Instructions to use dummy9996/SwiftVR-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dummy9996/SwiftVR-bf16 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dummy9996/SwiftVR-bf16", 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
| base_model: | |
| - H-oliday/SwiftVR | |
| <h2><center><strong>SwiftVR: Real-Time One-Step Generative Video Restoration</strong></center></h2> | |
| <center>Now in BF16</center> | |
| Original model is at https://huggingface.co/H-oliday/SwiftVR | |
| Install: | |
| git clone https://github.com/H-oliday/SwiftVR | |
| cd SwiftVR | |
| uv pip install -e . | |
| hf auth login --token {token} | |
| hf download dummy9996/SwiftVR-bf16 --local-dir checkpoints/ | |
| Run: | |
| from swiftvr import SwiftVRPipeline | |
| pipe = SwiftVRPipeline.from_pretrained("checkpoints/").to("cuda", dtype="bfloat16") | |
| pipe.restore_video("before.mp4", "after.mp4", upscale=2) |