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Delete the faulty check on multimodal tokens | {
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"merged_at... | This PR adds support for minor version in the `Expectations` system and changes the way the score is computed to avoid cross-device comparison. It also uses the revamped system to fix 6 tests on AMD devices.
cc. @mht-sharma | {
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"merged_at... | # What does this PR do?
Fixes [bitsandbytes](https://github.com/bitsandbytes-foundation/bitsandbytes/issues/837)
## Before submitting
- [X] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#create-a-pull-request),
Pull Request section?
- [X] ... | {
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https://api.github.com/repos/huggingface/transformers/issues/38527 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38527/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38527/comments | https://api.github.com/repos/huggingface/transformers/issues/38527/events | https://github.com/huggingface/transformers/issues/38527 | 3,110,000,793 | I_kwDOCUB6oc65XtiZ | 38,527 | Why do you remove sample_indices_fn for processor.apply_chat_template? | {
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<img width="712" alt="Image" src="https://github.com/user-attachments/assets/e055d5f5-4800-4eb7-8054-0f41a9be5707" /> | {
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https://api.github.com/repos/huggingface/transformers/issues/38526 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38526/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38526/comments | https://api.github.com/repos/huggingface/transformers/issues/38526/events | https://github.com/huggingface/transformers/pull/38526 | 3,109,883,331 | PR_kwDOCUB6oc6YnHAv | 38,526 | Don't use default attn if pre-set in sub-config | {
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As per title, so we can do smth like below. In current state the value will be overwritten with default `None`
Might be breaking if the configs on the hub have a certain attention implementation saved in sub-config level only. Though I don't think any model has it saved that way
```pyth... | {
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https://api.github.com/repos/huggingface/transformers/issues/38525 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38525/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38525/comments | https://api.github.com/repos/huggingface/transformers/issues/38525/events | https://github.com/huggingface/transformers/pull/38525 | 3,109,815,394 | PR_kwDOCUB6oc6Ym45r | 38,525 | [qwen-omni] fix sliding window | {
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The inference in broken on `main` because modular applied changes in the Talker's attention as well. However the config wasn't updated with the new keys for sliding window | {
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https://api.github.com/repos/huggingface/transformers/issues/38524 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38524/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38524/comments | https://api.github.com/repos/huggingface/transformers/issues/38524/events | https://github.com/huggingface/transformers/issues/38524 | 3,109,016,455 | I_kwDOCUB6oc65T9OH | 38,524 | 404 Client Error when accessing https://router.huggingface.co/nebius/v1/chat/completions endpoint | {
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Hello Hugging Face Team,
I encountered a 404 Client Error when trying to access the following API endpoint:
404 Client Error: Not Found for url: https://router.huggingface.co/nebius/v1/chat/completions
(Request ID: Root=1-683d55ae-4365e822229e0a423f164d56;0912aa19-4d00-4575-b250-5e23c4163bcb)
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Hi! I have an error "size mismatch" when trying to download ChatGPT-4 using transformers
```
from transformers import AutoModelForCausalLM
model_p = AutoModelForCausalLM.from_pretrained("OpenAI-ChatGPT/ChatGPT-4" )
```
```
RuntimeError: Error(s) in loading state_dict for Qwen2ForCausalLM:
size misma... | {
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https://api.github.com/repos/huggingface/transformers/issues/38522 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38522/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38522/comments | https://api.github.com/repos/huggingface/transformers/issues/38522/events | https://github.com/huggingface/transformers/issues/38522 | 3,108,344,215 | I_kwDOCUB6oc65RZGX | 38,522 | Allow `mlm_probability` to be set to None when `mlm`=False in `DataCollatorForLanguageModeling` | {
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Currently, in the `DataCollatorForLanguageModeling` class, the `mlm_probability` argument is required to be a float between 0 and 1, regardless of whether `mlm` is `True` or `False`.
However, since `mlm_probability` is only used when `mlm=True`, it would make sense to allow `mlm_probability=None` when... | {
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https://api.github.com/repos/huggingface/transformers/issues/38521 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38521/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38521/comments | https://api.github.com/repos/huggingface/transformers/issues/38521/events | https://github.com/huggingface/transformers/issues/38521 | 3,108,293,474 | I_kwDOCUB6oc65RMti | 38,521 | Error for `return_assistant_tokens_mask` in MLLM processor | {
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latest version of transformers, after #37602
### Who can help?
@zucchini-nlp
### Information
- [ ] The official example scripts
- [x] My own modified scripts
### Tasks
- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give detail... | {
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https://api.github.com/repos/huggingface/transformers/issues/38520 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38520/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38520/comments | https://api.github.com/repos/huggingface/transformers/issues/38520/events | https://github.com/huggingface/transformers/pull/38520 | 3,107,848,804 | PR_kwDOCUB6oc6YgZEK | 38,520 | Add QuasarV4 model | {
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## What does this PR do?
This PR adds the QuasarV4 model to the transformers library, introducing a new architecture with token temperature mechanism and multi-scale token processing for efficient long context handling.
QuasarV4 extends transformer architecture with two key innovations:
1. **Token Temperature ... | null | {
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https://api.github.com/repos/huggingface/transformers/issues/38519 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38519/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38519/comments | https://api.github.com/repos/huggingface/transformers/issues/38519/events | https://github.com/huggingface/transformers/pull/38519 | 3,107,791,628 | PR_kwDOCUB6oc6YgOIP | 38,519 | Fix `return_dict=False` giving errors in a few VLM models | {
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"merged_at... | # What does this PR do?
We have some VLM models that have the following patten:
```
@can_return_tuple
def forward(self):
....
return_dict = return_dict if return_dict is not None else self.config.use_return_dict
outputs = self.model( ..., return_dict=return_dict, ...)
....
... | {
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https://api.github.com/repos/huggingface/transformers/issues/38518 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38518/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38518/comments | https://api.github.com/repos/huggingface/transformers/issues/38518/events | https://github.com/huggingface/transformers/issues/38518 | 3,107,599,219 | I_kwDOCUB6oc65OjNz | 38,518 | Failed to export PyTorch traced graph of Mixtral-8x7B-Instruct-v0.1 due to the PR #32429 | {
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"node_id": ... | open | false | null | [] | null | [] | 2025-06-01T17:46:08 | 2025-08-04T14:16:00 | null | CONTRIBUTOR | null | null | null | null | ### System Info
Hi ,
I found the recently transformers 4.52.4 merged this PR https://github.com/huggingface/transformers/pull/32429
and it led me failed to run below code snippet which it could run successfully with 4.51.3.
```python
import transformers
import torch.export as te
import torch
from contextlib import ... | null | {
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https://api.github.com/repos/huggingface/transformers/issues/38517 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38517/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38517/comments | https://api.github.com/repos/huggingface/transformers/issues/38517/events | https://github.com/huggingface/transformers/issues/38517 | 3,107,580,153 | I_kwDOCUB6oc65Oej5 | 38,517 | model_type = self._reverse_config_mapping[key.__name__] KeyError: 'Qwen2RMConfig' | {
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File "/anaconda/envs/openrlhf/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py", line 767, in __getitem__
model_type = self._reverse_config_mapping[key.__name__]
KeyError: 'Qwen2RMConfig'
transformers version is 4.51.3
### Who can help?
_No response_
### Information
- [ ]... | {
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https://api.github.com/repos/huggingface/transformers/issues/38516 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38516/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38516/comments | https://api.github.com/repos/huggingface/transformers/issues/38516/events | https://github.com/huggingface/transformers/issues/38516 | 3,107,066,987 | I_kwDOCUB6oc65MhRr | 38,516 | Hang in quantized_phi::ModelWeights::forward() with Phi-2 GGUF on CPU (Candle main branch) | {
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Description:
The program hangs indefinitely when calling the forward() method on a quantized_phi::ModelWeights instance loaded from a Phi-2 GGUF file. This occurs during the first iteration of token generation, specifically after printing a log message "Calling model.forward()..." and before any indica... | {
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https://api.github.com/repos/huggingface/transformers/issues/38515 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38515/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38515/comments | https://api.github.com/repos/huggingface/transformers/issues/38515/events | https://github.com/huggingface/transformers/pull/38515 | 3,107,058,418 | PR_kwDOCUB6oc6YeC8p | 38,515 | added fast image processor for ZoeDepth and expanded tests accordingly | {
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"merged_at... | - Adds new fast image processor for zoedepth, see #36978
- Expands tests accordingly
potential reviewer: @yonigozlan
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https://api.github.com/repos/huggingface/transformers/issues/38514 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38514/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38514/comments | https://api.github.com/repos/huggingface/transformers/issues/38514/events | https://github.com/huggingface/transformers/issues/38514 | 3,106,975,261 | I_kwDOCUB6oc65MK4d | 38,514 | Can not reproduce Blip2ForImageTextRetrieval example from docs, getting different results | {
