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https://api.github.com/repos/huggingface/transformers/issues/39837 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39837/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39837/comments | https://api.github.com/repos/huggingface/transformers/issues/39837/events | https://github.com/huggingface/transformers/pull/39837 | 3,282,425,868 | PR_kwDOCUB6oc6hpAVr | 39,837 | add step3v in VLMS | {
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I would like to kindly request the addition of a new VLM entry, `"step3v"`, at the following location:
[https://github.com/huggingface/transformers/blob/2c0af41ce5c448f872f3222a75f56030fb2e5a88/src/transformers/modeling\_utils.py#L233](https://github.com/huggingface/transformers/blob/2c0af41... | null | {
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Allows specifying `inputs_embeds` in `TorchExportableModule`'s in order to support export of multimodal model's text decoders.
Adds `config` and `generation_config` to the constructors to support multimodal models since the `TorchExportableModule` will wrap the nested text decoder model, w... | {
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- `transformers` version: 4.54.1
- Platform: Linux-6.8.0-1032-aws-x86_64-with-glibc2.35
- Python version: 3.10.0
- Huggingface_hub version: 0.34.3
- Safetensors version: 0.5.3
- Accelerate version: 1.8.0
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (accelerator... | {
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Hi all, first of all if this feature already exists I apologise!
With the rise of multimodal LLMs if would be great if we could add extra outputs to `GenerationMixin.generate` results. For instance if we implement a model like Janus from DeepSeek, there are two output heads. One `lm_head`, and one... | null | {
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the model... | {
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"merged_at... | New Class: TorchExportableModuleForImageTextLM
Dedicated wrapper for image-text language models:
- Purpose: Handles multimodal models that need inputs_embeds instead of input_ids
- Architecture: Automatically chooses HybridCache vs StaticCache based on model config
- Usage: Takes embeddings from vision en... | {
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"merged_at... | # What does this PR do?
This PR refactors `LlamaRotaryEmbedding` to make the initialization for the default `rope_type` more explicit, as suggested in issue #39753.
Instead of relying on the `ROPE_INIT_FUNCTIONS` dictionary for the default case, the code now uses a direct call to `_compute_default_rope_parameters... | {
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"merged_at... | # What does this PR do?
Adds `visualize_keypoint_matching` to LightGlue and SuperGlue image processor
Deprecate `plot_keypoint_matching` from LightGlue image processor
## Who can review?
@qubvel @stevhliu
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LLMs in `transformers serve` now accept `content` messages containing arrays, as [expected in the API](https://platform.openai.com/docs/api-reference/chat/create).
Adds tests to prevent regressions.
Example of a command that gets fixed in this PR:
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curl -X POST http://localhost... | {
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https://api.github.com/repos/huggingface/transformers/issues/39828 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39828/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39828/comments | https://api.github.com/repos/huggingface/transformers/issues/39828/events | https://github.com/huggingface/transformers/pull/39828 | 3,281,001,997 | PR_kwDOCUB6oc6hkLxc | 39,828 | fix test_working_of_tp failure of accelerate ut | {
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`accelerate` UT `pytest -rA tests/tp/test_tp.py::TPIntegrationTest::test_working_of_tp` failed w/ below log
> stderr: [rank0]: File "/usr/local/lib/python3.11/dist-packages/transformers/integrations/tensor_parallel.py", line 1082, in distribute_model
> stderr: [rank0]: tp_plan = getattr(model, "_... | {
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Version 1
We want to support defining different RoPE params within one model, similar to how layer types defines different attention patterns. The reason: some models are already using global and local rope params (Gemma3, ModernBert), and we were forced to do monkey patching to support it... | {
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This PR adds MetaCLIP 2 using modular. Alternative of #39821
It adapts `CLIPProcessor` to support any tokenizer using `AutoTokenizer`.
To do:
- [x] update integration test and convert remaining checkpoints
- [x] transfer checkpoints to the Meta org
Failing CI is unrelated | {
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Some imports were not properly guarded, so `transformers env` was failing on a base install. This PR fixes it.
