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] | open | false | null | [] | null | [] | 2025-07-15T18:15:51 | 2025-09-23T17:18:11 | null | NONE | null | null | null | null | ### Feature request
**Summary**
I would like to propose a feature to enable **per-token latency tracking** during generation in Hugging Face’s `generate()` (via _beam_search, sample etc) loop. This is extremely useful for benchmarking models across hardware (e.g. CPU vs GPU, Arm vs x86), identifying bottlenecks, and ... | null | {
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- `transformers` version: 4.54.0.dev0
- Platform: macOS-15.5-arm64-arm-64bit
- Python version: 3.11.11
- Huggingface_hub version: 0.30.2
- Safetensors version: 0.5.3
- Accelerate version: 1.6.0
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (accelerator?): 2.9.0.de... | {
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"merged_at... | # What does this PR do?
Fixes #39365. Not a fix yet but introducing a unit test failing for the reason explained in this issue. Either the inputs are wrong, either the fix from issue #39365 is needed.
## 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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This PR:
- Adds `/v1/audio/transcriptions`, the speech to text (transcription) OAI API
- Adds `TimedModel`: models get deleted from memory after a certain amount of time (e.g try launching the server as `transformers serve --enable-cors --log-level debug --model-timeout 10`) | {
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The placeholders logic in auto_docstring seems to be broken currently, so that placeholders like {image_processor_class} are not replaced properly.
This PR simplifies greatly the logic and fixes the issue | {
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Fixes an AttributeError caused by attempting to access generation_kwargs from a GenerationConfig object in `convert_janus_weights_to_hf.py`.
When running the conversion script, the following error occurs:
```bash
Traceback (most recent call last):
File "/home/infidea/xxx/code/tmp/tr... | {
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Fixes [integration tests](https://github.com/huggingface/transformers/actions/runs/16282903241/job/45976159004) for EnCodec, which were all failing:
- Two because of mismatch with expected output
- One doesn't even compute outputs because of bad padding
```
FAILED tests/models/encodec/tes... | {
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We (BUT Speech@FIT) have recently developed DiCoW (Diarization-Conditioned Whisper), a target-speaker ASR model that enhances OpenAI’s Whisper by integrating speaker diarization for multi-talker, speaker-attributed ASR.
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"merged_at... | # What does this PR do?
Adds mistral's audio-text-to-text model 🤗
## EVALS
Ran transcriptions mode eval on librispeech test-clean ([this gist](https://gist.github.com/eustlb/fc899dd9ff7fe357065c35cb0120d145))
- 3B: 1.9% wer
- 24B: 1.6% wer
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- Fixed subject-verb agreement and pluralization issues.
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- Simplified the explanatio... | {
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When using the `google/gemma-3-1b-it`, I run into frequent recompilation issues, eventually resulting in the following error message:
```
torch._dynamo.exc.FailOnRecompileLimitHit: recompile_limit reached with one_graph=True. Excessive recompilations can degrade performance due to the compilation over... | {
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it seems to me that would be possible with a little modification in the function post_process_object_detection
with
```
``for score, label, box, index in zip(scores, labels, boxes, indexes):
results.append(
{
"scores": score[score > threshold],
... | null | {
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https://api.github.com/repos/huggingface/transformers/issues/39424 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39424/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39424/comments | https://api.github.com/repos/huggingface/transformers/issues/39424/events | https://github.com/huggingface/transformers/issues/39424 | 3,232,079,234 | I_kwDOCUB6oc7ApZ2C | 39,424 | [YosoConfig] Missing `architectures` field | {
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This issue tracks the fix to add the following field to:
📄 `src/transformers/models/yoso/configuration_yoso.py`
```python
architectures = ["YosoForMaskedLM"]
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A few issues:
- the checks and attention switch should be performed recursively for all submodels, not only the "top-most" model
- flash can dispatch even with cpu/disk offloading, as the module is put back on device prior to computation
- some models with the old class attention interface... | {
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https://api.github.com/repos/huggingface/transformers/issues/39422 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39422/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39422/comments | https://api.github.com/repos/huggingface/transformers/issues/39422/events | https://github.com/huggingface/transformers/pull/39422 | 3,231,927,121 | PR_kwDOCUB6oc6e-H-4 | 39,422 | refactor: remove `set_tracer_provider` and `set_meter_provider` calls | {
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As we are a library, we shouldn't set an OT tracer or a meter, given you can only set one per application.
Removing calls to `set_{tracer|meter}_provider`.
