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
File size: 499 Bytes
0627bf7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | {
"_class_name": "WanPipeline",
"_diffusers_version": "0.35.0.dev0",
"boundary_ratio": null,
"expand_timesteps": true,
"scheduler": [
"diffusers",
"UniPCMultistepScheduler"
],
"text_encoder": [
"transformers",
"UMT5EncoderModel"
],
"tokenizer": [
"transformers",
"T5TokenizerFast"
],
"transformer": [
"diffusers",
"WanTransformer3DModel"
],
"transformer_2": [
null,
null
],
"vae": [
"diffusers",
"AutoencoderKLWan"
]
}
|