Fixes #39779
Supercedes #39790 | {
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This PR enables `paged_attention` usage:
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model = AutoModelForCausalLM.from_prertained("path", attn_implementation="paged_attention|kernels-community/flash-attn3")
```
This means I want to use the `paged_attention` wrapper of `transformers` -> no attention mask, no input pre-proc... | {
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https://api.github.com/repos/huggingface/transformers/issues/39822 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39822/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39822/comments | https://api.github.com/repos/huggingface/transformers/issues/39822/events | https://github.com/huggingface/transformers/pull/39822 | 3,280,621,307 | PR_kwDOCUB6oc6hi4YU | 39,822 | chore: update DETR model card | {
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This PR updates the model card for DETR, following the template outlined in the issue.
## Before submitting
- [x] This PR improves the docs.
## Who can review?
@stevhliu
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https://api.github.com/repos/huggingface/transformers/issues/39821 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39821/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39821/comments | https://api.github.com/repos/huggingface/transformers/issues/39821/events | https://github.com/huggingface/transformers/pull/39821 | 3,280,524,873 | PR_kwDOCUB6oc6hijYj | 39,821 | Support MetaCLIP 2 | {
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Meta just released [MetaCLIP 2 (worldwide)](https://github.com/facebookresearch/MetaCLIP?tab=readme-ov-file#pre-trained-models), new CLIP models trained on 300+ languages.
However, when making them compatible with `modeling_clip.py`, I noticed there's a mistake with the original OpenAI CLI... | null | {
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https://api.github.com/repos/huggingface/transformers/issues/39819 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39819/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39819/comments | https://api.github.com/repos/huggingface/transformers/issues/39819/events | https://github.com/huggingface/transformers/pull/39819 | 3,280,316,405 | PR_kwDOCUB6oc6hh1ZL | 39,819 | Fix bad markdown links | {
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"merged_at... | # What does this PR do?
While writing the docs for one model and taking inspiration from another, I noticed bad links to other models.
For example, with [Dia](https://github.com/huggingface/transformers/blob/6ba8a1ff4550b4450a22a0b0d907312955ce0fd5/docs/source/en/model_doc/dia.md?plain=1#L36C1-L37C41), its markdo... | {
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https://api.github.com/repos/huggingface/transformers/issues/39818 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39818/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39818/comments | https://api.github.com/repos/huggingface/transformers/issues/39818/events | https://github.com/huggingface/transformers/issues/39818 | 3,280,308,340 | I_kwDOCUB6oc7DhYh0 | 39,818 | Qwen2-VL err | {
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```
[rank0]: Traceback (most recent call last):
[rank0]: File "/home/rupert/qwen2.5-v... | {
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https://api.github.com/repos/huggingface/transformers/issues/39817 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39817/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39817/comments | https://api.github.com/repos/huggingface/transformers/issues/39817/events | https://github.com/huggingface/transformers/pull/39817 | 3,280,063,386 | PR_kwDOCUB6oc6hhACa | 39,817 | Update documentation for Cohere2Vision models | {
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"merged_at... | # What does this PR do?
Update the documentation to include an example of using Cohere Command A Vision in a pipeline, and add it to the list of vision models.
## 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?
@z... | {
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https://api.github.com/repos/huggingface/transformers/issues/39816 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39816/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39816/comments | https://api.github.com/repos/huggingface/transformers/issues/39816/events | https://github.com/huggingface/transformers/pull/39816 | 3,279,979,046 | PR_kwDOCUB6oc6hgt1y | 39,816 | Refactor ViT-like models | {
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"merged_at... | # What does this PR do?
Refactor ViT and dependent models to use `@check_model_inputs` and `@can_return_tuple` decorator to remove all the logic for intermediate `hidden_states` and `attentions` capture
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"merged_at... | # What does this PR do?
As discussed internally, we don't have tests for chat templates loading-pushing to hub and a few bugs were encountered recently
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https://api.github.com/repos/huggingface/transformers/issues/39814 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39814/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39814/comments | https://api.github.com/repos/huggingface/transformers/issues/39814/events | https://github.com/huggingface/transformers/issues/39814 | 3,279,751,841 | I_kwDOCUB6oc7DfQqh | 39,814 | Flash Attention fails with non aligned position_ids | {
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- `transformers` version: 4.54.1
- Platform: Linux-6.1.123+-x86_64-with-glibc2.39
- Python version: 3.12.3
- 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.... | {
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https://api.github.com/repos/huggingface/transformers/issues/39813 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39813/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39813/comments | https://api.github.com/repos/huggingface/transformers/issues/39813/events | https://github.com/huggingface/transformers/pull/39813 | 3,279,670,512 | PR_kwDOCUB6oc6hfqkX | 39,813 | [docs] fix korean docs yet again | {
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"merged_at... | # What does this PR do?
