Instructions to use FrankCCCCC/cfm-corr-150-ss0.0-ep500-ema-50k-run2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FrankCCCCC/cfm-corr-150-ss0.0-ep500-ema-50k-run2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("FrankCCCCC/cfm-corr-150-ss0.0-ep500-ema-50k-run2", 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 finished.json from FrankCCCCC/cfm-corr-150-ss0.0-ep500-ema-50k-run2: direct link, hf CLI and curl.
- Browser
- Download file 35 Bytes
-
https://huggingface.co/FrankCCCCC/cfm-corr-150-ss0.0-ep500-ema-50k-run2/resolve/main/finished.json
- Command line
-
hf download hf://FrankCCCCC/cfm-corr-150-ss0.0-ep500-ema-50k-run2/finished.json
-
curl -L -o finished.json https://huggingface.co/FrankCCCCC/cfm-corr-150-ss0.0-ep500-ema-50k-run2/resolve/main/finished.json
35 Bytes
| { | |
| "Msg": "Training finished." | |
| } |