Instructions to use wolf1280/RealESRGAN_x2plus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wolf1280/RealESRGAN_x2plus with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wolf1280/RealESRGAN_x2plus", 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 config.json from wolf1280/RealESRGAN_x2plus: direct link, hf CLI and curl.
- Browser
- Download file 189 Bytes
-
https://huggingface.co/wolf1280/RealESRGAN_x2plus/resolve/main/config.json
- Command line
-
hf download hf://wolf1280/RealESRGAN_x2plus/config.json
-
curl -L -o config.json https://huggingface.co/wolf1280/RealESRGAN_x2plus/resolve/main/config.json
189 Bytes
| { | |
| "_class_name": "RRDBNet", | |
| "_diffusers_version": "0.37.0.dev0", | |
| "num_block": 23, | |
| "num_feat": 64, | |
| "num_grow_ch": 32, | |
| "num_in_ch": 3, | |
| "num_out_ch": 3, | |
| "scale": 2 | |
| } | |