Instructions to use mlx-community/SmolVLM2-256M-Video-Instruct-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mlx-community/SmolVLM2-256M-Video-Instruct-mlx with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("mlx-community/SmolVLM2-256M-Video-Instruct-mlx") model = AutoModelForImageTextToText.from_pretrained("mlx-community/SmolVLM2-256M-Video-Instruct-mlx") - MLX
How to use mlx-community/SmolVLM2-256M-Video-Instruct-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir SmolVLM2-256M-Video-Instruct-mlx mlx-community/SmolVLM2-256M-Video-Instruct-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
mlx-community
#2
by pcuenq HF Staff - opened
README.md
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@@ -25,5 +25,5 @@ pip install -U mlx-vlm
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```
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```bash
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python -m mlx_vlm.generate --model
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```
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```
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```bash
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python -m mlx_vlm.generate --model mlx-community/SmolVLM2-256M-Video-Instruct-mlx --image https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/bee.jpg --prompt "Can you describe this image?"
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```
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