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Minor updates to `granite_speech` to enable finetuning it with HF trainers.
- avoids a crash when trainers pass `padding=True` to the processor
- ensure all trainable parameters have gradients (bugfix) - remove `.data` from a forward call
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```
Torch version: 2.7.1+cu126
Transformers version: 4.41.2
Datasets version: 2.20.0
PEFT version: 0.11.1
TRL version: 0.8.6
Bitsandbytes version: 0.46.0
Accelerate version: 0.31.0
```
```!pip install -q transformers datasets accelerate peft bitsandbytes einops```
```
import torch
from transformers i... | {
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This PR updates the Phi-4 Multimodal card documentation as described in #36979, in an attempt to standardize all model-cards.
#36979
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Add support for asynchronous evaluation in `transformers.Trainer`, ideally enabling evaluation to run in parallel to training — potentially on a separate GPU — without blocking the training loop.
Even ideally, to really utilize the hardware fully, one GPU should be training, the other one should b... | null | {
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Fixes a broken closing tag in the Longformer model card. The broken tag caused the code examples to display incorrectly on the [model card page](https://huggingface.co/docs/transformers/main/en/model_doc/longformer).
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Earlier PR put executorch specific sdpa and mask function in the export function. This prevent any customization that can be done to sdpa, prior to export. By moving this to __init__, we still keep the original behavior but allow users like optimum-executorch to override sdpa by setting model.c... | {
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A cache as described in the [SepLLM paper - ICML 2025](https://arxiv.org/abs/2412.12094). In the training phase,
SepLLM condenses the segment i... | {
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I have a test case that instantiates a model with a number of class count options e.g. (1,2,10). The source model is trained on a single class. `ignore_mismatched_sizes` is set to `True`. If I change `num_classes` to 2, the model load fails. If I change it to anything else, it seems to be fine. The error seems to be i... | {
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https://api.github.com/repos/huggingface/transformers/issues/38822 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38822/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38822/comments | https://api.github.com/repos/huggingface/transformers/issues/38822/events | https://github.com/huggingface/transformers/pull/38822 | 3,144,967,151 | PR_kwDOCUB6oc6ad4x5 | 38,822 | Corrections to PR #38642 and enhancements to Wav2Vec2Processor __call__ and pad docstrings | {
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The modifications to Wav2Vec2Processor __call__ and pad docstrings adds back the reference of PreTrainedTokenizer __call__ and pad removed incorrectly in PR #38642. As the __call__ and pad methods are important public methods for Wav2Vec2Processor, this PR also enhances the docstrings with t... | {
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https://api.github.com/repos/huggingface/transformers/issues/38820 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38820/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38820/comments | https://api.github.com/repos/huggingface/transformers/issues/38820/events | https://github.com/huggingface/transformers/issues/38820 | 3,144,755,851 | I_kwDOCUB6oc67cSqL | 38,820 | CI skipped failures tracking issue | {
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"merged_at... | # What does this PR do?
I have encountered an error during training on an M1 mac, similar to:
https://github.com/pytorch/pytorch/issues/87688
I have implemented the suggested fix, and it works.
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's ... | null | {
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https://api.github.com/repos/huggingface/transformers/issues/38818 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38818/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38818/comments | https://api.github.com/repos/huggingface/transformers/issues/38818/events | https://github.com/huggingface/transformers/pull/38818 | 3,144,286,910 | PR_kwDOCUB6oc6abhbl | 38,818 | [Feature] Support `is_split_into_words` in the `TokenClassificationPipeline`. | {
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"merged_at... | # What does this PR do?
Fixes #30757
This PR solves the problem that when using an already tokenized input in the `TokenClassificationPipeline` by adding a `tokenizer_parameter` called `is_split_into_words`. I think we will need the aggregation code because some tokenizers are subword tokenizers, I have solved the ... | {
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Use revision as discussed offline (as [Hub PR](https://huggingface.co/microsoft/Phi-4-multimodal-instruct/discussions/70) is not merged) and also updated some expected values + one `require_torch_large_accelerator`.
