Text-to-Video
Safetensors
MLX
Wan2.2
mlx-gen
mflux
apple-silicon
8-bit precision
wan
video-generation
image-to-video
Instructions to use AbstractFramework/wan2.2-ti2v-5b-diffusers-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use AbstractFramework/wan2.2-ti2v-5b-diffusers-8bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir wan2.2-ti2v-5b-diffusers-8bit AbstractFramework/wan2.2-ti2v-5b-diffusers-8bit
- Wan2.2
How to use AbstractFramework/wan2.2-ti2v-5b-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:
- bf3b8aee04be236029297ef47527653bacb90bd627075b21177aa602568a154a
- Size of remote file:
- 1.41 GB
- SHA256:
- c5de7cc01b4737345a64908c281a46b95a1b5a97ef0942f60df6ff1c7e851beb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.