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:
- 7b394a35b976133ad1da85c778f27a4c737b38c2f6e464376e5d9b92aaff538c
- Size of remote file:
- 3.56 GB
- SHA256:
- 2f855d78ffb821ed6b3537f2d53262567693c64fad5880e7ba15d0fe0f53a22c
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