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https://api.github.com/repos/huggingface/transformers/issues/37111 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37111/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37111/comments | https://api.github.com/repos/huggingface/transformers/issues/37111/events | https://github.com/huggingface/transformers/pull/37111 | 2,958,673,707 | PR_kwDOCUB6oc6QrxX1 | 37,111 | Add Fast Image Processor for MobileNetV1 | {
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- `transformers` version: 4.49.0
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- DeepSpeed version: 0.15.4
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https://api.github.com/repos/huggingface/transformers/issues/37109 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37109/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37109/comments | https://api.github.com/repos/huggingface/transformers/issues/37109/events | https://github.com/huggingface/transformers/pull/37109 | 2,958,651,638 | PR_kwDOCUB6oc6QrtHO | 37,109 | Fix Gemma3 embedding scaling | {
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- Correctly apply embedding scaling per [official Gemma 3 impl](https://github.com/google-deepmind/gemma/blob/ebfa2c2bddcab1d7cc38b1dca0fe6d98e6e7df71/gemma/modules.py#L93-L96) (cast scale to BF16). Gemma 2 has this done in #29402
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cc @yonigozlan | {
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The `TASK_MAPPING` dictionary, mapping pipeline tags to the list of architectures that support that task, is missing the new [image-text-to-text pipeline tag](https://huggingface.co/models?pipeline_tag=image-text-to-text). This PR simply adds that missing one.
## Before submitting
- [ ]... | {
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https://api.github.com/repos/huggingface/transformers/issues/37106 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37106/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37106/comments | https://api.github.com/repos/huggingface/transformers/issues/37106/events | https://github.com/huggingface/transformers/pull/37106 | 2,958,056,506 | PR_kwDOCUB6oc6QqFSd | 37,106 | Add Sdpa Support: `[Electra]` | {
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To bake Sdpa support into `transformers` for Google's Electra.
### Motivation
Towards [#28005](https://github.com/huggingface/transformers/issues/28005),
To extend support for PyTorch's Scaled Dot Product Attention across model architectures listed in transformers, including Electra, enabling f... | null | {
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This PR updates the model-card for the `dinov2` model, as described in #36979, in an attempt to standardize all model-cards.
## 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?
Anyone in t... | {
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- `transformers` version: 4.50.0
- Platform: Linux-4.18.0-553.40.1.el8_10.x86_64-x86_64-with-glibc2.28
- Python version: 3.12.8
- Huggingface_hub version: 0.28.0
- Safetensors version: 0.5.2
- Accelerate version: 1.5.2
- Accelerate config: not found
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This PR updates the model-card for the GPT2 model, as described in https://github.com/huggingface/transformers/issues/36979, in an attempt to standardize all model-cards.
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the c... | {
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https://api.github.com/repos/huggingface/transformers/issues/37098 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37098/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37098/comments | https://api.github.com/repos/huggingface/transformers/issues/37098/events | https://github.com/huggingface/transformers/issues/37098 | 2,957,719,129 | I_kwDOCUB6oc6wSzZZ | 37,098 | Feature Request: Support Canary Models | {
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Add support for Canary Flash (1B/180M) models:
https://huggingface.co/nvidia/canary-1b-flash
https://huggingface.co/nvidia/canary-180m-flash
### Motivation
The 1B model is the second highest on the [Open ASR Leaderboard](https://huggingface.co/spaces/hf-audio/open_asr_leaderboard), outperformed... | null | {
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https://api.github.com/repos/huggingface/transformers/issues/37097 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37097/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37097/comments | https://api.github.com/repos/huggingface/transformers/issues/37097/events | https://github.com/huggingface/transformers/pull/37097 | 2,957,709,881 | PR_kwDOCUB6oc6QpBVM | 37,097 | Merge tensor operations with device transfer operations | {
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https://api.github.com/repos/huggingface/transformers/issues/37095 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37095/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37095/comments | https://api.github.com/repos/huggingface/transformers/issues/37095/events | https://github.com/huggingface/transformers/pull/37095 | 2,957,344,327 | PR_kwDOCUB6oc6QnxlP | 37,095 | handle training summary when creating modelcard but offline mode is set | {
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When using the trainer with HF_HUB_OFFLINE=1, I get this stack trace due to an unhandled edge case
```
/root/miniconda3/envs/py3.11/lib/python3.11/site-packages/transformers/trainer.py:4665: in create_model_card
training_summary = TrainingSummary.from_trainer(
/root/miniconda3/envs/py... | {
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Following https://github.com/huggingface/transformers/issues/36978:
This pull request introduces a new fast image processor for EfficientNet models and integrates it into the existing codebase. The changes include updates to documentation, initialization files, and test cases to support the ... | null | {
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taras1
### Open source status
- [x] The model implementation is available
- [x] The model weights are available
### Provide useful links for the implementation
<potentially malicious link removed - matt> | {
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PoC of Integrating kernels into the llama model. The kernels used are for `attn`, `mlp`, and `rmsnorm` | {
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kenlm has issue, an PR is not merged yet
https://github.com/kpu/kenlm/pull/464
Let's use kenlm@git+https://github.com/ydshieh/kenlm@master | {
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- The AUR package downloads the source from the rel... | {
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This PR adds a new model documentation file for ViTPose, following the standardized doc format seen in models like BERT
<!--
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 m... | {
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#36824
Add [Ovis2](https://github.com/AIDC-AI/Ovis) to Transformers.
