for Iterative generation. How ever, this happened:
`---------------------------------------------------------------------------
IndexError Tracebac... | {
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The following error comes up: ModuleNotFoundError: No module named transformers.models.ipynb_checkpoints'
Packages:
ipykernel==6.29.5
- `transformers` version: 4.52.4
- Platform: Linux-5.10.226-214.880.amzn2.x86_64-x86_64-with-glibc2.39
- Python version: 3.10.16
- Huggingface_hub version: 0.31.4
- Saf... | {
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### Reproduction
For example,
> RUN_SLOW=1 python3 -m pytest -v tests/models/moshi/test_modeling_moshi.py::MoshiIntegrationTests::test_moshika_greedy_unconditional_fp16
Since then, during 8 months, there are several periods where those tests are failing with di... | {
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"merged_at... | Added DPTImageProcessorFast for efficient batched preprocessing using torch/torchvision
# What does this PR do?
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They are failing for long time, some are matching issues and some are OOM issue.
Tests pass on A10 / T4 (torch 2.7.1) except `test_generation_siglip_backbone`
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transformers version 4.53.0.dev0
flash_attn version 2.7.4.post1 (via pip)
Using offical transformers image from: https://hub.docker.com/r/huggingface/transformers-pytorch-gpu
### Who can help?
@ArthurZucker
@zach-huggingface
### Information
- [ ] The official example scripts
- [x] My own modified ... | {
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"merged_at... | What does this PR do?
This PR adds a new encoder-only Transformer model called Fireflies, designed as a lightweight, modular architecture for NLP research. The model was built from scratch using standard PyTorch modules and Hugging Face’s PreTrainedModel interface.
Key Features:
Implements a standard nn.Transforme... | {
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- [x] Fixes a typo in `activations.py` that uses an undefined symbol `gelu`. | {
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error info is：
Joy_caption_two_advanced
`.to` is not supported for `4-bit` or `8-bit` bitsandbytes models. Please use the model as it is, since the model has already been set to the correct devices and casted to the correct `dtype`.
# ComfyUI Error Report
## Error Details
- **Node ID:** 64
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"merged_at... | This PR adds support for returning the last_hidden_state in the get_video_features method of XCLIPModel, as requested in #38709.
## ✅ Summary of changes
Added a new class `XCLIPVideoFeatureOutput` inheriting from `BaseModelOutput`, including:
- `pooled_output`
- Optional `last_hidden_state`
- Optional `hidden_... | null | {
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https://github.com/huggingface/transformers/blame/81799d8b556b3c810ed314187674bc439c0582b4/s... | {
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This PR aims to address the issue raised in #38032 by deciding the format in which the loss should be logged
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Replace typing.{List,Tuple,Dict} with {list, tuple,dict}. Due to the large amount of all changes, they are split into smaller PRs. | {
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Gradually apply Python 3.9 syntax to existing files. This PR changes OSError aliases to OSError. | {
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DeepSeek V3 generate uses get_max_length(removed in 4.49.0) and fp8 quantization(introduced in 4.49.0)
1. DeepSeek 671B models use: past_key_values.get_max_length:
https://huggingface.co/deepseek-ai/DeepSeek-V3/blob/main/modeling_deepseek.py#L1654
https://huggingface.co/deepseek-ai/DeepSeek-R1/blob/ma... | {
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https://github.com/huggingface/transformers/blob/f4fc42216cd56ab6b68270bf80d811614d8d59e4/src/transformers/models/x_clip/modeling_x_clip.py#L1376
Hi
The `get_video_features` function is hardcoded to always return the `pooled_output`. But sometimes, it might be beneficial to get the `last_hidden_state... | {
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**Bert2D** is a novel transformer-based model that builds upon the `BertModel` architecture by introducing a two-dimensional word embedding system. This enhancement is specifically designed to improve performance on morphologically rich languages, such as Turkish, Finnish, and Hungarian. This mod... | null | {
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"merged_at... | # What does this PR do?
<!--
Adding quotes to the large run command for the speech pretraining example, since it was not being run while copying and pasting.
-->
## 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 th... | {
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`test_11b_model_integration_forward` has dtype issue, it fails, and affect other tests (GPU OOM).
I also update the expected values for A10.