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- `transformers` version: 4.52.4
- Platform: Linux-4.4.0-x86_64-with-glibc2.36
- Python version: 3.12.6
- Huggingface_hub version: 0.32.3
- Safetensors version: 0.5.3
- Accelerate version: not installed
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (GPU?): 2.7.0+c... | {
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https://api.github.com/repos/huggingface/transformers/issues/38512 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38512/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38512/comments | https://api.github.com/repos/huggingface/transformers/issues/38512/events | https://github.com/huggingface/transformers/pull/38512 | 3,106,765,084 | PR_kwDOCUB6oc6YdH-G | 38,512 | Fix initialization of a pretrained backbone | {
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https://api.github.com/repos/huggingface/transformers/issues/38510 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38510/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38510/comments | https://api.github.com/repos/huggingface/transformers/issues/38510/events | https://github.com/huggingface/transformers/pull/38510 | 3,106,050,629 | PR_kwDOCUB6oc6Ya9Xr | 38,510 | Fix blip2 tests | {
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🎉 🎉 🎉
I added comments on the changes in `Files changed`
For the list of failing tests on current main, see
https://github.com/huggingface/transformers/actions/runs/15382744712/job/43276231818 | {
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https://api.github.com/repos/huggingface/transformers/issues/38509 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38509/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38509/comments | https://api.github.com/repos/huggingface/transformers/issues/38509/events | https://github.com/huggingface/transformers/issues/38509 | 3,105,992,692 | I_kwDOCUB6oc65Ia_0 | 38,509 | SparseVLM: Visual Token Sparsification for Efficient Vision-Language Model Inference | {
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] | open | false | null | [] | null | [] | 2025-05-31T20:21:42 | 2025-06-03T16:53:42 | null | CONTRIBUTOR | null | null | null | null | ### Feature request
I’d like to request the addition of **SparseVLM: Visual Token Sparsification for Efficient Vision-Language Model Inference** to the 🤗 Transformers library.
**Paper**: [https://arxiv.org/abs/2410.04417](https://arxiv.org/abs/2410.04417)
**Authors**: Yuan Zhang, Chun-Kai Fan, Junpeng Ma, et al. ... | null | {
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https://api.github.com/repos/huggingface/transformers/issues/38508 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38508/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38508/comments | https://api.github.com/repos/huggingface/transformers/issues/38508/events | https://github.com/huggingface/transformers/issues/38508 | 3,105,958,102 | I_kwDOCUB6oc65ISjW | 38,508 | Model Request: SLaM (Sparse Latent Mixer) – Multimodal Flamingo Alternative | {
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SLaM (Sparse Latent Mixer)
### Paper link
https://arxiv.org/abs/2405.12321
### Description
I came across the recent paper on **SLaM: Sparse Latent Mixer** and found it super exciting — it's a really promising direction for efficient multimodal modeling. SLaM builds on Flamingo-style architectures but i... | {
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https://api.github.com/repos/huggingface/transformers/issues/38507 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38507/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38507/comments | https://api.github.com/repos/huggingface/transformers/issues/38507/events | https://github.com/huggingface/transformers/issues/38507 | 3,105,652,617 | I_kwDOCUB6oc65HH-J | 38,507 | id2label assignment problem in run_glue.py | {
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Should It be model.config.id2label = {id: label for label, id in label_to_id.items()}?
Same as https://github.com/huggingface/transformers/blob/51d732709e5ae42... | {
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This PR fixes a trivial markdown issue on the formatting of the BertTokenizer's '[CLS]' token in the docstring for `add_special_tokens`
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This PR updates the model-card for the GPT Neo model, as described in https://github.com/huggingface/transformers/issues/36979, in an attempt to standardize all model-cards.
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Fixes formatting, code blocks were not rendered properly and comments were rendered as headings.
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [contributor guideline](https://github.com... | {
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"merged_at... | As per the title, it removes the type annotation that causes issues when using Modular as we don't usually have both text and vision config for all the models. Since SigLIP is commonly used in VLMs as vision backbone, and the Attention module is a quite generic so this allows us more flexibility in using Modular.