Closes #39115, #39143 | {
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>
>
>
> The issue was solved in [#30068](https://github.com/huggingface/transformers/pull/30068). You can install transformers from `main` with the following line for the correct generation with assisted decoding:
>
>
>
> `!pip install --upgrade git+https://github.com/huggingface/transformers.... | {
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As per title, I think these are quite common to be in the auto docstring
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Another day, another tool: when adding a model, tests fail as they should, and sometimes `test_modeling_common` feels irreconcilable with the peculiarities of our brand new model. But how can we be sure we're not breaking everything by adding a seemingly innocent `skip`?
Well I'm not 100% ... | {
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"merged_at... | This PR adds the missing `architectures` field to the `YosoConfig` class, as part of the issue [#39208](https://github.com/huggingface/transformers/issues/39208).
**Added:**
```python
architectures = ["YosoForMaskedLM"]
```
This helps ensure proper model auto-mapping and improves consistency across configurati... | {
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https://api.github.com/repos/huggingface/transformers/issues/39416 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39416/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39416/comments | https://api.github.com/repos/huggingface/transformers/issues/39416/events | https://github.com/huggingface/transformers/pull/39416 | 3,231,548,759 | PR_kwDOCUB6oc6e81lq | 39,416 | fix `kyutai` tests | {
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"merged_at... | # What does this PR do?
> HF_HOME=/mnt/cache HF_HUB_READ_TOKEN=hf_XXX RUN_SLOW=1 python3 -m pytest -v --flake-finder --flake-runs=10 tests/models/kyutai_speech_to_text/test_modeling_kyutai_speech_to_text.py::KyutaiSpeechToTextForConditionalGenerationIntegrationTests::test_generation_batched
It might be from a n... | {
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https://api.github.com/repos/huggingface/transformers/issues/39415 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39415/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39415/comments | https://api.github.com/repos/huggingface/transformers/issues/39415/events | https://github.com/huggingface/transformers/pull/39415 | 3,231,153,479 | PR_kwDOCUB6oc6e7fhS | 39,415 | [chat template] add a testcase for kwargs | {
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Just adds a testcase, I didn't know this was supported and I don't want it to break in the future | {
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https://api.github.com/repos/huggingface/transformers/issues/39414 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39414/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39414/comments | https://api.github.com/repos/huggingface/transformers/issues/39414/events | https://github.com/huggingface/transformers/pull/39414 | 3,231,031,605 | PR_kwDOCUB6oc6e7E20 | 39,414 | Fix typo in `/v1/models` output payload | {
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"merged_at... | # What does this PR do?
This PR fixes a typo affecting the output payload of the `/v1/models` endpoint in `transformers serve`.
## 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://git... | {
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https://api.github.com/repos/huggingface/transformers/issues/39413 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39413/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39413/comments | https://api.github.com/repos/huggingface/transformers/issues/39413/events | https://github.com/huggingface/transformers/issues/39413 | 3,230,706,385 | I_kwDOCUB6oc7AkKrR | 39,413 | Exeception 3 type mismatch | {
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[https://github.com/huggingface/transformers/blob/6017f5e8ed33d48096cdf8630d1cc7cbf2550c90/src/transformers/generation/utils.py#L482](url)
The type of cache_position[-1] and input_ids.shape[1] do not match to compare. One is tensor and the other is int
### Who can help?
_No response_
### Informatio... | {
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https://api.github.com/repos/huggingface/transformers/issues/39412 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39412/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39412/comments | https://api.github.com/repos/huggingface/transformers/issues/39412/events | https://github.com/huggingface/transformers/pull/39412 | 3,230,606,872 | PR_kwDOCUB6oc6e5olp | 39,412 | use the enable_gqa param in torch.nn.functional.scaled_dot_product_at… | {
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"merged_at... | …tention
the GQA could be accelerated in torch.nn.functional.scaled_dot_product_attention. this pytorch api offer a param to enable gqa. see https://docs.pytorch.org/docs/2.7/generated/torch.nn.functional.scaled_dot_product_attention.html#torch-nn-functional-scaled-dot-product-attention | {
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https://api.github.com/repos/huggingface/transformers/issues/39411 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/39411/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/39411/comments | https://api.github.com/repos/huggingface/transformers/issues/39411/events | https://github.com/huggingface/transformers/pull/39411 | 3,230,536,562 | PR_kwDOCUB6oc6e5ZtG | 39,411 | set document_question_answering pipeline _load_tokenizer to True | {
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"merged_at... | Hi @Rocketknight1 . The document-question-answering pipeline requires a tokenizer in the preprocessing step.