Something went wrong merging main into #39660 , and CI is still red.
`doc-builder build transformers docs/source/ko/ --language ko --clean` is green on my side. | {
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https://api.github.com/repos/huggingface/transformers/issues/39812 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39812/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39812/comments | https://api.github.com/repos/huggingface/transformers/issues/39812/events | https://github.com/huggingface/transformers/issues/39812 | 3,279,629,710 | I_kwDOCUB6oc7Dey2O | 39,812 | Why `lm-head` weight still exists with `"tie_word_embeddings": true` | {
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When I was directly loading the `model.safetetensors` file from qwen3-0.6b, I find that there is a weight stored with name "lm_head.weight", but the `config.json` shows `"tie_word_embeddings": true`.
So what EXACTLY does the tie word embedding do? I can't find it anywhere...
### Who can help?
@Arthur... | {
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Copy-and-paste the text below in your GitHub issue and FILL OUT the two last points.
- `transformers` version: 4.53.2
- Platform: Linux-4.19.90-vhulk2211.3.0.h1543.eulerosv2r10.aarch64-aarch64-with-glibc2.35
- Python version: 3.11.13
- Huggingface_hub version: 0.34.3
- Safetensors version: 0.5.3
- Acce... | {
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Add new model
A few unrelated but needed changes:
- Cache in multi-GPU wasn't working, needed to fix `layer_device_map` and `model.get_decoder()`
- The token isn't passed when downloading additional chat templates
- The new `check_outputs` don't work with VLMs because we don't know what... | {
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## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
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Translated the `gpt2.md` file of the documentation to Korean.
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Translated the `bamba.md` file of the documentation to Korean.
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Enable SIM rules of ruff, except those for code styles. | {
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| key | value |
| -------------------- | ----------- |
| transformers version | 4.53.3 |
| PyTorch version | 2.7.1 |
| PyTorch_npu version | 2.7.1 |
| deepspeed version | 0.17.2 |
| NPU | ascend 910b |
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| transformers version | 4.53.3 |
| PyTorch version | 2.7.1 |
| PyTorch_npu version | 2.7.1 |
| deepspeed version | 0.17.2 |
| NPU | ascend 910b*8 |
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In current qwen 2.5 VL implementation, if you mask out one item in a batch, then in the rope calculation you get
```
llm_positions = torch.cat(llm_pos_ids_list, dim=1).reshape(3, -1)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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_prepare_cache_for_generation
raise ValueError(
ValueError: This model does not support cache_implementation='static'. Please check the following issue: https://github.com/huggingface/transformers/issues/28981
I got this error and i have no clue of how to solve it. I tried different implementation... | {
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Add [EdgeTAM](https://github.com/facebookresearch/EdgeTAM)
Largely based on Sam2 with modular | {
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- `transformers` version: 4.54.1
- Platform: Windows-10-10.0.26100-SP0
- Python version: 3.10.11
- 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+cpu (N... | {
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Big simplifications everywhere, but most notably:
- all caches are initialized lazily -> no more issues of devices with device_map, which would lead to breaking the Static dynamo addresses due to device movement + no issue of dimensions with TP + much simpler to prepare for `generate` (all... | {
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"merged_at... | # What does this PR do?
⚠️ TODO before merging: after settling on the design, update pipeline usage in model docs accordingly.
This PR standardizes `text-to-audio` such that the following lines work with most* text-to-audio models:
```py
from transformers import pipeline
synthesiser = pipeline("text-to-aud... | null | {
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- `transformers` version: 4.54.0
- Platform: Linux-5.14.0-284.73.1.el9_2.x86_64-x86_64-with-glibc2.35
- Python version: 3.10.13
- Huggingface_hub version: 0.34.1
- Safetensors version: 0.5.3
- Accelerate version: 1.9.0
- Accelerate config: not found
- DeepSpeed version: not installed
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This PR fixes a bug in ProphetNet where passing `encoder_outputs` as a tuple to `forward()` would raise:
`AttributeError: 'tuple' object has no attribute 'last_hidden_state'`
This happens because the `forward()` method assumes `encoder_outputs` is a `BaseModelOutput` when provided manually, while the docstring... | null | {
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1. Fix DAC conversion:
- Most notably, performing weight norm removal on GPU instead of on CPU (otherwise get differences for layers with weight norm when applying models on GPU)
- Missing feature extractor parameters
- Correctly casting sampling rate
2. More consistent add/remove weight... | null | {
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This PR fixes an issue in the `transformers serve` functionality where the server could not handle chat messages with nested content (e.g., when the `content` field in a message was a list instead of a string or dictionary). The unhandled `TypeError` caused the server to crash instead of proces... | null | {
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## Bug Description
When using the `transformers serve` command to serve a model, it fails to process chat messages containing nested content, raising a `TypeError`. Specifically, when integrating the served model endpoint with a chat interface such as Gradio, and the messages sent have a nested struct... | {
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"merged_at... | ## What does this PR do?
