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AI モデル 85004

• llava-onevision-qwen2-0.5b-ov-hf↗

  llava-hf

  Check out also the Google Colab demo to run Llava on a free-tier Google Colab instance: [](https://colab.research.google.com/drive/1-4AtYjR8UMtCALV0AswU1kiNkWCLTALT?usp=sharing) Below is the model card of 0.5B LLaVA-Onevision model which is copied from the original LLaVA-Onevision model card that you can find here. **Model type:** LLaVA-Onevision is an open-source multimodal LLM trained by fine-tuning Qwen2 on GPT-generated multimodal instruction-following data. LLaVA-OneVision is the first single model that can simultaneously push the performance boundaries of open LMMs in three important computer vision scenarios: single-image, multi-image, and video scenarios. Importantly, the design of LLaVA-OneVision allows strong transfer learning across different modalities/scenarios, yielding new emerging capabilities. In particular, strong video understanding and cross-scenario capabilities are demonstrated through task transfer from images to videos.

• Qwen3.8_4B_Distilled_GGUF↗

  Ma7ee7

  GGUF quantizations of `Ma7ee7/Qwen3.8_4B_Distilled` for use with llama.cpp, LM Studio, Ollama, Jan, and other GGUF-compatible applications. **Qwen3.8 4B Distilled** is a 4-billion-parameter reasoning model created by distilling outputs from **Qwen3.8-Max** into the smaller **Qwen3-4B-Thinking-2507** student model. The full model was fine-tuned on `r0b0tlab/qwen3.8-max-distillation-50k`, a dataset of responses and reasoning traces generated by `qwen3.8-max-preview`.

• xclip-base-patch16↗

  Microsoft

  X-CLIP model (base-sized, patch resolution of 16) trained fully-supervised on Kinetics-400. It was introduced in the paper Expanding Language-Image Pretrained Models for General Video Recognition by Ni et al. and first released in this repository. Disclaimer: The team releasing X-CLIP did not write a model card for this model so this model card has been written by the Hugging Face team. X-CLIP is a minimal extension of CLIP for general video-language understanding. The model is trained in a contrastive way on (video, text) pairs.

• gemma-4-12B-coder-fable5-composer2.5-v1-OptiQ-4bit↗

  mlx-community

• NVIDIA-Nemotron-Nano-9B-v2-4bits↗

  mlx-community

• Qwen3.6-35B-A3B-8bit↗

  mlx-community

  This model was converted to MLX format from `Qwen/Qwen3.6-35B-A3B` using mlx-vlm version **0.4.4**. Refer to the original model card for more details on the model.

• transcoder-Llama-3.2-1B↗

  mntss

• Motif-3↗

  Motif-Technologies

• Apollo2-1.5B-GGUF↗

  mradermacher

• Chaifighter-20B-v3-i1-GGUF↗

  mradermacher