script: [impira/layoutlm-document-qa](https://huggingface.co/impira/layoutlm-document-qa)
```python
from transformers import pipeline
nlp = pipeline(
"document-question-answering",
model="impir... | {
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I recieve message "ValueError: The model you are trying to fine-tune is quantized with QuantizationMethod.FP8 but that quantization method do not support training. Please open an issue on GitHub: https://github.com/huggingface/transformers to request the support for training support for Quantizatio... | null | {
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```
!pip install bitsandbytes==0.45.0 --upgrade
!pip install insightface --upgrade
!pip install huggingface_hub==0.25.1 hf_transfer diffusers==0.31.0 transformers==4.36.0
!pip uninstall xformers triton --yes
!pip install torch==2.2.0+cu121 to... | {
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Looking at https://github.com/huggingface/transformers/commit/6017f5e8ed33d48096cdf8630d1cc7cbf2550c90
### Who can help?
@ArthurZucker
### Information
- [ ] The official example scripts
- [x] My own modified scripts
### Tasks
- [ ] An officially supported task in the `examples` folder (such as G... | {
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"merged_at... | # What does this PR do?
Updates LightGlue model card for #36979
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
## Who can review?
@stevhliu
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"merged_at... | # What does this PR do?
Updates SuperGlue model card for #36979
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
## Who can review?
@stevhliu
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Hello,
I had finetuned a model based on ESM class
https://huggingface.co/facebook/esm2_t30_150M_UR50D
at the time I had ```transformers.__version__ == '4.38.1'```
With this version, if I run the common import command
```
# Load model directly
from transformers import AutoTokenizer, AutoModelForMasked... | {
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Platform: Initially discovered on Nvidia. Can be reproduced on CPU and in Google Colab (see attached gist).
- `transformers` version: 4.53.2
- Platform: Linux-6.6.87.2-microsoft-standard-WSL2-x86_64-with-glibc2.39
- Python version: 3.12.3
- Huggingface_hub version: 0.33.4
- Safetensors version: 0.5.3
... | null | {
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"merged_at... | # What does this PR do?
This PR aims at integrating `Vocos` model to `transformers`.
Vocos is a neural vocoder designed for high quality audio synthesis in TTS pipelines and related tasks, outpeforms `HifiGan` and it is significantly faster. It has 2 main variants :
- `VocosModel` can be used as a standalone... | null | {
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"merged_at... | Draft PR for now, please don't merge!
The goal of this PR is to experiment with an `einsum` approach for `eager_attention_forward` that avoids a lot of reshapes and transposes that introduce intermediate tensors and unnecessary copies. In notebook benchmarks it seems to be 25-50% faster, but I'm making a proper PR s... | null | {
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transformers 4.53.2, Ubuntu 22.04.4, python 3.11.13
### Who can help?
@ArthurZucker and @itazap There must be a problem with the `offset_mapping` of Qwen3 `tokenizer`. The starting point in the text for each token, except the first and the last, is one position behind. I compared it with the BERT's `... | {
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transformers @ 4.53.2
### Who can help?
@amyeroberts @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, ...)
- [x] My own task or dataset (give details below)
#... | {
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- transformers version: 4.53.2
- Platform: Linux-6.11.0-29-generic-x86_64-with-glibc2.39
- Python version: 3.12.3
- Huggingface_hub version: 0.33.2
- Safetensors version: 0.5.3
- Accelerate version: 1.8.1
- PyTorch version: 2.7.1+cu128 (CUDA)
- Using distributed or parallel set-up in script?: Yes, Tens... | {
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cc @ydshieh | {
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Failing tests reported by CI bot after removing deprecations in https://github.com/huggingface/transformers/pull/38838
The main fixes are in test files and in ModernBert/Llama. The test was failing because RoPE needs to use local theta in local attention layers. I think at this point we ca... | {
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Fixes https://github.com/huggingface/transformers/issues/39389. There were two issues. First, using `getattr` on dict will never look for a dict key thus we were skipping on `token_type_ids_mask`.
Second, `kv_idx` can go beyond `token_type_ids` length because it includes the new tokens to... | {
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"merged_at... | Fixes #39392
This change improves loss calculation correctness for multi-GPU training by enabling proper token averaging across devices by default.
