Instructions to use RadwaH/CustomDiffusionAgnes2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use RadwaH/CustomDiffusionAgnes2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("RadwaH/CustomDiffusionAgnes2", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a <new1> girl" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 4987dcda4f02d2413fc23bf4a41884688739e7889ea637c74df360a140a7bd47
- Size of remote file:
- 1.36 GB
- SHA256:
- bc923fece17ad378d91782dd60645dca44caae7b76e0f1e73a8a8d5ba0f98c82
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