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Adds `--gradient_accumulation_steps` argument to the image classification no_trainer example script, addressing issue #18436.
## Motivation
Gradient accumulation allows training with larger effective batch sizes by accumulating gradients over multiple batches before performing an optim... | null | {
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transformer version: latest commit
in file: https://github.com/huggingface/transformers/blob/main/src/transformers/utils/auto_docstring.py#L1121 (and any other files using emoji symbols)
This "🚨" symbol cause encoding error as the system charset is not UTF-8 encoded. (especially on Windows, the UTF... | null | {
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Hi this is using TRL but it seems like a lower level issue.
I'm training a variant of Qwen3 (Intern-S1-mini) but I'm not using the vision tower so it's effectively Qwen3-8B. I've been doing finetuning and checking different attention implementations i.e. SPDA vs. Flash Attention 2. However, I've been... | null | {
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Failed to parse argument "include_num_input_tokens_seen" using HfArgumentParser, code is unusable.
error: argument --include_num_input_tokens_seen/--include-num-input-tokens-seen: Truthy value expected: got non_padding but expected one of yes/no, true/false, t/f, y/n, 1/0 (case insensitive).
### Who ... | null | {
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Fix small typo. Without consequences, but still confusing.
Fixes https://github.com/huggingface/transformers/issues/41919 | null | {
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This PR adds graceful fallback to slow tokenizers when `AutoTokenizer.from_pretrained()` with `use_fast=True` fails at runtime. Subsequently, this PR should improve robustness issue in tokenizer loading
## Problem
Currently, when `use_fast=True` is specified but the fast tokenizer fails... | null | {
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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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Why:
Without this, the constant isn’t exported when using
from transformers.utils.constants import *.
Impact:
- Keeps the constants module consistent.
- No functional changes or breaking impact. | null | {
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transformers version: 4.57.1
python version: 3.11
### Who can help?
@Cyrilvallez @eustlb
### Information
- [x] The official example scripts
- [ ] My own modified scripts
### Tasks
- [x] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset ... | null | {
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Related to https://github.com/huggingface/transformers/pull/41922, this PR corrects the assignment of the `rope_scaling` dictionary present on some Gemma 3 pre-trained models on HF Hub when normalizing to the new `rope_parameters` value.
## Before submitting
- [ ] This PR fixes a typo or ... | null | {
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This PR fixes an issue where quantized models (e.g., RedHatAI/Qwen2.5-VL-7B-Instruct-quantized.w8a8) fail to load due to a dtype incompatibility during weight initialization.
Problem
When loading quantized models (dtype=torch.int8), the method _load_pretrained_model() still calls initialize_w... | null | {
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It prevents import errors during dependency checks and allows transformers to load normally.
Changes made:
- Updated `setup.py` to conditionally check for safetensors
- Improved dependency handling logic
Tested locally: verified th... | null | {
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```
1.tests/models/video_llama_3/test_modeling_video_llama_3.py::VideoLlama3IntegrationTest::test_small_model_integration_test
2.tests/models/video_llama_3/test_modeling_video_llama_3.py::VideoLlama3IntegrationTest::test_small_model_integration_test_batch_wo_ima
ge
3... | null | {
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Should fix #41929 . The `check_model_inputs` / `can_record_outputs` interaction is not always trivial and models with several entrypoints such as `VisionModel` vs `VisionTransformer` are missing some, adding it here. Also added a modification in `generic` to make sure the flag was captured, n... | null | {
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macos 26.0
python 3.10
pytorch 2.7.1
transformers 4.57.1
### Who can help?
@yonigozlan @molbap
### 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... | null | {
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"merged_at... | - Add clear error message when mistral-common is missing for AutoTokenizer loading Voxtral