## What does this PR do?
Changes the default value of `average_tokens_across_devices` from `False` to `True` in `TrainingArguments`. This ensures more accurate los... | {
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Transformers version: 4.53.2
Ubuntu x86, Nvidia H100
- I've noticed previous [issue](https://github.com/huggingface/transformers/issues/38053) about bidirectional mask for image tokens and MRs fixing it merged[[1](https://github.com/huggingface/transformers/pull/38080)][[2](https://github.com/huggingf... | {
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- `transformers` version: 4.52.4
- Platform: macOS-15.5-arm64-arm-64bit
- Python version: 3.9.21
- Huggingface_hub version: 0.32.4
- Safetensors version: 0.5.3
- Accelerate version: not installed
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (GPU?): 2.6.0 (False)
-... | {
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Update SAM and SAM HQ attention implementation, and fix two lines that were causing unnecessary cuda sync when profiling with torch profiler.
Mostly split from https://github.com/huggingface/transformers/pull/32317 as PR is becoming huge | {
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Split from https://github.com/huggingface/transformers/pull/32317 as this PR is becoming huge
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ruff detects some invalid property definitions. This PR fixes them.
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Enables ruff checks and fixes some code. These checks are:
```
PERF102: Checks for uses of dict.items() that discard either the key or the value when iterating over the dictionary.
PLC1802: Checks for len calls on sequences in a boolean test context.
PLC0208: Checks for iteration over a set... | {
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Short version - processing an image alone versus in a batch with other images of different aspect ratios yields different prediction scores, even though the resolution of the image in the batch does not change (only padded pixels are added, which should be ignored with `pixel_mask`)
When using `Mask2Forme... | {
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"merged_at... | Pre-release of Apertus from the Swiss AI Initiative
Main modifications from Llama
- xIELU Activation
- QK-norm
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Fix the whole `perception_lm` test suite is failing.
Merge without waiting to make CI better | {
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N/A
### Who can help?
@ArthurZucker
### Information
- [ ] The official example scripts
- [ ] My own modified scripts
### Tasks
- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)
### Reproduction
In MllamaCross... | null | {
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Assume I have:
```python
conversation = [
{"role": "system", "content": "You are a helpful assistant"},
{"role": "user", "cont... | {
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"merged_at... | # What does this PR do?
This PR updates the Siglip2TextModel to simplify and clarify the logic for generating the pooled output. Specifically, it removes the ambiguous conditional logic and comment regarding the use of eos_token_id or padding tokens, and instead uses the last token's hidden state as the pooled represe... | {
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I attempted to use flash attention 2 with this model but it seems like it isn't supported, based on this error:
```
ValueError: LLaDAModelLM does not support Flash Attention 2.0 yet. Please request to add support where the model is hosted, on its model hub page: https://huggingface.co/GSAI-ML/LLaDA-8B-Instru... | {
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"merged_at... | # What does this PR do?
Ensures correct default value for `do_convert_rgb` parameter is set otherwise lm-eval on this model results in "ValueError: Unable to infer channel dimension format".
This patch is needed in conjunction with https://github.com/huggingface/transformers/pull/39375 for lm-eval to work on this mo... | {
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Sets the default value for optional parameter `do_convert_rgb` to True as described in the class definition in Line 81.
Otherwise, lm-eval on this model results in "ValueError: Unable to infer channel dimension format."
## Before submitting
- [ ] This PR fixes a typo or improves the doc... | {
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This allows an ImageTextToTextPipeline object to handle a user-defined generation_config passed to the pipeline, the same way a TextGenerationPipeline object does. Currently, it ignores these generation_config parameters set on pipeline object initialization, causing unexpected text generatio... | {
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"merged_at... | # What does this PR do?
The `quantization_method` attribute was not being deleted during model dequantization, causing methods like `to()` to fail even when the operation should be valid for dequantized models.
Fixes # 39295
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss... | {
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# What does this PR do?
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Adds config options for mixed precision and fp8 config, which are supported in accelerate's Accelerator object.
Also parses the `config` field for the torchao ("AO") fp8 backend from dictionary values into the required `Float8LinearConfig` object.
This requires also a simple gating chan... | {
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The script was failing to apply fixes because of a mismatch in how it reads the docstring for comparison versus how it reads it for replacement.
- To detect a mismatch, the script reads the docstring from the `obj.__doc__` attribute. Python automatically un-indents the string provided by `_... | {
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### What's included:
- Friendly, accessible model description
- Pipeline usage example for ... | {
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Enabling setting an api-key when serving in a way that's compatible with the openai api.
### Motivation
This would be a great feature to make our endpoint accessible over the internet.