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https://api.github.com/repos/huggingface/transformers/issues/38502 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38502/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38502/comments | https://api.github.com/repos/huggingface/transformers/issues/38502/events | https://github.com/huggingface/transformers/pull/38502 | 3,104,715,042 | PR_kwDOCUB6oc6YWsJC | 38,502 | Add fast imageprocessor vitpose | {
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"merged_at... | Adding Fast Image processor for VitPose
Fixes #36978
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [X] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#create-a-pull-req... | {
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https://api.github.com/repos/huggingface/transformers/issues/38501 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38501/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38501/comments | https://api.github.com/repos/huggingface/transformers/issues/38501/events | https://github.com/huggingface/transformers/issues/38501 | 3,104,267,967 | I_kwDOCUB6oc65B16_ | 38,501 | torch.compile fails for gemma-3-1b-it | {
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- `transformers` version: 4.52.4
- Platform: Linux-6.15.0-1-MANJARO-x86_64-with-glibc2.41
- Python version: 3.12.8
- Huggingface_hub version: 0.32.3
- Safetensors version: 0.5.3
- Accelerate version: 1.7.0
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (GPU?): 2.... | {
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https://api.github.com/repos/huggingface/transformers/issues/38500 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38500/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38500/comments | https://api.github.com/repos/huggingface/transformers/issues/38500/events | https://github.com/huggingface/transformers/issues/38500 | 3,103,767,863 | I_kwDOCUB6oc64_703 | 38,500 | Unable to deploy Gemma 3 on AWS SageMaker due to lack of support in tranfomers release | {
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it seems when i deploy the model
```
huggingface_model = HuggingFaceModel(
model_data=model_s3_uri,
role=role,
transformers_version="4.49.0",
pytorch_version="2.6.0",
py_version="py312",
)
predictor = huggingface_model.deploy(
instance_type="ml.g5.48xlarge",
initial_instance_cou... | {
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https://api.github.com/repos/huggingface/transformers/issues/38499 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38499/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38499/comments | https://api.github.com/repos/huggingface/transformers/issues/38499/events | https://github.com/huggingface/transformers/issues/38499 | 3,103,754,251 | I_kwDOCUB6oc64_4gL | 38,499 | ModernBERT for MLM outputs incorrect hidden state shape. | {
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When using `ModernBERTForMaskedLM` with `output_hidden_states=True` the hidden state is not correctly padded when it is returned. A minimal example is included below:
```
import torch
from transformers import AutoTokenizer, ModernBertForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("answerdotai/... | {
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https://api.github.com/repos/huggingface/transformers/issues/38498 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38498/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38498/comments | https://api.github.com/repos/huggingface/transformers/issues/38498/events | https://github.com/huggingface/transformers/issues/38498 | 3,103,713,402 | I_kwDOCUB6oc64_uh6 | 38,498 | [Florence-2] SyntaxWarning: invalid escape sequence '\d' in processing_florence2.py | {
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System Info
OS
nt
Python Version
3.12.10 (tags/v3.12.10:0cc8128, Apr 8 2025, 12:21:36) [MSC v.1943 64 bit (AMD64)]
Embedded Python
false
Pytorch Version
2.7.0+cu128
Arguments
ComfyUI\main.py --windows-standalone-build
RAM Total
31.93 GB
RAM Free
9.09 GB
Devices
### Who can help?
hookylee@gmail.com
H... | {
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https://api.github.com/repos/huggingface/transformers/issues/38497 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38497/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38497/comments | https://api.github.com/repos/huggingface/transformers/issues/38497/events | https://github.com/huggingface/transformers/pull/38497 | 3,103,537,398 | PR_kwDOCUB6oc6YSrIi | 38,497 | Add ZoeDepthImageProcessorFast: PyTorch-native Fast Image Preprocessing for ZoeDepth | {
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This PR introduces `ZoeDepthImageProcessorFast`, a new PyTorch-based fast image processor for the ZoeDepth model, designed to accelerate preprocessing and enable deployment in PyTorch-native pipelines.
---
## What does this PR do?
- **Implements `ZoeDepthImageProcessorFast`** in `src/transformers/models/zoed... | {
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"merged_at... | # What does this PR do?
Fixes https://github.com/huggingface/transformers/issues/38494
The import was not protected correctly, hence users who had torch < 2.5 faced issue when saving the model. This PR fixes this. | {
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https://api.github.com/repos/huggingface/transformers/issues/38495 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38495/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38495/comments | https://api.github.com/repos/huggingface/transformers/issues/38495/events | https://github.com/huggingface/transformers/pull/38495 | 3,103,438,338 | PR_kwDOCUB6oc6YSVeb | 38,495 | lazy cache init | {
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CB needs lazy cache init as well.
Making sure all layers are local, but casting to DTensor appropriately sounds a lot easier.
