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https://api.github.com/repos/huggingface/transformers/issues/40640 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/40640/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/40640/comments | https://api.github.com/repos/huggingface/transformers/issues/40640/events | https://github.com/huggingface/transformers/pull/40640 | 3,378,629,556 | PR_kwDOCUB6oc6mln9q | 40,640 | Resume training by trained samples to avoid elastic job loss or over-reading of data. | {
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Resume training by trained samples. Then we can avoid reading more or less data due to changes in the number of workers.
Fixes: #40245
## 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 [c... | null | {
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Add DeepseekV3ForTokenClassificaiton for using as a value model.
### Motivation
In verl, they use AutoModelForTokenClassification for loading value model.
https://github.com/volcengine/verl/blob/2d6c6dbb39bf846d4ebf98c89fc5b4f49c37dd3d/verl/utils/model.py#L627
so I want to add this for using tran... | {
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"merged_at... | The dtype in the pipeline does not work if I don't pass device_map. To reproduce the error:
```python
from transformers import pipeline
import torch
image_to_text = pipeline(
"image-feature-extraction",
model="google/vit-base-patch16-224-in21k",
dtype=torch.bfloat16,
)
print(ima... | {
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This PR introduces inference support for the openPangu-Embedded model. By integrating the inference implementation directly into the Transformers library, we aim to ensure seamless compatibility and enable continuous updates alongside future open-source releases.
This implementation requir... | null | {
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Even more test data cached | {
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- `transformers` version: 4.55.4
- Platform: Linux-6.1.123+-x86_64-with-glibc2.35
- Python version: 3.12.11
- Huggingface_hub version: 0.34.4
- Safetensors version: 0.6.2
- Accelerate version: 1.10.1
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (accelerator?): 2.... | {
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Enable ruff on benchmark and scripts | {
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The `CausalLMModelTest` mixin has RoPE tests, but it requires setting `rotary_embedding_layer` in each model tester. In most models, it was unset, so they were not running RoPE-related tests -- exposing ourselves to easily preventable issues like https://github.com/huggingface/transformers/is... | {
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Checked offline with other team members. Its not used in any big downstream library | {
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passing the mode to kernelize to fix : https://github.com/huggingface/transformers/issues/40459 | {
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Fix more typos.
## 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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This pr changes the |= to use the torch.logical_or operator which is supported by other backends like Onnx and Tensorrt.
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Same as https://github.com/huggingface/transformers/pull/40259 with updates. Can't push to the prev PR, prob the contributors didn't allow maintainer edits
I just did polishing on top of existing PR and added modular file. Should be ready for review | {
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We have for this test the following error (flaky)
> requests.exceptions.HTTPError: 429 Client Error: Too Many Requests for url: https://huggingface.co/api/models/hf-internal-testing/namespace-mistralai-repo_name-Mistral-Small-3.1-24B-Instruct-2503/tree/main
This PR just try to cache the... | {
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This PR #36682 introduced the batch size for images, everything is working correctly but the check for image existence don't support the PPIL images. The `len()` function could work with path or other things. So I converted it to check `is not None` it works for both PIL images and paths or U... | {
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This is a feature proposal to extend GGUF support in `transformers` for several Korean-specific LLM architectures that have recently been released on the Hugging Face Hub.
Reference issue: [Community contribution: Adding GGUF support for more architectures](https://github.com/huggingface/transform... | null | {
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I'm trying to use function/tool calling with gpt-oss while streaming responses using transformers serve.
When I generate a normal chat completion without triggering functions, everything works fine.
However, if I try to get a function/tool call, the response contains only two empty chunks and nothing ... | {
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* Ensured that the `attention_mask` is always checked for causality before being added to the buffer, and that this validation is performed only once for performance.
* Modified the logic so that the `attention_mask` is appended to buffers only after successful validation, preventing non-cau... | {
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Fix this flaky test which has
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> torch.testing.assert_close(result.aux_loss.cpu(), torch.tensor(2, dtype=torch.float32), rtol=1e-2, atol=1e-2)
E AssertionError: Scalars are not close!
```
Running 10000 times and all pass.
Also makes this much much faster by redu... | {
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Users can create an `Accelerator` instance and optionally pass this through to the `Trainer`, which should then handle further postprocessing based on the state of the object.
### Motivation
In the base `Trainer` class, the call to `create_accelerator_and_postprocess` creates the `Accelerator` in... | null | {
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This test uses `huggingface_hub's Repository` which doesn't have any cache mechanism, so from time to time we get `The requested URL returned error: 429` (`too many requests`) error.
