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
- LM Studio
- Xet hash:
- 4747d621061ff864406560d79c8c3e355c05f2e88ba30eba88c8d5881d3d220d
- Size of remote file:
- 4.24 MB
- SHA256:
- 61a7b147390c64585d6c3543dd6fc636906c9af3865a5548f27f31aee1d4c8e2
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