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https://api.github.com/repos/huggingface/transformers/issues/38494 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38494/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38494/comments | https://api.github.com/repos/huggingface/transformers/issues/38494/events | https://github.com/huggingface/transformers/issues/38494 | 3,103,429,351 | I_kwDOCUB6oc64-pLn | 38,494 | ImportError: cannot import name 'DTensor' from 'torch.distributed.tensor' | {
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I think this should be a ... | {
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https://api.github.com/repos/huggingface/transformers/issues/38492 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38492/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38492/comments | https://api.github.com/repos/huggingface/transformers/issues/38492/events | https://github.com/huggingface/transformers/pull/38492 | 3,102,794,109 | PR_kwDOCUB6oc6YQISO | 38,492 | Fix `Gemma2IntegrationTest` | {
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Currently on singe-gpu T4 runner, `test_export_hybrid_cache` use more than 60G CPU RAM memory and the process is killed, so we don't receive any report.
This PR skips this tests by introducing a new `require_large_cpu_ram`. I also update some tests to make them pass and to avoid some OOM.
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https://api.github.com/repos/huggingface/transformers/issues/38491 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38491/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38491/comments | https://api.github.com/repos/huggingface/transformers/issues/38491/events | https://github.com/huggingface/transformers/pull/38491 | 3,102,554,284 | PR_kwDOCUB6oc6YPV2Z | 38,491 | [bugfix] fix apply_rotary_emb error on Ascend NPU | {
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When using Qwen2.5-VL model with Flash Attention 2, we find that the implementation logic about api `torch_npu.npu_rotary_mul` is a little bit different from the same api in package `flash-attn`.
The former can only accept input param `x` and `sin`/`cos` with 4-dimension and same attentio... | {
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https://api.github.com/repos/huggingface/transformers/issues/38490 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38490/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38490/comments | https://api.github.com/repos/huggingface/transformers/issues/38490/events | https://github.com/huggingface/transformers/pull/38490 | 3,102,551,124 | PR_kwDOCUB6oc6YPVKf | 38,490 | Fix rope validation | {
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never mind. | {
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https://api.github.com/repos/huggingface/transformers/issues/38489 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38489/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38489/comments | https://api.github.com/repos/huggingface/transformers/issues/38489/events | https://github.com/huggingface/transformers/issues/38489 | 3,102,545,496 | I_kwDOCUB6oc647RZY | 38,489 | VLM reverse mapping logic in modeling_utils.py save_pretrained not doing anything? | {
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transformers version: 4.52.3
Platform: Ubuntu 24.04
Python version: 3.11.0
Huggingface_hub version: 0.32.2
Safetensors version: 0.5.3
Accelerate version: 1.7.0
Accelerate config: not found
DeepSpeed version: not installed
PyTorch version (GPU?): 2.7.0+cu126 (H100)
Tensorflow version (GPU?): not install... | {
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https://api.github.com/repos/huggingface/transformers/issues/38488 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38488/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38488/comments | https://api.github.com/repos/huggingface/transformers/issues/38488/events | https://github.com/huggingface/transformers/pull/38488 | 3,102,359,872 | PR_kwDOCUB6oc6YOsmy | 38,488 | [static cache] fix device map per layer in VLMs | {
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"merged_at... | # What does this PR do?
As per title, addresses the issue from https://github.com/huggingface/transformers/pull/38426#discussion_r2112312751
After the recent refactor, we don't return language model as `decoder` but only the base model, which contain vision/vq/audio etc encoders. Since generation relies on `get_d... | {
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https://api.github.com/repos/huggingface/transformers/issues/38487 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38487/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38487/comments | https://api.github.com/repos/huggingface/transformers/issues/38487/events | https://github.com/huggingface/transformers/pull/38487 | 3,102,148,552 | PR_kwDOCUB6oc6YN_TG | 38,487 | [Dinov2] Enable device_map="auto" support | {
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"merged_at... | This PR adds support for `device_map="auto"` to the Dinov2 model by defining `_no_split_modules = ["Dinov2Layer"]`, which enables inference across multiple devices using Accelerate and Transformers.
### ✔️ Summary
- Adds `_no_split_modules = ["Dinov2Layer"]` to `Dinov2PreTrainedModel`
- Includes a test `test_mod... | {
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https://api.github.com/repos/huggingface/transformers/issues/38486 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38486/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38486/comments | https://api.github.com/repos/huggingface/transformers/issues/38486/events | https://github.com/huggingface/transformers/pull/38486 | 3,102,120,322 | PR_kwDOCUB6oc6YN5R5 | 38,486 | [Dinov2] Enable device_map="auto" support | {
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"merged_at... | # What does this PR do?