Fixes [[#39779](https://github.com/huggingface/transformers/issues/39779)]:
`ModuleNotFoundError: No module named 'PIL'` when running `transformers env` (or any CLI command) after installing `transformers[torch]` in a fresh environment.
---
## Problem
This error occurs because:
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- Python version: 3.11.12
- Huggingface_hub version: 0.34.3
- Safetensors version: 0.5.3
- Accelerate version: 1.7.0
- Accelerate config: not found
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- PyTorch version (accelerator?): 2.7.1 (NA)
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Fixes https://github.com/huggingface/transformers/issues/39774.
As per title, if we are using the legacy `cache.key_cache[layer_idx]` a warning is emitted and fullgraph compilation breaks. This PR makes sure no warning are raised when using the models in core library | {
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This can create bugs since other parts of the code might try to access those attributes.
The call was added on https://github.com/huggingface/transformers/pull/39590 | {
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missing encoder states to intermediate states | null | {
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Add `skipped` and `errors` counts | {
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As per the title! Now that we are officially all-in on PyTorch, let's update the argument from `torch_dtype` to a simple `dtype` to be coherent with PyTorch and simplify!
Of course, it fully keeps BC for `torch_dtype` everywhere (with added tests to make sure), but it's already updated eve... | {
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This PR simplifies more `if` conditions and dict `get` code. The changes are part of efforts to finally enable `SIM` checks in `ruff`. | {
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- `transformers` version: 4.54.1
- Platform: Linux-6.11.0-17-generic-x86_64-with-glibc2.36
- Python version: 3.13.5
- Huggingface_hub version: 0.34.3
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- `transformers` version: 4.54.1
- Platform: Linux-6.11.0-17-generic-x86_64-with-glibc2.36
- Python version: 3.13.5
- Huggingface_hub version: 0.34.3
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As per title, fixes https://github.com/huggingface/transformers/issues/39763 and ensures Sequence Classification model works with official checkpoints | {
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As per title. TBH the helper is same for most models (excluding Qwen or other special arch), so we could just move it to the base modeling class. I thought it's against transformers philosophy, so that's why we have near-same code copied everywhere
Half of these are anyway handled by modul... | {
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# BioGPT Implementation Bug Report
**Repository**: transformers
**Component**: `src/transformers/models/biogpt/modular_biogpt.py`
**Reporter**: SunnyThakur
**Date**: July 30, 2025
**Priority**: High
## Executive Summary
This report identifies critical runtime errors and implementation issue... | {
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my environment:
```
- `transformers` version: 4.54.1
- Platform: Linux-6.8.0-59-generic-x86_64-with-glibc2.39
- Python version: 3.12.11
- Huggingface_hub version: 0.34.3
- Safetensors version: 0.5.3
- Accelerate version: not installed
- Accelerate config: not found
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- ... | {
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transformers version: 4.55.0.dev0
Platform: Linux-6.11.0-28-generic-x86_64-with-glibc2.35
Python version: 3.11.13
Huggingface_hub version: 0.34.2
Safetensors version: 0.5.3
Accelerate version: 1.8.1
Accelerate config: not found
DeepSpeed version: not installed
PyTorch version (accelerator?): 2.9.0.dev2... | {
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"merged_at... | After the issue #39746 fixed, the vision encoder decoder model can support static cache and can got more significant speed-up
```python
import time
import requests
import torch
import PIL.Image
from transformers import pipeline
model_id = "nlpconnect/vit-gpt2-image-captioning"
image_to_text = pipeline("imag... | {
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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.