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FAILED tests/models/auto/test_modeling_auto.py::AutoModelTest::test_dynamic_saving_from_local_repo... | {
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As er title, the slow tests in gemma3 were failing and the cause of issue is an incorrect indentation. We need to add exactly one sublist of images per batch, but the current code was treating each conversation turn as a new batch
Fixed and added a fast test as well | {
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In #36818, we tried to make tokenization tests faster by caching the objects (tokenizers). Despite we set the `maxsize=64` for `lru_cache`, many objects still live for much longer time than necessary, say `BertTokenizationTest` finished all of its tests but continue to live in the `lru_cache`... | {
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- Fix issue witnessed in https://github.com/huggingface/transformers/issues/37474: when using >1 GPU, the loss does not get normalized correctly
- Cause: each GPUs sees num_items_in_batch = cst = total number of tokens (instead of total number of tokens / n_gpus)
- Fix: adjust num_items_in_batch to be set to... | {
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https://github.com/huggingface/transformers/pull/39501 . It forgot to transpose the router_scores before applying it to routed_in, causing Llama4 to generate garbage output.
This PR fixes that issue by adding back the transpose() and adding some comments explaining why the tran... | {
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if True:
from unsloth import FastLanguageModel
model, tokenizer = FastLanguageModel.from_pretrained(
model_name = "model", # YOUR MODEL YOU USED FOR TRAINING
max_seq_length = 1024,
dtype = None,
load_in_4bit = True,
)
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Use `functools.cached_property` rather than the shipped one. | {
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https://api.github.com/repos/huggingface/transformers/issues/40606 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/40606/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/40606/comments | https://api.github.com/repos/huggingface/transformers/issues/40606/events | https://github.com/huggingface/transformers/issues/40606 | 3,374,256,950 | I_kwDOCUB6oc7JHxM2 | 40,606 | GPT-OSS attention backends available for SM120 other than Eager? | {
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https://api.github.com/repos/huggingface/transformers/issues/40605 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/40605/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/40605/comments | https://api.github.com/repos/huggingface/transformers/issues/40605/events | https://github.com/huggingface/transformers/pull/40605 | 3,374,208,449 | PR_kwDOCUB6oc6mXNAf | 40,605 | Fix arguments | {
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This PR fixes argument issues found by pyright, it also contains other tiny fixes.
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pillow is required to >= 10.0.1 in setup.py . | {
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```
- `transformers` version: 4.57.0.dev0
- Platform: Linux-5.15.0-1055-aws-x86_64-with-glibc2.39
- Python version: 3.12.3
- Huggingface_hub version: 0.34.4
- Safetensors version: 0.5.3
- Accelerate version: 1.7.0
- Accelerate config: not found
- DeepSpeed version: not installed
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- Implement fast processor for PromptDepthAnything, following request in https://github.com/huggingface/transformers/issues/36978
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- Add a **temporary file** (to be deleted before merging) to run additional test and g... | {
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Currently, `transformers.Trainer` allows a custom `compute_loss_func` function to be passed as a trainer argument. However, this user defined loss is only accessed in the case when labels is not None. I think that this hidden dependency is counter-intuitive. User defined loss functions should take ... | {
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Guided by: @PavloFesenko
# What does this PR do?
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FAILED tests/models/internvl/test_processing_internvl.py::InternVLProcessorTest::test_apply_chat_template_video_frame_sa... | {
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With the `@check_model_inputs` decorator, we no longer check and fallback to the `eager` attention in the Attention module's code, let's notify users to set proper attention implementation. Otherwise, we are silently getting `None` attentions even if we specify `output_attentions=True` (becau... | {
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Reduce more test data fetch:
- less connection errors
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We no longer need it. Initially, this was introduced to pass the proper `attn_implementation`, but since we are no longer passing it, we can initialize directly from the class constructor.
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We really have to review this test in general, but let's just skip this for now. | {
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cc @zucchini-nlp | {
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Make AMD happy | {
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This PR standardizes the **ConvNeXt V2 model card** to match the Hugging Face model card template described in [#36979](https://github.com/huggingface/transformers/issues/36979).
### Changes
- Added standardized **header and badges**.
