Instructions to use chengwendong/controlnet_canny_stable_video_diffusion_xl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use chengwendong/controlnet_canny_stable_video_diffusion_xl 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("chengwendong/controlnet_canny_stable_video_diffusion_xl", 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") - Notebooks
- Google Colab
- Kaggle
Upload pytorch_lora_weights.safetensors
Browse fileslora weights for fine-tuing stable-video-diffusion-xl
pytorch_lora_weights.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:2d21d4d7310181a287b98ab4fa747beaa6956774df7f374bf82b450ffce5793e
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size 26637168
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