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`MllamaModel` does not allow users to pass `pixel_values` and `inputs_embeds` simultaneously:
https://github.com/huggingface/transformers/blob/54cd86708d2b63a1f696ee1c59384a2f04100f57/src/transformers/models/mllama/modeling_mllama.py#L1702-L1705
However, commenting out those lines and running the ... | {
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So they can trigger a CI by leaving a comment on a PR. | {
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I am currently having the latest package install.
torch 2.6.0+cu124
transformers 4.51.3
sentence-transformers 4.1.0
### Who can help?
_No response_
### Information
- [ ] The official example scripts
- [ ] My own modified scripts
### Tasks
- [ ] An officially supported task in the `examples` folde... | {
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"merged_at... | # What does this PR do?
Adds a few minor improvements:
- `<think>` and `</think>` are now printed in the chat session. More generally, any pattern matching `<word_maybe_with_underscores>` (with optional `/` at the start of the word) should now be printed. Note that tokenizer decoding in `chat` skips special tokens ... | {
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"merged_at... | The comment in the test describes pretty well what the issue is:
```
# Flex attention relies on triton on compilation
# However, triton cannot handle hidden dimensions of less than 16
# --> forcing at least a hidden dim of 16
```
Flex attention tests were failing because triton needs bigger hidden dimensions to w... | {
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1. adds **MuP** **multipliers** in the fwd pass of the **slow path** `torch_forward`
2. Fixes the **repeat pattern** in **Mamba heads** , `repeat` **->** `repeat_interleave` see https://github.com/huggingface/transformers/pull/37533
@ArthurZucker
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In the constants [file](https://github.com/huggingface/transformers/blob/main/src/transformers/utils/constants.py) used for image pre-processing for CLIP, SigLIP, SigLip 2 etc. there are 2 default/standard values defined:
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IMAGENET_DEFAULT_MEAN = [0.485, 0.456, 0.406]
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I forgot to change a few more things weren't changed in previous PRs. Specifically:
- Attention refactor of Qwen and Persimmon (for Fuyu)
- The helper `get_image_features` has to return images of certain shape and format. May be breaking and we had the helper as public prev 🙈
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#38232 (follow-through of the deprecation of `forced_decoder_ids`) killed TF/FLAX generation, this PR fixes it :)
failures from the daily CI are now passing, e.g.
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CUDA_VISIBLE_DEVICES="" py.test tests/models/bart/test_modeling_tf_bart.py::TFBartModelTest::test_pipeline_text2text_gene... | {
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`run_slow` was renamed to `slow` | {
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- `transformers` version: 4.52.3
- Platform: Linux-6.8.0-59-generic-x86_64-with-glibc2.39
- Python version: 3.12.2
- Huggingface_hub version: 0.31.4
- Safetensors version: 0.4.3
- Accelerate version: 0.30.1
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (GPU?): 2.... | {
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Integrated the LagKV for KV compression.
https://github.com/AI-Lab-China-Merchants-Bank/LagKV
### Motivation
Right now, the Cache utils is expanding rapidly. But, it still lack an efficient token eviction algorithm except SinkCache and SlidingWindowCache, which show limited performance in inform... | null | {
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For Janus Processor Tests we are importing `CHAT_TEMPLATE` from conversion which is not ideal. Hence this PR fixes that issue.
Fixes #38270
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"merged_at... | Updates a few models to use the new `GradientCheckpointingLayer`. The models changed in this PR are leveraged by IBM model architectures (granite vision / bamba) or share code, either directly or through modular. Happy to submit a follow-up with other models too if that would be helpful!
Updated models:
- jamba
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from transformers import AutoModelForTimeSeriesPrediction
```
This class will be the portal to all time series models in Hugging Face.
It is a missing part of #34082 and this PR aims to fix it.
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"merged_at... | # What does this PR do?
As suggested in this issue - https://github.com/huggingface/transformers/issues/36979#issuecomment-2902300855 - this PR rewrites the altCLIP model card so it matches the standardized template that @stevhliu introduced in #36979.