Then, please replace this w... | null | {
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https://api.github.com/repos/huggingface/transformers/issues/39770 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39770/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39770/comments | https://api.github.com/repos/huggingface/transformers/issues/39770/events | https://github.com/huggingface/transformers/pull/39770 | 3,275,209,122 | PR_kwDOCUB6oc6hQtD_ | 39,770 | [Bugfix] Fix `AutoModel.from_pretrained(..., quantization_config=None)` regression | {
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"merged_at... | ## Purpose ##
* Fix bug where passing `quantization_config=None` to `AutoModelForCausalLM` will lead to an error
```
Traceback (most recent call last):
File "/home/kyle/llm-compressor/asdf.py", line 2, in <module>
model = AutoModelForCausalLM.from_pretrained("RedHatAI/Meta-Llama-3.1-8B-Instruct-quantized.w4a... | null | {
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As per the title | {
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The goal of this PR is to start improving the benchmarking infrastructure of Transformers. In the short-term we'd like to build a dataset similar to what Diffusers did (https://huggingface.co/datasets/diffusers/benchmarks) and put a dashboard on Spaces.
This PR starts with the data acquisi... | {
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I am using vllm with serve running it using the following command
`vllm serve Qwen/Qwen2.5-7B-Instruct --tool-call-parser hermes --enable-auto-tool-choice`
When I use below curl
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curl --location 'http://localhost:8000/v1/chat/completions' \
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As per the title! | {
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This change is necessary to s... | {
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"merged_at... | Improves the Gemma3n model and tests by:
- Remove hardcoded number of layers in the activation sparsity init.
- Better explanation for layer reuse.
- Enable and update integration tests.
- Removing unused pan and scan configuration options from ImageProcessor.
- Skipping some incompatible tests. | {
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https://api.github.com/repos/huggingface/transformers/issues/39763 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39763/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39763/comments | https://api.github.com/repos/huggingface/transformers/issues/39763/events | https://github.com/huggingface/transformers/issues/39763 | 3,274,159,127 | I_kwDOCUB6oc7DJ7QX | 39,763 | Instantiating `google/gemma-3-4b-pt` with AutoModelForSequenceClassification Reports Unitialized Model | {
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I'm trying to use a Gemma3 model (non-instruction tuned) for a classification task. I was glad that I saw that the model seems to be supported in the current code for this task: https://github.com/huggingface/transformers/pull/39465
When trying
```
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This was detected by ruff. | {
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So tests like `tests/commands/test_serving.py` and `tests/utils/test_add_new_model_like.py` in the job `tests_non_model` could run.
This job uses `"huggingface/transformers-torch-light` which has `testing` in the docker file.
(see https://app.circleci.com/pipelines/github/huggingface/... | {
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https://api.github.com/repos/huggingface/transformers/issues/39760 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39760/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39760/comments | https://api.github.com/repos/huggingface/transformers/issues/39760/events | https://github.com/huggingface/transformers/pull/39760 | 3,273,924,678 | PR_kwDOCUB6oc6hMZeP | 39,760 | [Draft] Add Llasa TTS family of models | {
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This PR adds the Llasa TTS family of models:
- 1B: https://huggingface.co/HKUSTAudio/Llasa-1B
- 3B: https://huggingface.co/HKUSTAudio/Llasa-3B
- 8B: https://huggingface.co/HKUSTAudio/Llasa-8B
Reproducers for integration tests: https://gist.github.com/ebezzam/1863ec8eb7ec4afff02c26bdcb76... | null | {
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https://api.github.com/repos/huggingface/transformers/issues/39759 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39759/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39759/comments | https://api.github.com/repos/huggingface/transformers/issues/39759/events | https://github.com/huggingface/transformers/pull/39759 | 3,273,753,333 | PR_kwDOCUB6oc6hLz0H | 39,759 | Fix version issue in modeling_utils.py | {
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As per the title. `nn.RMSNorm` was added in torch 2.4, which created friction when calling the function. This fixes it by simply removing it from the `isinstance` check, as the name test is enough anyway and already covers it | {
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Avoid OOM when other tests are failing | {
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https://api.github.com/repos/huggingface/transformers/issues/39756 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39756/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39756/comments | https://api.github.com/repos/huggingface/transformers/issues/39756/events | https://github.com/huggingface/transformers/pull/39756 | 3,273,490,758 | PR_kwDOCUB6oc6hK6bf | 39,756 | Fix rope_deltas corruption in Qwen2.5VL during CFG generation | {
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"merged_at... | ## Summary
Fixes #39749
This PR addresses a critical issue where the `rope_deltas` attribute in Qwen2.5VL models gets corrupted during Classifier-Free Guidance (CFG) generation due to shared mutable state between forward passes.
