Instructions to use ccc8/c7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ccc8/c7 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ccc8/c7", dtype=torch.bfloat16, device_map="cuda") prompt = "masterpiece forest" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- e98596a6812ef3fd5891f9c44de8e8085fe87c57d643930352a4ba30938f59a5
- Size of remote file:
- 3.44 GB
- SHA256:
- 60029e5158cda299e1b91fe2460af317b71fb98a69cda691334b1117d535bd7c
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