Text-to-Video
Safetensors
MLX
Wan2.2
mlx-gen
mflux
apple-silicon
bf16
wan
video-generation
image-to-video
Instructions to use AbstractFramework/wan2.2-ti2v-5b-diffusers-bf16 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-bf16 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir wan2.2-ti2v-5b-diffusers-bf16 AbstractFramework/wan2.2-ti2v-5b-diffusers-bf16
- Wan2.2
How to use AbstractFramework/wan2.2-ti2v-5b-diffusers-bf16 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:
- 15e82e0a6f2d99ba9db5425099bb4abe2bc4cf576e6dcea4ae85c13f97f1f244
- Size of remote file:
- 155 kB
- SHA256:
- e17c5be130a66a2ceb39134d8f70b6651d491c1a72001320fec95ac067658add
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.