This PR adds support for `device_map="auto"` to the Dinov2 model by defining `_no_split_modules = ["Dinov2Layer"]`. This enables offloading and multi-GPU inference using `accelerate` or `from_pretrained(..., device_map="auto")`.
### Highlights
- ✅ Added `_no_split_modules = ["Dinov2Laye... | {
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https://api.github.com/repos/huggingface/transformers/issues/38485 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38485/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38485/comments | https://api.github.com/repos/huggingface/transformers/issues/38485/events | https://github.com/huggingface/transformers/pull/38485 | 3,102,094,091 | PR_kwDOCUB6oc6YNzxM | 38,485 | [Dinov2] Enable device_map="auto" support | {
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This PR adds support for `device_map="auto"` to the Dinov2 model by defining `_no_split_modules = ["Dinov2Layer"]`. This enables multi-GPU and offload capabilities for large model inference.
A new test is added (`test_model_parallelism`) to verify `device_map="auto"` functionality in mult... | {
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- `transformers` version: 4.52.1
- Platform: Linux-5.15.0-1061-nvidia-x86_64-with-glibc2.35
- Python version: 3.10.16
- Huggingface_hub version: 0.30.2
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"merged_at... | # What does this PR do?
This PR adds the QuasarV4 model to the Transformers library. QuasarV4 is a new language model that introduces a token temperature mechanism, which dynamically adjusts token importance based on context. This mechanism enhances the model's ability to focus on relevant tokens and improves overal... | {
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Loading google/gemma-2-2b model raises KeyError: 'gemma2' even with Transformers 4.41.0 and trust_remote_code=True.
Error message is as below:
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
File /u... | {
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- `transformers` version: 4.52.3
- Platform: Linux-6.8.0-51-generic-x86_64-with-glibc2.39
- Python version: 3.12.0
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"merged_at... | # What does this PR do?
Reduces the Model size for ALBERT test model to improve testing speed.
Fixes #38344
# Changes Made:
- Reduced the number of parameters in the ALBERT test model.
- Optimized the model architecture to maintain testing relevance while minimizing resource usage.
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- `transformers` version: 4.52.3
- Platform: Windows-11-10.0.26100-SP0
- Python version: 3.13.2
- Huggingface_hub version: 0.31.2
- Safetensors version: 0.5.3
- Accelerate version: 1.7.0
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (GPU?): 2.7.0+xpu (False)
- ... | {
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"merged_at... | # What does this PR do?
Fix a issue found in quantized model TP test:
Fixes # (issue)
[rank0]: Traceback (most recent call last):
[rank0]: File "/workspace/transformers_tp_test.py", line 42, in <module>
[rank0]: model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=dtype, tp_plan=tp_plan,
[ra... | null | {
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"merged_at... | Test two with Opus 4 + OpenHands, description below
## What does this PR do?
This PR refactors the test classes for 5 causal language models to inherit from the base classes CausalLMModelTester and CausalLMModelTest defined in tests/causal_lm_tester.py. This reduces code duplication and ensures consistency across... | {
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I'm consistently running into this pickle error when trying to run DeepSeek R1 models (both R1 and R1-0528):
```
Can't pickle <class 'transformers_modules.deepseek-ai.DeepSeek-R1-0528.4236a6af538feda4548eca9ab308586007567f52.configuration_deepseek.DeepseekV3Config'>:
it's not the same object as transfo... | {
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It wrote the description below as well:
## What does this PR do?
This PR refactors the DBRX model tests to use the CausalLMModelTester and CausalLMModelTest base classes from tests/causal_lm_tester.py, fol... | {
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`Gemma3IntegrationTest` is never actually run. Before #36820, no access to gated repo. Before #38093, `@require_read_token` didn't work on test class.
All tests are now passing on T4 (with torch 2.7) and A10 (with torch 2.6) - if not skipped by the conditions | {
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https://api.github.com/repos/huggingface/transformers/issues/38470 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38470/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38470/comments | https://api.github.com/repos/huggingface/transformers/issues/38470/events | https://github.com/huggingface/transformers/pull/38470 | 3,099,960,662 | PR_kwDOCUB6oc6YGjG- | 38,470 | Add detailed ConvBERT model card with usage, architecture, and refere… | {
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This PR adds a detailed and standardized model card for **ConvBERT** to improve Hugging Face Transformers documentation.