All passing on T4/A10 with torch 2.7.1 | {
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https://api.github.com/repos/huggingface/transformers/issues/38815 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38815/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38815/comments | https://api.github.com/repos/huggingface/transformers/issues/38815/events | https://github.com/huggingface/transformers/pull/38815 | 3,143,642,843 | PR_kwDOCUB6oc6aZV3V | 38,815 | Fix a minor security issue | {
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There is an security report about this. It's not a big deal as `utils/check_self_hosted_runner.py` is only used in some AMD workflow files that could be only triggered by push event `.github/workflows/self-push-amd.yml` (not really used) or in
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```python
from trl import SFTTrainer, SFTConfig
from datasets import load_dataset
trainer = SFTTrainer(
model="Qwen/Qwen2.5-0.5B",
args=SFTConfig(report_to="trackio"),
train_dataset=load_dataset("trl-lib/Capybara", split="train"),
)
trainer.train()
```
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https://api.github.com/repos/huggingface/transformers/issues/38813 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38813/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38813/comments | https://api.github.com/repos/huggingface/transformers/issues/38813/events | https://github.com/huggingface/transformers/pull/38813 | 3,143,513,047 | PR_kwDOCUB6oc6aY5O6 | 38,813 | Fix `llava_next` tests | {
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Update expected values + a few dtype / device issue | {
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"merged_at... | # What does this PR do?
As per title, another tiny clean up that deletes a `from_text_vision_configs` for initializing configs from its sub-configs. That can perfectly be done by `cls.__init__` and this no need to maintain a separate method for that
I added a warning with a deprecation cycle of 7 minor releases, ... | {
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Video inference broke after https://github.com/huggingface/transformers/pull/38105 because the model was inferring number of frames before processing. Previously that worked fine, but with the new workflow the actual number of frames can be inferred only after processing and sampling | {
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This PR update the forward method to support kwargs for flexible loss customization.
Fixes #36119
## 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://githu... | null | {
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```python
def prediction_step(
self,
model: nn.Module,
inputs: dict[str, Union[torch.Tensor, Any]],
prediction_loss_only: bool,
ignore_keys: Optional[list[str]] = None,
) -> tuple[Optional[torch.Tensor], Optional[torch.Tensor], Optional[tor... | {
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Draft PR to add Dust3R
Cc @raf-fonseca
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transformers version: 4.52.4
pytorch version: 2.6
### Who can help?
transformers version: 4.52.4
pytorch version: 2.6
When running Llama4 with tensor parallel, [torch.nn.Unfold used in llama4 ](https://github.com/huggingface/transformers/blob/v4.52.4/src/transformers/models/llama4/modeling_llama4.py... | {
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# What does this PR do?
This PR adds the `granite`, `granitemoe`, `granitemoeshared`, and `granitemoehybrid` model architectures to the `TOKENIZER_MAPPING_NAMES` mapping so that using `pipeline` will correctly infer the tokenizer class when loading the models without needing to add... | {
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Allows for the case where `GraniteMoeHybrid` models have `num_local_experts = 0`
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Fixes #26286
For the issue basically when `align_to_words=True` , I added start/end subword probabilities per each word and assigned to the first subword of the word (also assigned 0s for start/end probs to rest subwords), this way assured that the first subword will always be chosen prov... | {
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Fixes a small typo in the docstring reference to `Qwen2VLImageProcessor`. The incorrect reference (`Qwen2_5_VLImageProcessor`).
## Before submitting
- [x] This PR fixes a typo or improves the docs.
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers... | {
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"merged_at... | Hi, this PR fixes a small issue in the LlamaAttention class. The return type in the forward method currently shows three values, but the function actually returns only two. This seems to have been missed during the attention refactor (possibly in PR #35235).
I’ve updated the type hint to reflect the actual return va... | {
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Description:
This pull request fixes minor typos in comments across two files:
- In `modeling_swin.py`, the word "disible" was corrected to "divisible" for clarity in the padding comment.
