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
Download vocab.json from mlx-community/SmolVLM2-500M-Video-Instruct-mlx: direct link, hf CLI and curl.
- Browser
- Download file 801 kB
-
https://huggingface.co/mlx-community/SmolVLM2-500M-Video-Instruct-mlx/resolve/refs%2Fpr%2F3/vocab.json
- Command line
-
hf download hf://mlx-community/SmolVLM2-500M-Video-Instruct-mlx@refs/pr/3/vocab.json
-
curl -L -o vocab.json https://huggingface.co/mlx-community/SmolVLM2-500M-Video-Instruct-mlx/resolve/refs%2Fpr%2F3/vocab.json
801 kB
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