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https://api.github.com/repos/huggingface/transformers/issues/40588 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/40588/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/40588/comments | https://api.github.com/repos/huggingface/transformers/issues/40588/events | https://github.com/huggingface/transformers/pull/40588 | 3,372,022,030 | PR_kwDOCUB6oc6mQDfR | 40,588 | Fix llava image processor | {
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Fixes https://github.com/huggingface/transformers/issues/40577. Llava next image processor fails when `do_pad=False` because the variable was not assigned | {
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https://api.github.com/repos/huggingface/transformers/issues/40587 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/40587/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/40587/comments | https://api.github.com/repos/huggingface/transformers/issues/40587/events | https://github.com/huggingface/transformers/pull/40587 | 3,371,864,776 | PR_kwDOCUB6oc6mPhee | 40,587 | feat(utils): add vision utils for embedding images and getting the hidden size | {
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Adds generic utilities to understand the hidden size of an image encoder (currently need to write complex logic), and generically encode images using an image encoder.
Fixes #40457
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks ... | null | {
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The intent of this PR is to allow custom CALLABLE generation modes (that reuse generate's preparation step) to define their own parameters.
To do this, we need to inspect the signature and remove those parameters before `validate_model_kwargs`.
So to do this, we need some notion of `g... | {
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Fix more typos. | {
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This test is very flaky for dtype bf16 for 3 reasons:
- `bf16` has bad precision, especially when the magnitude is large
- siglip has larger outputs (than llama, clip, for example). The maximal abs. values for them:
- siglip: 3.0~4.0
- clip: 0.9 ~ 1.0
- llama: ~0.1
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This PR introduces an optimization that significantly accelerates the Mixture-of-Experts (MoE) layer computations in the `DeepseekV3` model by integrating the `grouped_gemm` library. This enhances performance for both training and inference.
The original MoE implementation processed expert n... | null | {
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This is a proposal to integrate an optimized Mixture-of-Experts (MoE) forward pass for the `DeepseekV3` model using the `grouped_gemm` library. This new implementation significantly accelerates MoE computations by replacing the iterative execution over experts with a single, batched kernel call.
T... | null | {
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This PR fixes `test_eager_matches_sdpa_inference` not run for `CLIP` after #37498.
#37498 changed `tests/models/clip/test_modeling_clip.py` from
```python
def test_eager_matches_sdpa_inference(self, torch_dtype: str):
super().test_eager_matches_sdpa_inference(
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https://api.github.com/repos/huggingface/transformers/issues/40580 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/40580/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/40580/comments | https://api.github.com/repos/huggingface/transformers/issues/40580/events | https://github.com/huggingface/transformers/pull/40580 | 3,370,841,177 | PR_kwDOCUB6oc6mMG-i | 40,580 | Fix inexistent imports | {
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Fix inexistent imports in `src/transformers/__init__.py` | {
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https://api.github.com/repos/huggingface/transformers/issues/40579 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/40579/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/40579/comments | https://api.github.com/repos/huggingface/transformers/issues/40579/events | https://github.com/huggingface/transformers/pull/40579 | 3,370,800,479 | PR_kwDOCUB6oc6mL-YK | 40,579 | Enable more ruff UP rules | {
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Fix and enable remaining `ruff` rules.
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This PR updates the model-card for the SAM (Segment Anything Model) model, as described in this [issue](https://github.com/huggingface/transformers/issues/36979), in an attempt to standardize all model-cards.
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```
if do_pad:
processed_images = self._pad_for_batching(new_images)
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Add ko translation for `docs/source/en/jan.md`.
## Changes
- Add ko translation: `docs/source/ko/jan.md`
- Original file: `docs/source/en/jan.md`
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As suggested in this issue - https://github.com/huggingface/transformers/issues/36979#issue-2947704577 - this PR updates the documentation of the [VideoMAE](https://huggingface.co/docs/transformers/v4.56.0/en/model_doc/videomae#overview) model, which will now be aligned with the standardized ... | {
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Docker image python:3.9
It works for transformers 4.22.0 correctly, but not 4.21.0-3.
### Who can help?
@ArthurZucker and @itazap
### Information
- [x] The official example scripts
- [ ] My own modified scripts
### Tasks
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- `transformers` version: 4.56.0
- Platform: Linux-6.6.87.2-microsoft-standard-WSL2-x86_64-with-glibc2.35
- Python version: 3.10.12
- Huggingface_hub version: 0.34.4
- Safetensors version: 0.6.2
- Accelerate version: 1.10.1
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch ... | {
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Currently onnxruntime > 4 is required. | {
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Same as #40530 | {
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"merged_at... | # What does this PR do?
The new model support for MetaCLIP 2 is done, but the documentation is with the wrong links and wrong model names.