- In `pt_utils.py`, the typo "lookig" was corrected to "looking" in a comment explaining iterator behavior.
These chan... | null | {
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`low_cpu_mem_usage` argument was removed in https://github.com/huggingface/transformers/pull/36963 - this PR removes all leftover everywhere in the library (the arg is ignored already)
We only keep it in the `peft` integration, as it is used downstream in `peft` | {
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As usual, just some updates of expected values.
Now pass both on A10 / T4 torch 2.7.1 | {
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Removes the upper bound on the PyTorch dependency, as the original issue in PyTorch (https://github.com/pytorch/pytorch/issues/152275) has been resolved and released.
Fixes # (issue)
Fixes https://github.com/huggingface/transformers/issues/37824
## Before submitting
- [ ] This PR fixes ... | {
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Adds a classification model compatible with the released pretrained classifiers on Something-Something-v2 and Diving48 datasets.
Epic Kitchen is a bit special, with 3 different classifiers on top of pooler (noun, verb, action), so it might require an additional model class to handle the ca... | {
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Irrelevant
### Who can help?
@ArthurZucker
Documentation [says](https://github.com/huggingface/transformers/blob/89c46b648d82b670cc7286a25fa64d2d92770418/src/transformers/models/qwen3/configuration_qwen3.py#L115C9-L116C134):
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"merged_at... | In the current documentation, I believe there is an error in the sample code. While the language token of the input is specified as `<2pt>` (Portuguese), the returned translation is in Italian, so actually the language should be `<2it>`.
I didn't initially understand that this was a token for the target language, so... | null | {
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Averaging a single value is not strictly speaking incorrect. So I suggest rephrasing, and reducing the level to info. This removes recurring warnings when True is used as the default for this argument.
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss t... | {
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https://github.com/huggingface/transformers/pull/38561 removed the try/catch statement but changed True to False in sliding and chunked mask logic. This PR fixes it.
cc @zucchini-nlp for viz | {
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This PR fixes a RuntimeError that occurs in InformerModel when config.input_size is set to 1.
When input_size=1, the loc and scale tensors calculated by the scaler retained an extra dimension (e.g., shape [B, 1, 1] instead of [B, 1]). This incorrect shape caused a dimension mismatch error duri... | {
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[Quickly merged to check everything is working now]
#38754 My comment https://github.com/huggingface/transformers/pull/38754#issuecomment-2963796287
is actually incorrect as my experiment on my own forked repository forgot to leave a comment after the style bot push.
We still some pe... | {
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This PR fixes a bug in beam search generation where early stopping heuristics (when `early_stopping=False`) was incorrectly applied across the entire batch, instead of per instance.
## 🔍 Problem
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As suggested in this issue - #36979 - this PR updates the documentation of the Roberta model, which will now be aligned with the standardized format for all the docs.
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transformers v4.52.3
The docs at https://huggingface.co/docs/transformers/accelerate show -

However when working with accelerate in TrainingArgs I get the following issue of fsdp strategy not available
![image]... | {
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Fixes https://github.com/huggingface/transformers/issues/38727 and adds tiny block about possible issues with chat templates
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As suggested in this issue - https://github.com/huggingface/transformers/issues/36979 - this PR updates the documentation of the Roberta model, which will now be aligned with the standardized format for all the docs.
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I updated the Pegasus model card in #38675 but missed a single `<div>`, causing the badges to appear misaligned on the page. This PR adds the missing div and fixes the alignment issue.
## Before submitting
- [X] This PR fixes a typo or improves the docs (you can dismiss the other checks i... | {
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Hi from pytorch distributed! Thanks for showcasing pytorch APIs
device_map='auto' and tp_plan='auto' are somehow coupled right now:
https://github.com/huggingface/transformers/blob/main/src/transformers/modeling_utils.py#L4280-L4283
if people load model with `device_map='auto'`, they will ended u... | {
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I’ve updated the type hint to reflect the actual return va... | {
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- In `modeling_visual_bert.py`, the word "averege" is corrected to "average".