## 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.
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### **Issue Title**: Support for `llava_mistral` Model Architecture
---
### **Environment Information**
- **Transformers Version**: `<4.51.0dev0>`
- **Python Version**: `3.10.16'
- **OS**: 'Ubuntu 20.04.02'
- **PyTorch Version**: `2.5.1`
- **CUDA Version**: `11.8`
- **GPU**: `A4000`
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Fix following https://github.com/huggingface/transformers/pull/35926. If we now allow to load on meta with quantization as well, we need to be coherent on both sides
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Making a new account to better handle notifications
Fixes # (issue)
## 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/... | {
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hello | null | {
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VLLM is seeing some output differences in their CI when beam search is being used. The difference can be tracked to the beam search refactor (#35802).
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https://api.github.com/repos/huggingface/transformers/issues/37079 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37079/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37079/comments | https://api.github.com/repos/huggingface/transformers/issues/37079/events | https://github.com/huggingface/transformers/issues/37079 | 2,956,451,308 | I_kwDOCUB6oc6wN93s | 37,079 | Need to get hidden features from Siglip but ValueError: You have to specify input_ids | {
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## this is my code
ckpt = "google/siglip2-base-patch16-224"
model = AutoModel.from_pretrained(ckpt, device_map="cpu",
output_hidden_states=True).eval()
image = load_image("https://huggi... | {
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Hi, currently I am doing some training and I have a use case where I want to reuse the KV cache for the context without having to resolve to a deep copy or truncating the cache after each generation.
### Motivation
In the decoder, `.update` is called even in cases where use_cache = False, that is... | null | {
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https://api.github.com/repos/huggingface/transformers/issues/37077 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37077/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37077/comments | https://api.github.com/repos/huggingface/transformers/issues/37077/events | https://github.com/huggingface/transformers/pull/37077 | 2,956,427,296 | PR_kwDOCUB6oc6QkuiE | 37,077 | Fix: Unexpected Keys, Improve `run_compressed`, Rename Test Folder | {
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- `transformers` version: 4.50.2
- Platform: Linux-5.15.0-1040-nvidia-x86_64-with-glibc2.35
- Python version: 3.12.9
- Huggingface_hub version: 0.29.3
- Safetensors version: 0.5.3
- Accelerate version: 1.5.2
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (GPU?): ... | {
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cc @yonigozlan | {
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This is a follow-up of https://github.com/huggingface/transformers/pull/36963.
This PR makes `_init_weights` work seamlessly with composite models. Until this point, composite models would only use the `_init_weights` of the outer-most `PreTrainedModel` wrapper, leading to errors or skippe... | {
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"merged_at... | <!-- PR의 제목은 "🌐 [i18n-KO] Translated `<your_file>.md` to Korean" 으로 부탁드립니다 -->
# What does this PR do?
Translated the `roberta.md` file of the documentation to Korean.
Thank you in advance for your review.
Part of https://github.com/huggingface/transformers/issues/20179
## Before reviewing
- [ ] Check for ... | {
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Seems that BLIP2 `keep_in_fp32_modules` was not picking up correctly until [36722](https://github.com/huggingface/transformers/pull/36722) (thus no errors up to today). Now that the `query_tokens` are actually kept in 32, we are getting dtype mismatch error in inference. (reported by @hmellor... | {
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"merged_at... | # What does this PR do?
FIX 4090/Ada not detected as having valid FP8 hw support.
Did a simple layer/module inference test with DeepSeek V3 0324 using GPTQModel and there is no issue with Transformer inference on 4090 at the layer/module level. 4090 does not have the memory to run a full all-layer generation.
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"merged_at... | Key reasons for this change:
1. MP4 container format requires random access to metadata (moov atoms)
which is often located at the end of the file. Pipe streaming makes
this access pattern impossible.
2. FFmpeg's format detection works more reliably with physical files
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"merged_at... | # What does this PR do?
This PR updates the model-card for the `depth_anything` model, as described in #36979, in an attempt to standardize all model-cards.
