Instructions to use kandinskylab/Kandinsky-S2V-1.0-Pro-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kandinskylab/Kandinsky-S2V-1.0-Pro-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-S2V-1.0-Pro-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 modular_model_index.json from kandinskylab/Kandinsky-S2V-1.0-Pro-Diffusers: direct link, hf CLI and curl.
- Browser
- Download file 2.52 kB
-
https://huggingface.co/kandinskylab/Kandinsky-S2V-1.0-Pro-Diffusers/resolve/main/modular_model_index.json
- Command line
-
hf download hf://kandinskylab/Kandinsky-S2V-1.0-Pro-Diffusers/modular_model_index.json
-
curl -L -o modular_model_index.json https://huggingface.co/kandinskylab/Kandinsky-S2V-1.0-Pro-Diffusers/resolve/main/modular_model_index.json
2.52 kB
| { | |
| "_class_name": "KandinskyS2VModularPipeline", | |
| "_diffusers_version": "0.40.0", | |
| "_blocks_class_name": "KandinskyS2VAutoBlocks", | |
| "transformer": [ | |
| "diffusers", | |
| "KandinskyS2VTransformer3DModel", | |
| { | |
| "type_hint": [ | |
| "diffusers", | |
| "KandinskyS2VTransformer3DModel" | |
| ], | |
| "pretrained_model_name_or_path": "kandinskylab/Kandinsky-S2V-1.0-Pro-Diffusers", | |
| "subfolder": "transformer", | |
| "variant": null, | |
| "revision": null | |
| } | |
| ], | |
| "vae": [ | |
| "diffusers", | |
| "AutoencoderKLHunyuanVideo", | |
| { | |
| "type_hint": [ | |
| "diffusers", | |
| "AutoencoderKLHunyuanVideo" | |
| ], | |
| "pretrained_model_name_or_path": "kandinskylab/Kandinsky-S2V-1.0-Pro-Diffusers", | |
| "subfolder": "vae", | |
| "variant": null, | |
| "revision": null | |
| } | |
| ], | |
| "text_encoder": [ | |
| "transformers", | |
| "Qwen2_5OmniThinkerForConditionalGeneration", | |
| { | |
| "type_hint": [ | |
| "transformers", | |
| "Qwen2_5OmniThinkerForConditionalGeneration" | |
| ], | |
| "pretrained_model_name_or_path": "kandinskylab/Kandinsky-S2V-1.0-Pro-Diffusers", | |
| "subfolder": "text_encoder", | |
| "variant": null, | |
| "revision": null | |
| } | |
| ], | |
| "tokenizer": [ | |
| "transformers", | |
| "Qwen2_5OmniProcessor", | |
| { | |
| "type_hint": [ | |
| "transformers", | |
| "Qwen2_5OmniProcessor" | |
| ], | |
| "pretrained_model_name_or_path": "kandinskylab/Kandinsky-S2V-1.0-Pro-Diffusers", | |
| "subfolder": "tokenizer", | |
| "variant": null, | |
| "revision": null | |
| } | |
| ], | |
| "text_encoder_2": [ | |
| "transformers", | |
| "CLIPTextModel", | |
| { | |
| "type_hint": [ | |
| "transformers", | |
| "CLIPTextModel" | |
| ], | |
| "pretrained_model_name_or_path": "kandinskylab/Kandinsky-S2V-1.0-Pro-Diffusers", | |
| "subfolder": "text_encoder_2", | |
| "variant": null, | |
| "revision": null | |
| } | |
| ], | |
| "tokenizer_2": [ | |
| "transformers", | |
| "CLIPTokenizer", | |
| { | |
| "type_hint": [ | |
| "transformers", | |
| "CLIPTokenizer" | |
| ], | |
| "pretrained_model_name_or_path": "kandinskylab/Kandinsky-S2V-1.0-Pro-Diffusers", | |
| "subfolder": "tokenizer_2", | |
| "variant": null, | |
| "revision": null | |
| } | |
| ], | |
| "scheduler": [ | |
| "diffusers", | |
| "FlowMatchEulerDiscreteScheduler", | |
| { | |
| "type_hint": [ | |
| "diffusers", | |
| "FlowMatchEulerDiscreteScheduler" | |
| ], | |
| "pretrained_model_name_or_path": "kandinskylab/Kandinsky-S2V-1.0-Pro-Diffusers", | |
| "subfolder": "scheduler", | |
| "variant": null, | |
| "revision": null | |
| } | |
| ] | |
| } | |