Instructions to use kandinskylab/Kandinsky-5.0-I2V-Pro-distilled-5s-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kandinskylab/Kandinsky-5.0-I2V-Pro-distilled-5s-Diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kandinskylab/Kandinsky-5.0-I2V-Pro-distilled-5s-Diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files- .gitignore +0 -6
- text_encoder/model-00001-of-00005.safetensors +3 -0
- text_encoder/model-00002-of-00005.safetensors +3 -0
- text_encoder/model-00003-of-00005.safetensors +3 -0
- text_encoder/model-00004-of-00005.safetensors +3 -0
- text_encoder/model-00005-of-00005.safetensors +3 -0
- text_encoder_2/model.safetensors +3 -0
- text_encoder_2/pytorch_model.bin +3 -0
- transformer/diffusion_pytorch_model.safetensors +3 -0
- vae/diffusion_pytorch_model.safetensors +3 -0
.gitignore
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# Ignore large model weights (if you plan to use model hub or upload via git-lfs)
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*.safetensors
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# Training artifacts & logs
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runs/
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# Training artifacts & logs
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