All tests pass now on T4/A10 + torch 2.6/2.7 | {
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"merged_at... | ### What does this PR do?
This PR makes the `transformers-cli add-new-model-like` command usable again for any model whose tokenizer mapping is written on multiple lines (e.g. llama).
### Current failure modes
1. **`IndexError` while locating `TOKENIZER_MAPPING_NAMES`.**
Inside function `transformers/src/t... | {
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Irrelevant
### Who can help?
@ArthurZucker
Google Gemma implementation casts embedding scale to bloat16, which rounds 33.9411 to 34.0
To match this behaviour, [HF implementation](https://github.com/huggingface/transformers/blob/d7b87b415a5dd4a3152051e1a0abd098a02c5bfa/src/transformers/models/gemma3... | {
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Just some updates of expected outputs.
I change the dtype used in `InternVLQwen2IntegrationTest` from `bfloat16` to `float16`, as the outputs with `bfloat16` on `T4` machine is not very stable (here across torch versions), and therefore I have to update the outputs for A10 `("cuda", 8)` to... | {
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https://api.github.com/repos/huggingface/transformers/issues/38700 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38700/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38700/comments | https://api.github.com/repos/huggingface/transformers/issues/38700/events | https://github.com/huggingface/transformers/pull/38700 | 3,130,223,599 | PR_kwDOCUB6oc6Zrk5X | 38,700 | Small fixes amd | {
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"merged_at... | This PR fixes two small things:
- `janus` decoder handling to avoid a multiple device error (will soon be merged in main, #38488 )
- `modernbert` has a `pos_idx_in_fp32` kwargs for RotaryEmbedding which is no longer an argument for init in the parent class (https://github.com/Dao-AILab/flash-attention/commit/1870a0dc... | {
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https://api.github.com/repos/huggingface/transformers/issues/38699 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38699/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38699/comments | https://api.github.com/repos/huggingface/transformers/issues/38699/events | https://github.com/huggingface/transformers/pull/38699 | 3,130,210,566 | PR_kwDOCUB6oc6Zrh-v | 38,699 | Standardize ByT5 model card format | {
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"merged_at... | # What does this PR do?
This PR updates the ByT5 model card to follow the standardized format as requested in #36979.
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [contributor guideline](https://github.com/hug... | {
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cc. @mht-sharma | {
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The goal of this PR is to integrate inference and training support for the FP-Quant method that utilizes the Hadamard Transform for efficient weights+activations quantization. When using it with MXFP4 and MSE-based scaling, it implements [Quartet forward pass](https://... | {
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This PR introduces MViT, which is the basis for MeMViT, which is a video transformer that got requested in the issue below. I'm currently doing research in fine-grained video understanding and MeMViT happens to be able to process long video sequences. Unfortunately it's only available from th... | {
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Fix some models import.
<!--
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.
Th... | {
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I’d like to contribute an implementation of the MulT model described in the paper:
**Title:** Multimodal Transformer for Unaligned Multimodal Language Sequences
**Paper:** [https://arxiv.org/pdf/1906.00295v1](https://arxiv.org/pdf/1906.00295v1)
### 💡 Motivation
MulT is a powerful approach f... | {
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Hi guys, I just downloaded flux models and then if I Run, I received the following error:
CheckpointLoaderSimple ..... Error while deserializing header: InvalidHeaderDeserialization
# ComfyUI Error Report
## Error Details
- **Node ID:** 3
- **Node Type:** CheckpointLoaderSimple
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"merged_at... | # What does this PR do?
This is needed to avoid `.item()` calls in `_flash_attention_forward`.
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/bl... | {
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torch 2.7.1
Regression introduced by #37866
### Who can help?
@SunMarc @cyrilzakka @ArthurZucker
### Information
- [ ] The official example scripts
- [x] My own modified scripts
### Tasks
- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [x] My own task or ... | {
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"merged_at... | per https://github.com/pytorch/ao/tree/main/torchao/prototype, from1.11.0, `torchao.prototype.low_bit_optim` is promoted to `torchao.optim`, so will have `AttributeError: module 'torchao.prototype' has no attribute 'low_bit_optim' ` w/ torchao 1.11.0.
@ydshieh , pls help review, thx. | {
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"merged_at... | ✨What does this PR do?
This PR introduces a new transformer-based model architecture called Fireflies into the Hugging Face Transformers library.
