Hugging Face Transformers v4.56.0. Source highlight: DINOv3 is a family of versatile vision foundation models that outperforms the specialized state of the art across a broad range of settings, without fine-tuning. DINOv3 produces high-quality dense features that achieve outstanding performance on various vision tasks, significantly surpassing previou
Hugging Face Transformers v4.55.4. Source highlight: There was a mick mack on our side when cherry-picking the commit #40197 which led to a wrong commit in the patch!
Hugging Face Transformers v4.54.0. Source highlight: In order to become the source of truth, we recognize that we need to address two common and long-heard critiques about `transformers`:
Hugging Face Transformers v4.53.0. Source highlight: Gemma 3n models are designed for efficient execution on low-resource devices. They are capable of multimodal input, handling text, image, video, and audio input, and generating text outputs, with open weights for pre-trained and instruction-tuned variants. These models were trained with data in over
Hugging Face Transformers v4.52.1. Source highlight: The Qwen2.5-Omni model is a unified multiple modalities model proposed in Qwen2.5-Omni Technical Report from Qwen team, Alibaba Group.
Hugging Face Transformers v4.51.3. Source highlight: A mix of bugs were fixed in this patch; very exceptionally, we diverge from semantic versioning to merge GLM-4 in this patch release.
Hugging Face Transformers v4.51.0. Source highlight: Llama 4, developed by Meta, introduces a new auto-regressive Mixture-of-Experts (MoE) architecture.This generation includes two models: