Instructions to use INCModel/Wan2.2-I2V-A14B-Diffusers-MXFP8-AutoRound with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use INCModel/Wan2.2-I2V-A14B-Diffusers-MXFP8-AutoRound with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("INCModel/Wan2.2-I2V-A14B-Diffusers-MXFP8-AutoRound", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Wan2.2-I2V-A14B-Diffusers-MXFP8-AutoRound / transformer_2 /diffusion_pytorch_model-00002-of-00003.safetensors
- Xet hash:
- 504d3c81c9473979fb0360856ec7b9ef8ccecca837e46f69fa3716dd477ecc05
- Size of remote file:
- 4.99 GB
- SHA256:
- 036eabad44e66e2d710e088c11cd0d9ab0b54d6fba35d6a1116cbd7f4cf0ba62
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