The Fireflies model is a flexible, encoder-based architecture designed for language modeling and research experimentation. It is compatible with the Hugging Face AutoMode... | {
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transformers version: 4.52.4
Platform: linux
Python version: 3.10.16
Accelerate version: 1.7.0
PyTorch version: 2.6.0+cu124
peft version: 0.15.2
trl version: 0.18.1
### Who can help?
_No response_
### Information
- [ ] The official example scripts
- [x] My own modified scripts
### Ta... | {
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When the model inherits from `PreTrainedModel`, the _save() function follows [this logic](https://github.com/huggingface/transformers/blob/10627c1a0f6877ce6715b9537afe7fafb2a89edd/src/transformers/t... | {
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This PR adds a new custom Transformer-based language model architecture named **Fireflies** to the Hugging Face Transformers library.
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This is a feature request to implement "Orthogonal Residual Update," a novel mechanism for training deep neural networks proposed in the paper "[Revisiting Residual Connections: Orthogonal Updates for Stable and Efficient Deep Networks](https://arxiv.org/abs/2505.11881)".
The core idea is to modif... | null | {
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* Handling of indi... | {
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cc @guangy10
issue opened https://github.com/pytorch/pytorch/issues/153599 | {
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This PR replaces the Pegasus model card with a new model card matching the format introduced in https://github.com/huggingface/transformers/issues/36979.
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did ... | {
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The processor tests and integration tests are never run due to an issue of `@require_read_token`.
After a fix #38093, I should had update the expected values for integration test but not done at that moment - now it is done.
For processor tests, we no longer need `@require_read_token` a... | {
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Fixes #38258
## Description
This PR resolves an issue where keyword arguments passed to `from_pretrained` or `from_config` for composite models were not being correctly routed to the respective sub-configs. This would lead to a `TypeError` when an argument intended for a sub-model (e.g., `use_cache=True` for a ... | null | {
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TPUs now support bfloat16 (bf16). But current version of transformers would raise an error `"Your setup doesn't support bf16/gpu."` if bf16 is enabled on TPU.
## 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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GGUF support for deci
Fixes #37736
## Before submitting
- [X] Was this discussed/approved via a Github issue or the Please add a link
## Who can review?
@MekkCyber
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"merged_at... | Add post_init() calls to EsmForMaskedLM, EsmForTokenClassification and EsmForSequenceClassification.
# What does this PR do?
Adds `post_init()` calls to esm models in order to prevent the error "TypeError: 'NoneType' object is not iterable".
Fixes # 38667
## Before submitting
- [:x: ] This PR fixes a typo... | {
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2 machines:
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- Python version: 3.12.10
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"merged_at... | # What does this PR do?
This PR addresses [huggingface/hub-docs#1600](https://github.com/huggingface/hub-docs/issues/1600).
The issue relates to the [`Trainer.compute_loss`](https://huggingface.co/docs/transformers/v4.48.2/en/trainer) documentation, which is maintained in the `transformers` repository.
I have ... | null | {
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Platform: Linux-5.10.0-1029-oem-x86_64-with-glibc2.31
GPU device: Quadro RTX 8000
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Huggingface_hub version: 0.32.2
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https://api.github.com/repos/huggingface/transformers/issues/38664 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38664/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38664/comments | https://api.github.com/repos/huggingface/transformers/issues/38664/events | https://github.com/huggingface/transformers/pull/38664 | 3,127,505,864 | PR_kwDOCUB6oc6ZiYtZ | 38,664 | Fixed modeling_auto.py MODEL_FOR_MASK_GENERATION_MAPPING_NAMES variable | {
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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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https://api.github.com/repos/huggingface/transformers/issues/38663 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38663/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38663/comments | https://api.github.com/repos/huggingface/transformers/issues/38663/events | https://github.com/huggingface/transformers/issues/38663 | 3,127,503,194 | I_kwDOCUB6oc66aela | 38,663 | MODEL_FOR_MASK_GENERATION_MAPPING_NAMES variable is present twice in modeling_auto.py | {
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Was looking around the Auto classes for some reason and noticed that ``MODEL_FOR_MASK_GENERATION_MAPPING_NAMES`` is present twice in ``modeling_auto.py``. Seems to come from this [PR](https://github.com/huggingface/transformers/pull/35147)
See here
https://github.com/huggingface/transformers/blob/ebeec13609b537f9... | {
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- Platform: Linux-6.8.0-60-generic-x86_64-with-glibc2.39
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- Accelerate config: not found
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https://api.github.com/repos/huggingface/transformers/issues/38661 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38661/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38661/comments | https://api.github.com/repos/huggingface/transformers/issues/38661/events | https://github.com/huggingface/transformers/pull/38661 | 3,127,358,412 | PR_kwDOCUB6oc6Zh4vF | 38,661 | fix(auto): Route kwargs correctly for composite models | {
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Fixes #38258
## Description
This PR resolves an issue where keyword arguments passed to `from_pretrained` or `from_config` for composite models were not being correctly routed to the respective sub-configs. This would lead to a `TypeError` when an argu... | {
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"merged_at... | # What does this PR do?