The issue is already mentioned by @howardhsu in https://github.com/huggingface/transformers/issues/39826#issuecomment-3221359417_
> just realized the example code in the docu... | {
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- **transformers version**: 4.53
- **Python version**: 3.12
- **Platform**: Linux
- **Models affected**: google/gemma-3-12b-it (confirmed), likely affects other models
- **Training setup**: torchrun with DeepSpeed, LoRA fine-tuning
## Description
The HuggingFace Trainer exhibits incorrect loss scalin... | {
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https://api.github.com/repos/huggingface/transformers/issues/40563 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/40563/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/40563/comments | https://api.github.com/repos/huggingface/transformers/issues/40563/events | https://github.com/huggingface/transformers/pull/40563 | 3,369,113,636 | PR_kwDOCUB6oc6mGwjQ | 40,563 | fix to get output of intermediate output of dinov3 for more use case | {
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"merged_at... | # What does this PR do?
@qubvel @yonigozlan Can anyone review this simple PR?
since DINOv3 has alot of use case the output format should be enables to return intermediate hidden_states.
Fixes # (issue)
## Before submitting
- [X] This PR fixes a typo or improves the docs (you can dismiss the other checks if... | null | {
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"merged_at... | # What does this PR do?
Add Gemma3TextForSequenceClassification for Gemma3 small text 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 #40554
## Before submitting
- [ ] This PR... | {
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Avoid failures due to https://github.com/pytest-dev/pytest-rerunfailures/issues/303 | {
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- `transformers` version: 4.55.4
- Platform: macOS-15.6.1-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 (NA)... | {
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### System info
transformers==4.56.0, Python 3.12.11, Linux (pip install)
I encountered this problem when using the latest version
`RuntimeError: Type resolution failed for <class '__main__.TrainingArguments'>. Try declaring the class in global scope or removing line of from __future__ import annotatio... | {
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# What does this PR do?
Translated the `code_llama.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 f... | {
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As per the title, unbloating the following methods to remove `output_*` arguments that have no sense for these methods.
As a bonus: updating snippets to use `load_image` function instead of PIL + requests | {
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While #39465 added support for larger Gemma 3 (4b parameters or more) via `Gemma3ForSequenceClassification`, it did not add a `Gemma3TextForSequenceClassification` as for example proposed in https://github.com/huggingface/transformers/issues/36755#issuecomment-2929098303. However this is necessary ... | {
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This PR (🔴 = BC breaking):
1. Adds `config.get_sub_config()`. This function is an upgrade to `get_text_config`:
a. Allows model-agnostic extraction of different modalities in a single function, future-proofing its uses;
b. Uses heuristics to determine correct encoder/decoder and modal... | {
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No idea why pytest have exit code 0 in this case. Just adding a new step to check the content of `tests_output.txt` to see if there is any `crashed and worker restarting disabled` and fails that step instead if any. | {
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This test is flaky:
- the eps needs to be set to 1.0 to avoid large difference
- but even with this, we still get something > 5e-5 from time to time on CPU. On GPU, they are all very small , around 1e-9.
- no idea and just increate the atol/rtol to 1e-4 | {
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When initializing gpt-oss model, we would receive the following warning when it shouldn't be the case.
`config.rope_scaling['original_max_position_embeddings'], the pre-yarn context length, is unset. We will **assume** config.max_position_embeddings holds the pre-yarn context length. Some... | {
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As per the title. For the following test:
```
pytest tests/models -k test_flash_attn_2_inference_equivalence
```
On main:
```
177 failed, 195 passed, 546 skipped
```
On this PR:
```
96 failed, 305 passed, 517 skipped
```
So it's far from perfect but still paves the way f... | {
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"merged_at... | # What does this PR do?
Merge the model from https://github.com/microsoft/VibeVoice/tree/main
HF:
https://huggingface.co/microsoft/VibeVoice-1.5B | null | {
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"merged_at... | The indices has been masked by `0`, but the `0` will be recognized as `experts[0]`. We need a new class specific for masking
I run gpt-oss with EP=2, and found both rank0 and rank1 computed expert 0
<img width="800" height="250" alt="image" src="https://github.com/user-attachments/assets/3c2f40b7-9852-4118-9356-39c... | {
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Need to pin greater or equal and smaller | {
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Mark TVP image processor test flaky, It fails a lot under PRs currently. cc @yonigozlan to investigate when you have time | {
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As per the title. This started to be quite complicated and convoluted to follow how `attn_implementation` are dispatched. This should simplify a bit
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