Includes:
- Model Overview and Architecture
- Training objective and dataset details
- Use cases and limitations
- Code usage examples via `pipeline`, `AutoModel`,... | null | {
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Pins Scippy to fix the batch of `TypeError: gaussian_filter() got an unexpected keyword argument 'axes'` issues.
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Ascend NPU
transformers>=4.50.0
torch 2.1
### 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 dataset (give details bel... | {
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As per title + some clean up on generation tests
Didn't expect this PR to grow so large. Now all vision LLMs can accept `inputs_embeds` as an input along with `pixel_values`. The tests are all passing on my end | {
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"merged_at... | # What does this PR do?
Fixes #36254
And this PR makes it possible to infer bnb-4bit Flux with hqq-4bit quantized T5 model in the diffusers pipeline.
I uploaded models to [HighCWu/FLUX.1-dev-bnb-hqq-4bit](https://huggingface.co/HighCWu/FLUX.1-dev-bnb-hqq-4bit).
I use hqq-4bit to quantize T5. It seems to qua... | {
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# What does this PR do?
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Ran into this bug https://github.com/huggingface/transformers/issues/38329. Tried installing from main to get access to this fix https://github.com/huggingface/transformers/pull/38376, but ran into this bug
```
(python) MacBookPro~/projects/bastet[embedding_app_python L|✚2…1] % python3 embeddingApp/em... | {
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transformers==4.51.3
Ascend 910B
torch==2.5.1
torch-npu==2.5.1
### 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 dat... | {
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"merged_at... | This PR adds support for `GLPNImageProcessorFast`, enabling fast inference for the GLPN model using TorchVision backends.
**Changes:**
- Added `GLPNImageProcessorFast` implementation in `image_processing_glpn_fast.py`.
- Updated `__init__.py` to include the new fast processor in `import_structure`.
- Verified fun... | {
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"merged_at... | Summary
This PR adds a fast image processor for the GLPN model (GLPNImageProcessorFast) using the PyTorch/TorchVision backend. This brings improved performance for inference workflows using GLPNModel and aligns with fast processor support across other vision models in the library.
Changes
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- Use dict comprehension to create dict e9c081ffe9436f65c310fe301da80f31fe4b6b06
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torch.get_default_device() is not an official PyTorch API (even in 2.2), but it’s being called inside modeling_utils.py in version 4.52.1.
get_torch_context_manager_or_global_device() function is calling the following API
Error - Exception : module 'torch' has no attribute 'get_default_device'
### W... | {
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We did not yet publish this API in a major release, and we have changed the name | {
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When trying to quantize w/ torchao on 4.52.3 and not having bits and bytes installed I am getting:
```Py
python ao/prep_model.py --model_name "facebook/opt-125m" --quant_type "fp8" --granularity per_row --push_to_hub True
Using Model name: facebook/opt-125m
Quantization type: fp8
Loading and quantizi... | {
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Fixes a dtype mismatch in **Qwen2.5-Omni** models when Flash Attention is enabled:
`sin` and `cos` positional embeddings are now explicitly cast to the same dtype as the working tensor.
**Related issue:** [#38451](https://github.com/huggingface/transformers/issues/38451)
Thanks @zucc... | {
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] | open | false | null | [] | null | [] | 2025-05-28T18:58:52 | 2025-05-29T12:38:15 | null | NONE | null | null | null | null | ### Feature request
In [`loss_utils.py`](https://github.com/huggingface/transformers/blob/main/src/transformers/loss/loss_utils.py), logits are upcasted for float32 for some losses. This can waste memory for cases where certain labels are `ignore_index`. This is especially true for fine tuning cases where one chooses ... | null | {
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File: modeling_qwen2_5_omni.py
```
def _apply_rotary_pos_emb_flashatt(self, tensor: torch.Tensor, freqs: torch.Tensor) -> torch.Tensor:
tensor_ = tensor.float()
cos = freqs.cos() # .type_as(tensor_)
sin = freqs.sin() # .type_as(tensor_)
output = apply_rotary_emb(tensor_, co... | {
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Hi 🤗 team and contributors,
I'm currently exploring ways to extend the `transformers` library to support **temporal grounding** — the task of identifying a [start, end] timestamp segment in a video given a natural language query.
While Hugging Face already supports pipelines like `video-classifi... | null | {
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"merged_at... | ## Summary
Fixes a TypeError in the `save_pretrained` error handling routine that occurs when `shared_names` contains shared tensors.