Fixes raising `TypeError` instead of ValueError when encountering invalid types
## 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/transfor... | {
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- `transformers` version: 4.52.4
- Platform: Linux-6.1.123+-x86_64-with-glibc2.35
- Python version: 3.11.13
- Huggingface_hub version: 0.32.4
- Safetensors version: 0.5.3
- Accelerate version: 1.7.0
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (GPU?): 2.6.0+cu124... | {
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These never pass since the model is added.
Now pass both on A10 and T4 | {
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Transformers have become de facto essential deep learning tools. However, you only provide interface APIs for three languages: Python, JavaScript, and Rust. Have you forgotten about Java, Scala, and Kotlin? Is it because your team lacks manpower or isn't proficient in the JVM? Currently, there are ... | null | {
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Hi team,
Thank you for your great work on `transformers`!
While using the `AutoProcessor` with `use_fast=True`, I noticed that there seems to be a memory leak or possibly some form of persistent caching when processing images. Even after deleting the processor and clearing the CUDA cache, approximate... | {
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"merged_at... | Hey! Fixed errors:
src/transformers/masking_utils.py
`necesary` - `necessary` x2
src/transformers/model_debugging_utils.py
`spearate` - `separate`
src/transformers/video_processing_utils.py
`successfull` - `successful` | null | {
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I tried to restore the image, using tensor in inputs['pixel_values'], but I found that the restored image patches were in disorder.
So how to restore the image from inputs['pixel_values'] in a proper way?
For ex... | {
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"merged_at... | Fixes #38268
### Feature Description
This PR implements the feature request to add sampling capabilities (e.g., Top-K, Top-P, temperature) to Group Beam Search, which was previously a purely greedy algorithm.
### Problem
Currently, `_group_beam_search` in the `GenerationMixin` is implemented as a deterministic ... | null | {
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It fixes a couple of typos under the Language Modeling Pytorch examples directory that prevented the example to be run successfully. It also changes the DsitributedType in the accelerator module from TPU to TP according to the accelerate [repository](https://github.com/huggingface/accelerate/... | {
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"merged_at... | # What does this PR do?
Updates the quantization overview documentation to indicate that bitsandbytes is now compatible with `torch.compile`.
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [contributor guideline]... | {
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"ValueError: GGUF model with architecture qwen3 is not supported yet."
I have the latest transformers and gguf-0.17.0
```
self.tokenizer = AutoTokenizer.from_pretrained(model_name, gguf_file= "Qwen3-0.6B-Q2_K_L.gguf",use_fast=True)
... | {
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"merged_at... | # What does this PR do?
Refactored the Qwen2MoE model card to match the template
## Before submitting
- This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
## Who can review?
@stevhliu
Anyone in the community is free to review the PR once the tests have pa... | {
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"merged_at... | Fixes #38268
### Feature Description
This PR implements the feature request to add sampling capabilities (e.g., Top-K, Top-P, temperature) to Group Beam Search, which was previously a purely greedy algorithm.
### Problem
Currently, `_group_beam_search` in the `GenerationMixin` is implemented as a deterministic ... | {
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Revert minimal changes made from https://github.com/huggingface/transformers/pull/37866 that breaks export to ExecuTorch in [huggingface/optimum-executorch](https://github.com/huggingface/optimum-executorch) when developing from latest `transformers` trunk
TODO: Will update with tests shor... | {
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"merged_at... | # What does this PR do?
