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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- e7969f5ac48dc6294ee90a069f4544740f2fe59a32e7c3069a6dff97281e9251
- Size of remote file:
- 609 MB
- SHA256:
- 3f349ea17fece3cd7b922e617521c656026b6f0a28e2dd09d02c628d6a36b05a
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