Key points:
- Friend-style overview + sidebar badges.
- <... | {
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# What does this PR do?
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When calling a `custom_generate` method, don't forwards the following `generate` arguments: `custom_generate` and `trust_remote_code`.
This is done to enable naive pre/post processing extensions to the original `generate`, i.e. a custom generate doing:
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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 [ViTMAE](https://huggingface.co/docs/transformers/v4.52.1/en/model_doc/vit_mae) model, which will now be aligned with the standardized format for a... | {
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"merged_at... | Keeping track of the models that are done:
- [x] Bert
- [x] Roberta
- [x] Albert
- [x] Data2VecText
- [x] Xmod
- [x] Electra
- [x] XLM Roberta
- [x] Roberta Prelayernorm
- [x] Ernie
- [x] Camembert
- [x] Bert Generation
- [x] XLM Robert XL
- [x] RoCBert
- [x] Mobile Bert
Up to discussion:
- Fla... | {
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Question: Are there plans from Google or Huggingface to implement Gemma 3n in other frameworks?
I've seen the LiteRT weights and Android App Link on Huggingface, and was wandering if it would be possible to convert the model architecture in the *.task file to a transformer pytorch Module?
Perso... | {
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As per the title!
It aligns HybridChunkedCache on what was done in https://github.com/huggingface/transformers/pull/37972 (i.e. simply take the min between max_len and window), which was causing lengths mismatches with llama4 in `get_mask_sizes` with the default HybridChunkedCache!
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Create and upload new test failure reports for all CI jobs | {
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Fixes https://github.com/huggingface/transformers/issues/38121 and updates the weights on the hub. Note, hub PR is not yet merged | {
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Fix issue where kwargs given to `from_pretrained` for processors would not be taken into account in the processor's `__init__` directly, but would override the processor's attributes after the fact, resulting in unexpected behaviors.
This might be slightly breaking, as before the kwargs, a... | {
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As per the title. It got fixed in https://github.com/huggingface/transformers/pull/38080 in the middle of https://github.com/huggingface/transformers/pull/37866/. This PR corrects the additional mask. See images for correctness for both sliding and full cases.
Before https://github.com/huggi... | {
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This PR fixes an issue when the torch distributed is already initialized. current_device is referenced before assignment.
Getting the following traceback in accelerate when testing tp training.
```
[rank1]: tp_plan, device_map, device_mesh = initialize_tensor_parallelism(tp_plan, t... | {
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4.52.2
```
inference.sh: failed to run task: Unexpected type in sourceless builder transformers.models.gemma3.configuration_gemma3.Gemma3TextConfig
from user code:
File "/app/venv/3.12/lib/python3.12/site-packages/transformers/models/gemma3/modeling_gemma3.py", line 1345, in forward
outputs = ... | {
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As discussed offline | {
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>>> import transformers
>>> print(transformers.__version__)
4.52.2
### Who can help?
_No response_
### Information
- [ ] The official example scripts
- [ ] My own modified scripts
### Tasks
- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or ... | {
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"merged_at... | Scaling has been applied twice to OPT. This fixes it by passing `1.0` explicitly to avoid sdpa and co. to create a default scaling.
Fixes #38277 | {
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I am encountering a persistent issue when trying to use the Inference API for the 'gpt2' model, consistently receiving an HTTP 401 Unauthorized error with the message: {"error": "Invalid credentials in Authorization header"}.
I have been trying to set up an API connection from my Bubble application, bu... | {
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"merged_at... | # What does this PR do?
this is aligned with our roadmap to reduce the bloating, this allows us to remove codepaths for warning:
<img width="1116" alt="image" src="https://github.com/user-attachments/assets/cd1d9480-667a-48bd-941c-f57f54442799" />
Instead of having it in all of the forwards | {
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"merged_at... | # Resolve DTensor Import Path Inconsistency Across PyTorch Versions
Summary:
This pull request addresses an import issue for DTensor arising from its path change across different PyTorch versions. It implements a conditional import mechanism to ensure compatibility.