**Problem**: During CFG generation, the model performs two forward passe... | null | {
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I would like to follow up on the status of the following issues. Both of these issues involve erroneous behavior that occurs when resuming from an interruption . One issue is that regardless of when training is interrupted at any given timestep, in most cases, a certain amount of data will be un-trained (http... | {
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Fixes https://github.com/huggingface/transformers/issues/39746 | {
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https://github.com/huggingface/transformers/blob/95faabf0a6cd845f4c5548697e288a... | null | {
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As discussed with infra team | {
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# What does this PR do?
Translated the `<your_file>.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 ... | null | {
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Fixes https://github.com/huggingface/transformers/issues/39747
Two issues:
- The attention setting fn apparently was renamed afetrwards, but ModernBert had it overwritten and started to fail.
- The RoPE theta is different for global and local attentions, and is already being updated in h... | {
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transformers 4.49.0
### 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, ...)
- [x] My own task or dataset (give details below)
... | {
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Paged attention was broken because it is not layered yet! Needs to be in the patch! | {
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transformers 4.54.0
### Who can help?
@zucchini-nlp @ArthurZucker
### details
Regarding PR #38974, it modifies the model's default attention initialization behavior.
Referring to the ModernBERT code:
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- `transformers` version: 4.55.0.dev0
- Platform: Linux-6.11.0-28-generic-x86_64-with-glibc2.35
- Python version: 3.11.13
- Huggingface_hub version: 0.34.2
- Safetensors version: 0.5.3
- Accelerate version: 1.8.1
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (ac... | {
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"merged_at... | # What does this PR do?
I find Pylance in VSCode cannot import the `Gemma3NForConditionalGeneration` and `Qwen2_5OmniModel` automatically. The reason is that these symbols are not exported for type checking. When running in lazy import mode, this symbols will not be exported and thus no type hint.
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transformers main branch
### 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)
### Reprodu... | {
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The change ensures that the audio encodings are cast to the same type as `conv.weight` tensor. This is done by appending `to(self.conv.weight.dtype)` to the `audio_encodings_padded` rvalue.
Fixes an issue where the conv2d forward pass throws an error. Code for reproducible error (run on ... | {
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"merged_at... | # What does this PR do?
This PR updates the HuBERT model card to comply with the format introduced 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).
## Who can review?
@stevhliu
## Notes
- I did not include the **Attentio... | {
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"merged_at... | # What does this PR do?
This PR updates `HfArgumentParser` to filter out dict types from `Union` annotations. This prevents runtime errors with argparse, which does not support parsing arguments as dicts. Previous work (PR #39467) reordered `Union[str, dict]` to `Union[dict, str]` throughout the codebase, but this a... | null | {
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https://api.github.com/repos/huggingface/transformers/issues/39740 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39740/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39740/comments | https://api.github.com/repos/huggingface/transformers/issues/39740/events | https://github.com/huggingface/transformers/pull/39740 | 3,271,128,166 | PR_kwDOCUB6oc6hC5ev | 39,740 | [Tests] [Bugfix] Make weights tied for `dynamic_tied_weights` test | {
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"merged_at... | ## Background ##
* When I added this test, I neglected to actually tie the weights
## Purpose ##
* The purpose of `test_save_offloaded_model_dynamic_tied_weights_keys` is to test the case when tied weights are dynamically added. While the test achieved its original goal of testing https://github.com/huggingface/tr... | null | {
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"merged_at... | As the title says.
Cc @zucchini-nlp as I think you reviewed these models?
Also it would be great to have fast image processors on release for the newest models, don't hesitate to ping me on the PRs, happy to help! | {
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https://api.github.com/repos/huggingface/transformers/issues/39738 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39738/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39738/comments | https://api.github.com/repos/huggingface/transformers/issues/39738/events | https://github.com/huggingface/transformers/pull/39738 | 3,270,778,225 | PR_kwDOCUB6oc6hBsaM | 39,738 | Standardize CLAP model card format | {
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"merged_at... | # What does this PR do?
This PR updates the CLAP model card to follow the standardized format as requested 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 you read t... | {
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