This PR adds gguf loading support for qwen3 models.
## Before submitting
- [No] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [Yes] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.... | {
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Add sliding window attention support to Continuous Batching code. Took inspiration from the existing `SlidingWindowCache`. | {
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We won't actively maintain the torchscript stuff.
See #35972
Probably I need to do the same as in #35972 but you get the idea :-) | {
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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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Adds [Universal Intelligence](https://github.com/blueraai/universal-intelligence) to `awesome-transformers.md` documentation
## Who can review?
Documentation: @stevhliu @LysandreJik
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https://api.github.com/repos/huggingface/transformers/issues/38640 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38640/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38640/comments | https://api.github.com/repos/huggingface/transformers/issues/38640/events | https://github.com/huggingface/transformers/pull/38640 | 3,125,139,597 | PR_kwDOCUB6oc6ZaSod | 38,640 | Fix qwen2-audio chat template audio placeholder insertion | {
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transformers/pytorch_utils.py", line 300, in id_tensor_storage
if is_torch_greater_or_equal_than_2_0:
from torch.distributed.tensor import DTensor
The error "ImportError: cannot import name 'dtensor' from 'torch.distributed.tensor'" arises due to changes in the location of the DTensor clas... | {
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https://api.github.com/repos/huggingface/transformers/issues/38638 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38638/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38638/comments | https://api.github.com/repos/huggingface/transformers/issues/38638/events | https://github.com/huggingface/transformers/pull/38638 | 3,124,801,652 | PR_kwDOCUB6oc6ZZJiy | 38,638 | 5GB to 50GB as a default | {
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https://api.github.com/repos/huggingface/transformers/issues/38637 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38637/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38637/comments | https://api.github.com/repos/huggingface/transformers/issues/38637/events | https://github.com/huggingface/transformers/pull/38637 | 3,124,177,537 | PR_kwDOCUB6oc6ZXA5W | 38,637 | Fix attention mask expansion when converting to executorch | {
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I was trying to convert clip to Executorch and had an issue with `AttentionMaskConverter._expand_mask`
```
# load model
import torch
from transformers import AutoProcessor, AutoModel
model_clip = AutoModel.from_pretrained("openai/clip-vit-base-patch32", torch_dtype=torch.float16) # ... | {
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https://api.github.com/repos/huggingface/transformers/issues/38636 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38636/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38636/comments | https://api.github.com/repos/huggingface/transformers/issues/38636/events | https://github.com/huggingface/transformers/pull/38636 | 3,124,028,089 | PR_kwDOCUB6oc6ZWf5H | 38,636 | Skip `test_initialization` for `SwiftFormer` | {
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`SwiftFormer` has
```
class SwiftFormerEfficientAdditiveAttention(nn.Module):
def __init__(self, config: SwiftFormerConfig, dim: int = 512):
super().__init__()
self.w_g = nn.Parameter(torch.randn(dim, 1))
```
and `self.w_g` is not handled by `_init_weights` and ... | {
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https://api.github.com/repos/huggingface/transformers/issues/38635 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38635/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38635/comments | https://api.github.com/repos/huggingface/transformers/issues/38635/events | https://github.com/huggingface/transformers/pull/38635 | 3,123,999,045 | PR_kwDOCUB6oc6ZWZb1 | 38,635 | [cache] make all classes cache compatible finally | {
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As per title, and let's get rid of `_supports_cache/_supports_quantized_cache` flags. We will assume all models from now on support cache and initialize a `DynamicCache` (model-specific cache in case of mamba) by default
For the static cache, we can't yet assume all models support it becau... | {
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https://api.github.com/repos/huggingface/transformers/issues/38634 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38634/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38634/comments | https://api.github.com/repos/huggingface/transformers/issues/38634/events | https://github.com/huggingface/transformers/issues/38634 | 3,123,973,333 | I_kwDOCUB6oc66NAzV | 38,634 | Download models from a private hub in 2025 | {
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In the context of a private hub deployment, customers would like to use from_pretrained() to load models from their hub, not from the public hub. This doesn't seem to be configurable at the moment and it would be nice to add this feature.
The obvious workaround is to clone the repo first and then ... | {
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Adds logger warning when user uses `split_batches=True` in `accelerator_config` arg of Trainer.
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