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Apple recently released FastVLM, a new vision-language model introduced at CVPR 2025, which significantly improves on previous models in the LLaVA family.
The smallest FastVLM variant outperforms LLaVA-OneVision-0.5B, achieving:
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https://github.com/huggingface/transformers/pull/38757
https://github.com/huggingface/transformers/pull/38756
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WIP
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WIP | null | {
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Adds the SmolLM3 modular arch
## 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 [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#create-a-pull-r... | {
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Let's see if it works. I tested on my own ydshieh/transformers with an external contributor `ydshieh2`. | {
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- `transformers` version: 4.49.0
- Platform: Linux-5.4.0-216-generic-x86_64-with-glibc2.31
- Python version: 3.13.2
- Huggingface_hub version: 0.29.2
- Safetensors version: 0.5.3
- Accelerate version: 1.7.0
- Accelerate config: not found
- DeepSpeed version: 0.16.8
- PyTorch version (GPU?): 2.6.0+cu... | {
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When working on https://github.com/huggingface/transformers/pull/38635, I found that there are some models which have `past_key_values` in their signature, even though they cannot generate. The reason is that models were all copying from Bert
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Before this PR [38288](https://github.com/huggingface/transformers/pull/38288), the program will run smoothly even when we set `output_attentions=True` and the attn implementation is not `eager`, as it will fallback to use eager mode, after this PR, it will throw error directly: [L342](https://github.c... | {
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This PR fixes a RuntimeError that occurs in InformerModel when config.input_size is set to 1.
When input_size=1, the loc and scale tensors calculated by the scaler retained an extra dimension (e.g., shape [B, 1, 1] instead of [B, 1]). This incorrect shape caused a dimension mismatch error duri... | {
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Adds chatterbox text-to-speech model!
[Original code](https://github.com/resemble-ai/chatterbox)
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When I set the infomerconfig.input_size = 1, I find a bug, but I don't know how to fix it.
- Function Name : `create_network_inputs`
```
time_feat = (
torch.cat(
(
past_time_features[:, self._past_length - self.config.context_length :, ...],
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Similar to the changes made in https://github.com/huggingface/transformers/pull/37037, this commit allows passing kwargs to layers when using gradient checkpointing for more models.
For example, Pixtral needs to [pass](https://github.com/huggingface/transformers/blob/main/src/transformers/... | {
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Implement handling for configurations where the `q_lora_rank` parameter is set to `None`.
Fixes #38742
## 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://... | {
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Implement handling for configurations where the `q_lora_rank` parameter is set to `None`.
### Motivation
1. [DeepSeek-V2-Lite](https://huggingface.co/deepseek-ai/DeepSeek-V2-Lite/blob/main/config.json) model has `q_lora_rank=None` so we can support this model with this modeling.
2. [Original remo... | {
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Since flash_attention_2 relies solely on position_ids, emitting the block attention mask avoids unnecessary memory usage and prevents OOM on large inputs.
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Have a section on Pruna AI within the documentation. We did [a similar PR for diffusers](https://github.com/huggingface/diffusers/pull/11688) and thought it would be nice to show how to optimize transformers models too.
.
### Motivation
Have a section on Pruna AI within the documentation to show... | null | {
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For the current version (4.52.4), in the `LlamaAttention` class, the type hint for the forward function
https://github.com/huggingface/transformers/blob/aa798b7ac9ff5018b3578eb927dc438671ab6a3e/src/transformers/models/llama/modeling_llama.py#L231
and what it actually returns
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This PR is a clone of https://github.com/huggingface/transformers/pull/38578 with a small fix, this time targeting main. It's part of a series of PRs propagating back fixes for AMD devices from https://github.com/huggingface/transformers/tree/amd-hf-ci-branch .
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Unfortunately, this is not working.
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