Instructions to use Runware/Video-Upscale with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Runware/Video-Upscale with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Runware/Video-Upscale", 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
Download vae/diffusion_pytorch_model.bin from Runware/Video-Upscale: direct link, hf CLI and curl.
- Browser
- Download file 455 MB
-
https://huggingface.co/Runware/Video-Upscale/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://Runware/Video-Upscale/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/Runware/Video-Upscale/resolve/main/vae/diffusion_pytorch_model.bin
455 MB
- Xet hash:
- 506af462ea3eddbfe90eb215d21fef7d23e472667690d8d69dd18dc8ec4be89e
- Size of remote file:
- 455 MB
- SHA256:
- 8eb1c1a72bcb80c607f0258c3e1dbeb84d28e79c464f11fdd89b10f70f825a20
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