Instructions to use smartypantsnet/FastWan2.2-TI2V-5B-mlx-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use smartypantsnet/FastWan2.2-TI2V-5B-mlx-bf16 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download smartypantsnet/FastWan2.2-TI2V-5B-mlx-bf16 --local-dir FastWan2.2-TI2V-5B-mlx-bf16
- Wan2.2
How to use smartypantsnet/FastWan2.2-TI2V-5B-mlx-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
- Atomic Chat
FastWan 2.2 TI2V-5B for MLX (Smarty Pants)
The video model that Smarty Pants owners' Macs download to make short clips from a text prompt.
model.safetensors: the 3-step transformer from FastVideo/FastWan2.2-TI2V-5B-FullAttn-Diffusers (commit3e187042), renamed from Diffusers names to the original Wan names and laid out for MLX, bfloat16.t5_encoder.safetensors,vae.safetensors: the UMT5 prompt reader and the VAE from Wan-AI/Wan2.2-TI2V-5B (commit921dbaf3), converted for MLX with mlx-video-with-audio 0.1.37.tokenizer/: the UMT5 tokenizer files from the FastWan repository, unchanged.
Changes from the originals: weight names and layouts only (no retraining). Both originals are Apache-2.0; this copy is too (see LICENSE).
Model size
5B params
Tensor type
BF16
ยท
Hardware compatibility
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