Instructions to use phi-lab-rice/GRADE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use phi-lab-rice/GRADE with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("phi-lab-rice/GRADE", 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 src/Baselines/cafnet/split.json from phi-lab-rice/GRADE: direct link, hf CLI and curl.
- Browser
- Download file 232 Bytes
-
https://huggingface.co/phi-lab-rice/GRADE/resolve/main/src/Baselines/cafnet/split.json
- Command line
-
hf download hf://phi-lab-rice/GRADE/src/Baselines/cafnet/split.json
-
curl -L -o split.json https://huggingface.co/phi-lab-rice/GRADE/resolve/main/src/Baselines/cafnet/split.json
232 Bytes
| { | |
| "test": [ | |
| "Dell-1", | |
| "Dell-2", | |
| "Smoke-Dell-1", | |
| "Smoke-Dell-2", | |
| "Keck-1", | |
| "Keck-2", | |
| "Keck-3", | |
| "Smoke-keck-1", | |
| "Smoke-keck-2", | |
| "Smoke-keck-3" | |
| ] | |
| } |