Image-to-Video
Diffusers
Diffusion Single File
English
Chinese
i2v
video generation
comfyui
distillation
LoRA
quantization
nvfp4
Instructions to use InsecureErasure/Wan2.1-I2V-14B-480P-StepDistill-CfgDistill-Lightx2v-NVFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use InsecureErasure/Wan2.1-I2V-14B-480P-StepDistill-CfgDistill-Lightx2v-NVFP4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("InsecureErasure/Wan2.1-I2V-14B-480P-StepDistill-CfgDistill-Lightx2v-NVFP4", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Diffusion Single File
How to use InsecureErasure/Wan2.1-I2V-14B-480P-StepDistill-CfgDistill-Lightx2v-NVFP4 with Diffusion Single File:
# 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
Upload assets/wan21_output_cat.mp4 with huggingface_hub
Browse files
assets/wan21_output_cat.mp4
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