- Add unit test
# What does this PR do?
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"merged_at... | Fixing a few deepspeed tests
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https://api.github.com/repos/huggingface/transformers/issues/41924 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/41924/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/41924/comments | https://api.github.com/repos/huggingface/transformers/issues/41924/events | https://github.com/huggingface/transformers/issues/41924 | 3,563,519,251 | I_kwDOCUB6oc7UZv0T | 41,924 | `output_attentions=True` always warns for non-`"eager"` attention implementations, even when a custom AttentionInterface backend does return attention weights | {
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- `transformers` version: 4.57.1
- Platform: Linux-5.10.233-223.887.amzn2.x86_64-x86_64-with-glibc2.26
- Python version: 3.10.19
- Huggingface_hub version: 0.36.0
- Safetensors version: 0.6.2
- Accelerate version: not installed
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch... | null | {
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https://api.github.com/repos/huggingface/transformers/issues/41923 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/41923/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/41923/comments | https://api.github.com/repos/huggingface/transformers/issues/41923/events | https://github.com/huggingface/transformers/pull/41923 | 3,563,463,159 | PR_kwDOCUB6oc6wPhqk | 41,923 | fix some ut failures on XPU w/ torch 2.9 | {
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"merged_at... | cases are below, all passed. @ydshieh , pls help review, thx very much.
> tests/models/aya_vision/test_modeling_aya_vision.py::AyaVisionIntegrationTest::test_small_model_integration_generate_text_only
> tests/models/aya_vision/test_modeling_aya_vision.py::AyaVisionIntegrationTest::test_small_model_integration_forwa... | {
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"merged_at... | # What does this PR do?
Fixes the rope_parameters in the weights conversion script for Gemma 3.
These should be:
```
local => default @ 10_000.0
global => linear(8.0) @ 1_000_000.0
``` | null | {
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"merged_at... | If run below 2 cases on 2 accelerators:
> pytest -rA tests/models/speech_to_text/test_modeling_speech_to_text.py::Speech2TextModelIntegrationTests::test_generation_librispeech
>pytest -rA tests/models/speech_to_text/test_modeling_speech_to_text.py::Speech2TextModelIntegrationTests::test_generation_librispeech_bat... | null | {
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https://api.github.com/repos/huggingface/transformers/issues/41920 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/41920/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/41920/comments | https://api.github.com/repos/huggingface/transformers/issues/41920/events | https://github.com/huggingface/transformers/pull/41920 | 3,562,379,835 | PR_kwDOCUB6oc6wL7Po | 41,920 | evaluate>=0.4.6 is needed | {
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"merged_at... | Some HF Transformers tests/examples fail with main and `evaluate < 0.4.6`
Fixing:
```
stderr: [rank0]: Traceback (most recent call last):
stderr: [rank0]: File "/code/users/stas/github/transformers-alst-integration/examples/pytorch/question-answering/run_qa.py", line 692, in <module>
stderr: [rank0]: main(... | {
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In LFM2-VL image_processing_lfm2_vl_fast.py line 212 following the MEAN and STD from imagenet is used for preprocessing.
However it seems like they are swapped:
image_mean = IMAGENET_STANDARD_STD
image_std = IMAGENET_STANDARD_MEAN
or is this correct ?
### Who can help?
@Cyrilvallez
### Inf... | null | {
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Refactor `test_tensor_parallel.py` by removing `subprocess`. This way we can easily debug with breakpoint the test if it fails. On top of that, I made the tests more robust by testing on more than `--nproc_per_node> 2.` `--nproc_per_nodes = 8` crashes because the llama model we use is too ti... | null | {
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"merged_at... | # What does this PR do?
- TODO:
- update my branch
- explain changes
## Who can review?
Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.
@ArthurZucker @Cyrilvallez
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- `transformers` version: 4.57.1
- Platform: macOS-26.0.1-arm64-arm-64bit
- Python version: 3.12.0
- Huggingface_hub version: 0.35.3
- Safetensors version: 0.5.3
- Accelerate version: 1.7.0
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (accelerator?): 2.6.0 (NA)
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