### Your contribution
I'm not sure where to start to make a PR for this. Any pointer? | null | {
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**Note**: I need to load this model without vLLM because I may need to... | null | {
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In [sdpa_forward_attention](https://github.com/huggingface/transformers/blob/main/src/transformers/integrations/sdpa_attention.py#L44),
we have this:
```python
if attention_mask is not None and attention_mask.ndim == 4:
attention_mask = attention_mask[:, :, :, : key.shape[-2]]
```
In [eager_atten... | null | {
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@stevhliu @thomwolf | {
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Fix an issue raised here https://github.com/huggingface/transformers/pull/39172#issuecomment-3052873789
After internal discussions with @ydshieh , we found that the issue is not due to class attributes, but to lists/dicts being passed around without being copied.
In fact the same issue is ... | {
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The value is changed after #39120 but remain reasonable. Not sure the root reason why this might be changed though | {
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Following up on #39164 lazy init is not really an option for now so for CB we need to make sure we init the cache properly | {
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2 times facing the link error -> time to update it on main | {
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- `transformers` version: 4.53.1
- Platform: Linux-6.8.0-62-generic-x86_64-with-glibc2.35
- Python version: 3.12.11
- Huggingface_hub version: 0.33.2
- Safetensors version: 0.5.3
- Accelerate version: 1.8.1
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (accelerato... | {
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<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
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"merged_at... | What does this PR do?
This PR updates the class docstring example for a multimodal model, addressing the following issues:
Corrects the input type: Changes the model input from a list to a tensor, aligning with model requirements.
Properly handles image input: Adds the image to the model input for correct multim... | null | {
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"merged_at... | Fix example: resolve input, image, and processor usage issues
- Changed input from list to tensor to match model requirements.
- Added image to model input to enable correct multimodal inference.
- Replaced tokenizer with processor for proper multimodal preprocessing.
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"merged_at... | Fix example: input should be tensor, and image was missing in model input
- Correct input type from list to tensor.
- Ensure image is properly passed to the model.
# What does this PR do?
This PR fixes two issues in the example code provided in the class docstring:
Input Type Correction:
The example in the ... | {
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Fixes # (issue)
Fixes the issue of Colpali not working sincer the breaking changes with VLMs in 4.52.
Most models were converted, not the native HF colpali making the code in docs here fail: https://huggingface.co/docs/transformers/model_doc/colpali.
@yonigozlan @zucchini-nlp
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I'm using @xenova/transformers in a browser-based transcription app. I noticed that when I set:
env.useBrowserCache = true , it introduces multiple bugs : the main one being a JSON parsing error during or after model loading. Due to this, I have to set
env.useBrowserCache = false;
which fixes the errors, but i... | {
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Fixes # (issue)
gpt2 usage doc can not execute rightly
@stevhliu
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). | {
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surpport for google/medgemma-27b-it
### Open source status
- [x] The model implementation is available
- [x] The model weights are available
### Provide useful links for the implementation
surpport for google/medgemma-27b-it | null | {
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Fix the csm model(text_to_audio) cannot work with pipeline mode.
example:
```
import torch
from transformers import pipeline
device = "hpu"
if torch.cuda.is_available():
device="cuda"
print(f"device: {device}")
tts_pipeline = pipeline(
"text-to-audio",
model="sesame... | {
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As per title, reported by @ydshieh internally
(how many more models we have that load a VLM internally 🥲 ) | {
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`audio_utils.py` still uses `np.lib.pad` from numpy 1.X rather than `np.pad`. This fixes the single remaining call in `transformers` to use `np.pad`.
## Who can review?
cc: @ArthurZucker, @Rocketknight1
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Fixes a typo in the docs
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Update OLMoE card
Unfortunately my computer do not have enough power to run the code and Colab too, making it a draft until I try a smaller OLMoE.
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These tests are not slow and don't require GPUs, but they're being flaky on the CI setup. This PR tags them as slow to unblock CI. | {
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**TL;DR**
`PreTrainedModel` now mixes in `EmbeddingAccessMixin` providing default
`get_input_embeddings` / `set_input_embeddings` / `get_output_embeddings` / `set_output_embeddings` for all models. These methods should be removed from the codebase unless exceptionally weird.
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To be merged into #39155
### Testing
Works with the [OpenAI responses starter app](https://github.com/openai/openai-responses-starter-app/):
1. launch server as `transformers serve --force-model HuggingFaceTB/SmolLM3-3B`
2. launch app as `OPENAI_API_KEY="<KEY>" OPENAI_BASE_URL=http:/... | {
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With verion of transfomers == 4.53.0
Script: https://github.com/huggingface/smollm/blob/main/vision/finetuning/SmolVLM2_Video_FT.ipynb
This script for tuning SmolVLM2 on video undrestanding causing CUDA out of memory problem.
While this script on the same hardware with transformers == 4.51.3 is worki... | {
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