Duplicated from kandinskylab/Kandinsky-S2V-1.0-Lite-Diffusers
How to use ml-resources/Kandinsky-S2V-1.0-Lite-Diffusers 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("ml-resources/Kandinsky-S2V-1.0-Lite-Diffusers", 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")
https://huggingface.co/ml-resources/Kandinsky-S2V-1.0-Lite-Diffusers/resolve/main/tokenizer_2/tokenizer.json
hf download hf://ml-resources/Kandinsky-S2V-1.0-Lite-Diffusers/tokenizer_2/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/ml-resources/Kandinsky-S2V-1.0-Lite-Diffusers/resolve/main/tokenizer_2/tokenizer.json
