Video-Text-to-Text
MLX
Safetensors
dattn_gemma2
video-understanding
temporal-grounding
multimodal
gemma2
siglip2
whisper
8-bit precision
quantized
Instructions to use wangjazz/Vidi1.5-9B-mlx-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use wangjazz/Vidi1.5-9B-mlx-8bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Vidi1.5-9B-mlx-8bit wangjazz/Vidi1.5-9B-mlx-8bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Xet hash:
- bff94622acf3d53c89829c7896136769f40284df060bf2c28224b64da461d81e
- Size of remote file:
- 4.28 GB
- SHA256:
- dfd350c94479fc2244431e1105d9dc92651ab6951096d96c09e19d1c20a1e63f
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