Image-to-Video
Diffusers
Safetensors
Kandinsky6TI2VAPipeline
video
video-generation
text-to-video
audio-generation
kandinsky
Instructions to use kandinskylab/Kandinsky-6.0-Pro-distill-5s-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kandinskylab/Kandinsky-6.0-Pro-distill-5s-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("kandinskylab/Kandinsky-6.0-Pro-distill-5s-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") - Notebooks
- Google Colab
- Kaggle
Download vocoder/diffusion_pytorch_model.safetensors from kandinskylab/Kandinsky-6.0-Pro-distill-5s-Diffusers: direct link, hf CLI and curl.
- Browser
- Download file 489 MB
-
https://huggingface.co/kandinskylab/Kandinsky-6.0-Pro-distill-5s-Diffusers/resolve/main/vocoder/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://kandinskylab/Kandinsky-6.0-Pro-distill-5s-Diffusers/vocoder/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/kandinskylab/Kandinsky-6.0-Pro-distill-5s-Diffusers/resolve/main/vocoder/diffusion_pytorch_model.safetensors
489 MB
- Xet hash:
- f1e0d97c4923cd2c02743df4fa7763eafd3ac47bdebf326b84232b6a9658b8fd
- Size of remote file:
- 489 MB
- SHA256:
- abf0536824bdce8dcf8ee10b815770111f4b5d05d0122e1bab4b5719324edca7
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