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
- Draw Things
- DiffusionBee
- Xet hash:
- 9ca4824e998dce189982adce99a5c33c4a12becdd1e5f0355a0ecf4aa2b76258
- Size of remote file:
- 492 MB
- SHA256:
- 1483d9726c583f728dcad6168eff7c84c89b03c2a902b290bd4769fbdd777e3b
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