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
Commit History
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Rename unet/pytorch_model.bin to unet/diffusion_pytorch_model.bin
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Rename unet/unet_video.bin to unet/pytorch_model.bin (#9)
Verified signature- Rename unet/unet_video.bin to unet/pytorch_model.bin (519eff1d2bba82784a902a068fa0a522e7ee517a) Co-authored-by: Munaza Ashraf <Munaza10@users.noreply.huggingface.co>16d7e30 -
Rename unet/unet_video_config.json to unet/config.json (#5)
Verified signature- Rename unet/unet_video_config.json to unet/config.json (1181108a6030e37b6c8e16ac0182d57aea33cff1) Co-authored-by: Munaza Ashraf <Munaza10@users.noreply.huggingface.co>251368d -
Adding `safetensors` variant of this model (#2)
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Upload 18 files (#1)
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