Instructions to use mlx-community/SmolVLM2-500M-Video-Instruct-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mlx-community/SmolVLM2-500M-Video-Instruct-mlx with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("mlx-community/SmolVLM2-500M-Video-Instruct-mlx") model = AutoModelForMultimodalLM.from_pretrained("mlx-community/SmolVLM2-500M-Video-Instruct-mlx", device_map="auto") - MLX
How to use mlx-community/SmolVLM2-500M-Video-Instruct-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download mlx-community/SmolVLM2-500M-Video-Instruct-mlx --local-dir SmolVLM2-500M-Video-Instruct-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Commit History
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Manually update processor, for now. Part of https://huggingface.co/HuggingFaceTB/SmolVLM2-500M-Video-Instruct/commit/d52b9cddd52922722e9e0780315d209dd8311f45. (#1)
Verified signature- Manually update processor, for now. Part of https://huggingface.co/HuggingFaceTB/SmolVLM2-500M-Video-Instruct/commit/d52b9cddd52922722e9e0780315d209dd8311f45. (7f8745f5ca6a2e975c55b9f08441d6c977b183e9)3771818
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initial commit
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