Problem:
The location of the DTensor module h... | {
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This PR adds a small util that lets us perform CI runs locally with report generation as it happens during the prod run. This is used for debugging purposes and for debugging new hardware.
Tied to @ivarflakstad's PR: https://github.com/huggingface/transformers/pull/37976 .
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Loading `meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8` with `transformers==4.53.0.dev0` or `4.51.0` initially failed with `TypeError: argument of type 'NoneType' is not iterable` in `transformers.modeling_utils.post_init`. This occurred with `Llama4ForConditionalGeneration` and `AutoModelForC... | {
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Loading `meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8` succeeds with `transformers==4.51.0`, but inference fails with `KeyError: 'model.layers.37.feed_forward.experts.gate_up_proj'` during `model.generate`. This occurs on 4x NVIDIA RTX A6000 (~196GB VRAM, CUDA 12.4, Python 3.12.3, Ubuntu 24.0... | {
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When attempting to load `meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8` using `transformers==4.53.0.dev0` (or `4.51.0`), I encounter a `TypeError: argument of type 'NoneType' is not iterable` in `transformers.modeling_utils.post_init`. This occurs with both `Llama4ForConditionalGeneration` and... | {
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During analyzing performance of flash attention on Ascend NPU, we find that a fixed-size 2048*2048 upper triangular matrix `attn_mask_npu` is frequently defined in func `npu_flash_attn_func` and `npu_flash_attn_varlen_func`, which will cost a lot of time.
This PR is committed for solving t... | {
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lm-eval 0.48
A100
Ubuntu
### Reproduction
~~~bash
lm_eval --model hf --model_args pretrained="facebook/opt-125m" --tasks lambada_openai
~~~
V4.52.2
| Tasks |Version|Filter|n-shot| Metric | | Value | | Stderr |
|--------------|------:|------|-----:|----------|---|----------:|---|... | {
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"merged_at... | # What does this PR do?
Adds a new architecture called normalized Transformer (nGPT) ([Paper](https://arxiv.org/abs/2410.01131)).
Fixes #38275
## 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 gui... | {
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Normalized Transformer (nGPT) is a novel architecture with representation learning on the hypersphere. In nGPT, all vectors forming the embeddings, MLP, attention matrices and hidden states are unit norm normalized. The input stream of tokens travels on the surface of a hypersphere, with each lay... | {
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- `transformers` version: 4.51.3
- Platform: Linux-5.15.0-122-generic-x86_64-with-glibc2.31
- Python version: 3.12.8
- Huggingface_hub version: 0.31.1
- Safetensors version: 0.5.2
- Accelerate version: 1.3.0
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (GPU?): ... | {
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In transformers v.4.52.0 - v4.52.2, the file: src/transformers/models/janus/convert_janus_weights_to_hf.py from #36053 is missing and results in an `ModuleNotFoundError` when running tests/models/janus/test_processor_janus.py:
```
Traceback:
tests/models/janus/test_processor_janus.py:23: in <module>
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21 May 2025 11:50:41 | polyaxon-main | from sentence_transformers import SentenceTransformer
21 May 2025 11:50:41 | polyaxon-main | File "/opt/conda/lib/python3.9/site-packages/sentence_transformers/__init__.py", line 14, in <module>
21 May 2025 11:50:41 | polyaxon-main | from sentence_transf... | {
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In the current generation code, group beam search is necessarily greedy. From a theoretical point of view, it is not very clear why that should be the case, since the diversity penalty is applied on the logits anyway, yielding a full distribution from which sampling can still be performed.
### Mot... | null | {
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### Model description
ByteDance recently released a multimodal understanding and generation model. While the code and weights have been made publicly available, the code requires significant formatting and cleaning to align with the standards of the Hugging Face Transformers library.
**BAGEL**
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Cleanup PR: moves a whisper processor test from the ASR pipeline test file to the whisper processor test file. In the process, it cleans up unused code from the library.
Some context: this was originally an ASR test because it used logic that was present in the ASR pipeline (`_find_timesta... | {
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This PR includes one improvements to the convert_internvl_weights_to_hf.py script for converting InternVL models:
- Allows loading model weights directly from a local path, enabling conversion without requiring remote downloads.
This change has been tested and verified on the InternVL2_... | {
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- `transformers` version: 4.52.1 (the problem occurs on `4.52.2`, but when i ran `transformers env,` I get the same error!)
- Platform: Linux-6.8.0-1026-gcp-x86_64-with-glibc2.35
- Python version: 3.11.0rc1
- Huggingface_hub version: 0.31.4
- Safetensors version: 0.5.3
- Accelerate version: not instal... | {
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This PR updates AMD CI image to use the latest PyTorch base image. This fix is required for the MI300 tests as PyTorch falls back to CPU on older versions.
## 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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Remove unnecessary decorators and docstring in modular falcon h1, use can_return_tuple decorators | {
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- `transformers` version: 4.52.0.dev0
- Platform: Linux-5.10.134-008.12.kangaroo.al8.x86_64-x86_64-with-glibc2.35
- Python version: 3.10.17
- Huggingface_hub version: 0.31.1
- Safetensors version: 0.5.3
- Accelerate version: 1.6.0
- Accelerate config: not found
- DeepSpeed version: 0.16.7
- PyTorch ... | {
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cc @Cyrilvallez @pcuenca @ArthurZucker | {
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This PR was reverted because it was failing... 711d78d104366c16dd99ef11084c27848f7a4133 | {
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Will transformers support dynamic quantization config for bitsandbytes? Currently transformers support hqq dynamic quantization, via
```python
q4_config = {"nbits": 4, "group_size": 64}
q8_config = {"nbits": 8, "group_size": 64}
quant_config = HqqConfig(
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https://api.github.com/repos/huggingface/transformers/issues/38252 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38252/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38252/comments | https://api.github.com/repos/huggingface/transformers/issues/38252/events | https://github.com/huggingface/transformers/pull/38252 | 3,079,111,965 | PR_kwDOCUB6oc6XAKtN | 38,252 | refine `transformers env` output | {
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"merged_at... | @ydshieh , pls help review, thx.
And one more thing is, I can see there is a [print_env.py](https://github.com/huggingface/transformers/blob/711d78d104366c16dd99ef11084c27848f7a4133/utils/print_env.py#L35) in `utils`, I am curious in which situation I should use `transformers env` and in which i should use `print_en... | {
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`DTensor` import was changed during Pytorch 2.5,
before 2.5, it uses `from torch.distributed._tensor import DTensor`.
And this broke the code, please check
[src/pytorch_utils.py](https://github.com/huggingface/transformers/blame/711d78d104366c16dd99ef11084c27848f7a4133/src/transformers/pytorch_utils.p... | {
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"merged_at... | ## Resolve DTensor Import Path Inconsistency Across PyTorch Versions
**Summary:**
This pull request addresses an import issue for `DTensor` arising from its path change across different PyTorch versions. It implements a conditional import mechanism to ensure compatibility.
**Problem:**
The location of the `DTen... | {
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"merged_at... | # What does this PR do?
This PR aims at integrating X-Codec model to `transformers`.
The X-Codec model is a neural audio codec that integrates semantic information from self-supervised models (e.g., HuBERT) alongside traditional acoustic information. This enables :
- **Music continuation** : Better modeling of... | {
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"merged_at... | @ydshieh , as we discussed in https://github.com/huggingface/transformers/pull/38192, i propose to change all device callings to device agnostic `backend_xx` calling for test cases, and i go through the `tests` folder and change the rest device-binding callings to that way. Pls help review, and thx for your patience in... | {
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"merged_at... | This PR addresses Issue #38187.
- Deleted `docs/source/ja/tasks/sequence_classification.md`
- Removed the entry from `_toctree.yml`
- Updated links in docs to point to the English sequence_classification page (with "(英語版)" in the link text)
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"merged_at... | # What does this PR do?