## Problem
In `src/transformers/modeling_utils.py` line 3747, the code attempts to call `set(shared_names)` where `shared_names` is `List[Set[str]]`. This raises:
TypeError: ... | {
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I check the shape of the inputs and find follows:
In [1]: logits.shape
Out[1]: torch.Size([4, 896, 152064])
In [2]: labels.shape
Out[2]: torch.Size([4, 896])
In [3]: num_items_in_batch
Out[3]: 4390
Why is 439... | {
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`next_token` was set but not propagated correctly to the `GenerationOutput`, thus making streaming non-functional.
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"merged_at... | # What does this PR do?
Allows for multi-turn style requests in continuous batching. Cache is retained and has to be manually cleared by the owner of the `ContinuousBatchingManager` instance.
For power users mostly.
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"merged_at... | ## Summary
Addresses issue #38318 by adding configurable normalization schemes to SigLIP image processors, allowing users to choose between official SigLIP normalization and traditional ImageNet normalization while maintaining full backwards compatibility.
## Problem
Users reported that SigLIP models may perfo... | null | {
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"merged_at... | This PR splits the `transformers chat` frontend from its backend (now moved to `transformers serve`).
We take this opportunity to have `transformers serve` act as a server with an OpenAI-compatible API, via http, using SSE to stream tokens.
You can take it for a spin either by spawning a server:
```
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It's not uncommon to define new special tokens in the tokenizer at fine-tuning time. e.g. for rounds of conversations in a chat LLM. However, this is a source of misalignment: the tokenizer and the model configs (`model.config` and `model.generation_config`) may have different special tokens,... | {
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https://github.com/huggingface/transformers/blob/badc71b9f604ca910bb87a43979c795eaf6e7d64/src/transformers/quantizers/quantizer_hqq.py#L74-L75
However the original HQQ library also runs on CPU, by falling back to default aten operators: https://github.com/mobiusml/hqq?tab=read... | {
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This enables the following:
```py
[...]
manager: ContinuousBatchingManager = model.init_continuous_batching(
generation_config=generation_config,
streaming=True
)
manager.start()
for result in manager:
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Let's bring the documentation to all the Romanian-speaking community 🌐
Who would want to translate? Please follow the 🤗 [TRANSLATING guide](https://github.com/huggingface/transformers/blob/main/docs/TRANSLATING.md). Here is a list of the files ready for translation. Let us know in this issue if you'd like to t... | null | {
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As per title, skips the test unless all sub-models support flex attn. Some models didn't have the flag set even though they can support Flex attn, this PR goes over all recent;y refactored vision models and sets the flags to `True`. Flex attention tests are passing for all models (except Zamb... | {
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There are some models such as idefics 2+3, smolvlm which do not have the `_is_composite` flag and as I do not want to affect other tests - so,... | {
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This PR does the following:
- Move `FlashAttentionKwargs` and `ForCausalKwargs` to `generic` folder
- Better handle kwargs check for gradient accumulation ( now we also check that we have the LossKwargs typing, otherwise, we disable the fix)
- Extend forward function with `LossKwargs` typ... | null | {
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2. This PR has completed the refactoring of the related modules. Due to the overlap of F definitions (torch and torchvision), image_processors and videos_processors have not been placed u... | {
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https://api.github.com/repos/huggingface/transformers/issues/38430 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38430/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38430/comments | https://api.github.com/repos/huggingface/transformers/issues/38430/events | https://github.com/huggingface/transformers/pull/38430 | 3,096,736,741 | PR_kwDOCUB6oc6X7l-i | 38,430 | [seamless_m4t] Skip some tests when speech is not available | {
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https://api.github.com/repos/huggingface/transformers/issues/38429 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38429/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38429/comments | https://api.github.com/repos/huggingface/transformers/issues/38429/events | https://github.com/huggingface/transformers/pull/38429 | 3,096,618,431 | PR_kwDOCUB6oc6X7MXH | 38,429 | Update error when using additional and/or masks | {
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The version was correctly fixed before, but the error was not correctly updated | {
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https://api.github.com/repos/huggingface/transformers/issues/38428 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/38428/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/38428/comments | https://api.github.com/repos/huggingface/transformers/issues/38428/events | https://github.com/huggingface/transformers/issues/38428 | 3,096,566,930 | I_kwDOCUB6oc64kdyS | 38,428 | [Question] The logic of data sampler in data parallel. | {
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When reading the source code of transformers, I cannot understand the implementation of `_get_train_sampler` in `trainer.py`. Why the default data sampler is `RandomSampler` rather than `DistributedSampler`? How does the trainer handle the sampler for data parallel?
reference code: http... | {
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