Image-to-Video
Safetensors
MLX
Wan2.2
mlx-gen
mflux
apple-silicon
8-bit precision
mixed-q8-bf16
wan
video-generation
wan-a14b
Instructions to use AbstractFramework/wan2.2-i2v-a14b-diffusers-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use AbstractFramework/wan2.2-i2v-a14b-diffusers-8bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir wan2.2-i2v-a14b-diffusers-8bit AbstractFramework/wan2.2-i2v-a14b-diffusers-8bit
- Wan2.2
How to use AbstractFramework/wan2.2-i2v-a14b-diffusers-8bit with Wan2.2:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio

- Xet hash:
- 0ea1c47717d6b02bd8e6065cc3c3c286e88b277582a7e8398f3d0ac6c03b9394
- Size of remote file:
- 460 kB
- SHA256:
- 8a7e505cb0368a0e1f0c8d4dc4edfb5924048e6dc70e86cfb490caaf9ed6d9fb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.