Image-to-Video
Diffusers
Safetensors
Kandinsky6TI2VAPipeline
video
video-generation
text-to-video
audio-generation
kandinsky
Instructions to use ml-resources/Kandinsky-6.0-Pro-5s-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ml-resources/Kandinsky-6.0-Pro-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("ml-resources/Kandinsky-6.0-Pro-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 tokenizer/tokenizer.json from ml-resources/Kandinsky-6.0-Pro-5s-Diffusers: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/ml-resources/Kandinsky-6.0-Pro-5s-Diffusers/resolve/main/tokenizer/tokenizer.json
- Command line
-
hf download hf://ml-resources/Kandinsky-6.0-Pro-5s-Diffusers/tokenizer/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ml-resources/Kandinsky-6.0-Pro-5s-Diffusers/resolve/main/tokenizer/tokenizer.json
11.4 MB
- Xet hash:
- d3f835122bddb470f53048ff36f1a5116791b8f3a003f9d17b3b03b0b81cc5fe
- Size of remote file:
- 11.4 MB
- SHA256:
- 3fd169731d2cbde95e10bf356d66d5997fd885dd8dbb6fb4684da3f23b2585d8
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