## 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?
Anyone ... | {
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in the _preprocess function of Qwen2VLImageProcessor Class(https://github.com/huggingface/transformers/blob/348f3285c5114159d2ff4933b4b8ae36866d01a7/src/transformers/models/qwen2_vl/image_processing_qwen2_vl.py#L278), it writes down as follows:
```python
if patches.shape[0] % temporal_patch_size != 0:... | {
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This PR updates the ELECTRA model card to follow the standardized format outlined in issue #36979. The updated model card includes:
- A conversational description of how ELECTRA works and what makes it unique
- Code examples for using ELECTRA with both Pipeline and AutoModel
- A quantiza... | {
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Use weights_only=True in all code. | {
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"merged_at... | refactor(audio_processing): replace pipe with temp files for FFmpeg processing
This change replaces the previous pipe-based FFmpeg audio decoding approach
with temporary file operations to improve reliability, especially for
container formats like MP4/m4a.
Key reasons for this change:
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Follow pr : [quicky ](https://github.com/huggingface/transformers/commit/d6b3c7486b441296366f788fde57109337f63bca)
<!--
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 ma... | {
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This PR updates the model card for Cohere and follows the template outlined in the issue. Please let me know if any changes are required.
As part of this update, I also replaced the outdated blog link [`https://txt.cohere.com/command-r/`](https://txt.cohere.com/command-r/) with the updated ... | {
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Add Fast Image Processor https://github.com/huggingface/transformers/issues/36978 for EfficientNet
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As described in the issue, this PR updates the model card for ModernBERT. Please let me know if any modifications are required and I will make the necessary changes.
Fixes #36979
## Before submitting
- [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if t... | {
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- `transformers` version: 4.50.2
- Python version: 3.12.0
- Huggingface_hub version: 0.29.3
- Safetensors version: 0.5.3
- Accelerate version: 1.5.2
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (GPU?): 2.5.0+cu124 (True)
- Tensorflow version (GPU?): not install... | {
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Any system (incl. Google Colab)
Certain versions (incl. 4.50.0 and up) produce this behavior
The version that Colab has installed by default works fine
### Reproduction
```py
#@title 🤗 AutoTrain
#@markdown Install requirements and fix dependencies
# Install requirements
!pip install -q autotrain-a... | {
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This PR is to add a stub for the MiniCPM-o model familly to the main huggingface/transformer/models library
This PR, as its mean as a stub, shall be improved by people who are familiarized with the huggingface and the MiniCPM-o,
# Why a Stub?
I'm not nearly qualified enough to do a ful... | null | {
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**Affect... | {
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"merged_at... | Fixes #36938
Fixes #36814
[fine-tunning gemma3 or other models with a non-default cache]
🚨 Breaking: renaming of a public attribute in a public class.
`accelerate` sensibly detects whether a given object is a tensor or tensor-like through its type or, alternatively, through the existence of a `dtype` attrib... | {
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It looks like ruff was updated before the last run of tests for https://github.com/huggingface/transformers/pull/36614 | {
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"merged_at... | # 量子经典同构Transformer模型实现与优化 | Quantum-Classical Isomorphic Transformer Model Implementation and Optimization
## PR描述 | PR Description
### 中文
本PR实现了基于量子经典同构理论的Transformer模型，该模型将Transformers架构与宇宙本质结构完全同构，补齐了原有架构中缺失的量子特性和自我参照机制。
实现的核心功能：
1. **量子-经典界面交互机制**：通过QuantumClassicalInterface模块实现量子域与经典域之间的动态耦合，使模型能够在... | null | {
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As suggested in this issue - https://github.com/huggingface/transformers/issues/36979#issue-2947704577 - this PR updates the documentation of the CLIP model, which will now be aligned with the standardized format for all the docs.
## Who can review?
@stevhliu, please let me know if any ... | {
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_Originally posted by @airMeng in https://github.com/huggingface/transformers/pull/36526#discussion_r2015946292_
Transformers version 49b5ab6a27511de... | {
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Fix torchao usage including config and save-load and tests. | {
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"merged_at... | # What does this PR do?
Stage one of vLLM with transformers backend support for vision LLMs. As discussed internally, we don't want to break existing models, so we sacrifice readability and duplicate code
The PR adds base models for all model where missing. The base model is supposed to be same as in LLMs, everyt... | {
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"merged_at... | ## What does this PR do?
This PR enables this case on XPU: https://github.com/huggingface/transformers/pull/36656. So we don't need this test marker anymore. Furthermore, `AwqConfigTest` already has the `require_torch_accelerator` test marker.
```bash
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"merged_at... | # What does this PR do?
An update of #33913 before merge. That PR is approved by @ArthurZucker , but since then a huge refactorization is done by @Cyrilvallez, and I prefer to make sure the updated changes still looks fine for @Cyrilvallez .