The if condition check can be simplified, since DTensor is also a Tensor:
if isinstance(tensor, torch.Tensor) or isinstance(tensor, DTensor): =>
if isinstance(tensor, torch.Tensor):
The code for DTensor export later within this function will handle it.
<!--
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Fixes KeyError in 4D attention mask creation for encoder-decoder models when generating with attention mask and static cache.
This occurs because `inputs_embeds` does not get added to `model_inputs` for encoder-decoder models, like Whisper. Subsequently it tries to check if `model_inputs["in... | {
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As the title says. However not sure if worth it, as there are a lot of different descriptions currently for the same args. The descriptions that are different from the one in ModelOutputArgs are left in the ModelOutput docstring, which is why the there's not that much more deletions than addi... | {
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I think it's more intuitive and impactful to start by showing `tp_plan` so they understand how it works at a higher-level, and then they can explore the different strategies and how to set those. | {
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request the support for training support for QuantizationMethod.BITNET
### Open source status
- [ ] The model implementation is available
- [ ] The model weights are available
### Provide useful links for the implementation
_No response_ | null | {
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"merged_at... | Fixes #37333
This PR corrects the initialization of the bbox_embed layers in GroundingDinoForObjectDetection when config.decoder_bbox_embed_share is set to False.
What does this PR do?
Previously, the bbox_embed list was not properly initialized with independent layers when decoder_bbox_embed_share=False. The c... | {
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Fixing some failing gptq tests.
Fixing some bnb tests
in gptq, It seems there's a regression in the new release — the layer type used to be `tritonv2` in CI, but it's now `torch`. An issue has been opened [here](https://github.com/ModelCloud/GPTQModel/issues/1617). Will update once the... | null | {
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"merged_at... | # What does this PR do?
whisper has a very slow set of tests.
This PR applies low-hanging fruit changes to get faster tests (slow tests: 7m47s -> 6m59s on my machine)
- the main dataset is now loaded once per test suite (as opposed to once per test in relevant tests)
- generation tests happen on GPU when possi... | {
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"merged_at... | Whisper attention refactor according to the same strategies applied in #38108
Also, several fixes on Whisper along the way, reducing the number of failed tests to 3 (disregarding skipped tests):
- `test_small_longform_timestamps_generation`
- `test_tiny_token_timestamp_batch_generation`
- `test_whisper_longform_m... | {
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As stated in the title | {
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Fix InternVL conversion script.
Fixes #38203 | {
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Fixes #37172
`forced_decoder_ids`, an old `whisper` flag, was deprecated in favor of the more explicit `task` and `language` flags (#28687). However, we need to handle it for BC: the original checkpoints have them.
This PR does a few deprecation-related changes, in an attempt to move us... | {
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Should fix https://github.com/huggingface/transformers/issues/38228 | {
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- allow non-Nvidia daily scheduled CI runs being able to compare to Nvidia runs
- allow manual trigger by `push` or `workflow_dispatch`
- this is useful when we need to trigger a manual runs, like a run for new torch version (RC) to see if there is any regression
- (If AMD workflow wa... | {
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This pr simply fixes an issue related to using `_replace_with_bitnet_linear` outside of the quantizer in tests. It checks if `quantization_config` is not None before accessing `use_rms_norm`
Action : https://github.com/huggingface/transformers/actions/runs/15127726788/job/42523132728 | {
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The new entry for `sam_hq` overwrites the existing entry for regular `sam`.
```
MODEL_FOR_MASK_GENERATION_MAPPING_NAMES = OrderedDict(
[
("sam", "SamModel"),
]
)
MODEL_FOR_MASK_GENERATION_MAPPING_NAMES = OrderedDict(
[
("sam_hq", "SamHQModel"),
]
)
```
See
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This PR fixes a breaking change that was caused by https://github.com/huggingface/transformers/pull/38090. We removed in that PR `train_dataset` arg but TRL lib uses it. We make it optional instead now | {
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