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:
- 1a38cac7775bb8a06b0ea3b2b28d4bbd71cf532d9ad72490a6a34e264c9e5351
- Size of remote file:
- 4.29 GB
- SHA256:
- 4034ddeb798f6ddd2e054bcab98e054e3b09d44d1711883949af04763d97cdee
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