In order to see the effect, run the following code snippet. On `main` it... | {
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transformers==4.50.0
torch==2.4.0+cu121
flash_attn==2.7.4.post1
### Who can help?
@ArthurZucker @muellerzr @SunMarc
### Information
- [ ] The official example scripts
- [x] My own modified scripts
### Tasks
- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [... | {
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As discussed in #31836, I would like to add the miniCPM-o model.
I believe the miniCPM family has had a significant impact on the LMM, LLM field.
Currently, the miniCPM-o code is uploaded to the Hugging Face Hub, which makes maintenance very difficult.
Therefore, I want to add models like mini... | {
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Also, the mix-precision 8-bit training on CPU and XPU has been fixed.
cc @Titus-von-Koeller @matthewdouglas | {
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- After learning is complete, the problem of saving the model occurs at the end of the train() function. (Multi-GPU)
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Linked: https://github.com/huggingface/transformers/issues/36978
Adding fast processor for Segformer.
CC: @yonigozlan
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adds fast image processor to video-llava with appropriate tests
please let me know how it goes 😇
cc @yonigozlan | {
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Add support for fast image processing in image-pretraining example
- Fix typo: correct tuple formatting in IMAGE_PROCESSOR_MAPPING_NAMES
- Add support for fast image processing in image-pretraining example
Fixes #37020
## Before submitting
- [x] This PR fixes a typo or improves the ... | {
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- `transformers` version: 4.51.0.dev0
- Platform: Linux-5.15.0-73-generic-x86_64-with-glibc2.35
- Python version: 3.12.9
- Huggingface_hub version: 0.29.3
- Safetensors version: 0.5.3
- Accelerate version: 1.5.2
- Accelerate config: not found
- DeepSpeed version: not installed
- PyTorch version (GPU... | {
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Fixes an image resizing issue for Mistral3 that I found when integrating into vLLM (https://github.com/vllm-project/vllm/pull/15505)
The issue was found when processing [this image](https://careforplant.com/wp-content/uploads/2024/01/1677123490_gagaru-club-p-krasivie-malenkie-tsvetochki-kr... | {
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Before, the only arg to be accepted was `images`, but in some cases like for segmentation models, more inputs are necessary such as segmentations annotations or bounding boxes. This fixes the is... | {
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https://api.github.com/repos/huggingface/transformers/issues/37017 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37017/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37017/comments | https://api.github.com/repos/huggingface/transformers/issues/37017/events | https://github.com/huggingface/transformers/issues/37017 | 2,950,678,427 | I_kwDOCUB6oc6v38eb | 37,017 | SwitchTransformer: Initialization of tensor to collect expert results is incorrect for dropped tokens (from ML POV) | {
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This is a about a logical bug from ML point of view. It will not result in crashes but influence model behavior significantly.
In the [transformers code of SwitchTransfomer](https://github.com/huggingface/transformers/blame/main/src/transformers/models/switch_transformers/modeling_switch_transformers.... | {
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Windows 11
python-3.10
tokenizers-0.21.1
transformers-4.50.1
### Who can help?
_No response_
### 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 dat... | {
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https://api.github.com/repos/huggingface/transformers/issues/37015 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37015/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37015/comments | https://api.github.com/repos/huggingface/transformers/issues/37015/events | https://github.com/huggingface/transformers/issues/37015 | 2,950,375,321 | I_kwDOCUB6oc6v2yeZ | 37,015 | Add NeoBERT | {
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[NeoBERT](https://arxiv.org/abs/2502.19587) is a next-generation encoder model, outperforming BERT large, RoBERTa large, NomicBERT, and ModernBERT under identical fine-tuning conditions on MTEB.
### Open source status
- [x] The model implementation is available
- [x] The model weights are avail... | null | {
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"merged_at... | # What does this PR do?
Related to #36942
We need to allocate static caches on the correct device. In `generate`, we peek at the model's `hf_device_map` to find the correct device for each layer, so that the cache stays on the same device as the layer it is caching.
Previously, given that decoder-only LLMs we... | {
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https://api.github.com/repos/huggingface/transformers/issues/37012 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/37012/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/37012/comments | https://api.github.com/repos/huggingface/transformers/issues/37012/events | https://github.com/huggingface/transformers/pull/37012 | 2,950,277,552 | PR_kwDOCUB6oc6QPsOp | 37,012 | Add Fast Chinese-CLIP Processor | {
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"merged_at... | Related #36978
cc @qubvel @yonigozlan
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Hello,
When adding custom tokens to the `gemma_3b_1_it` tokenizer, an unexpected token (`<image_soft_token>`) appears in the model's embedding matrix — even though it was not explicitly added.
### Who can help?
_No response_
### Information
- [ ] The official example scripts
- [ ] My own modified... | {
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