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:
- aa03da8419197563d653ddb0c73c76aa849f89f9374823aeb397297a5106fe3b
- Size of remote file:
- 102 MB
- SHA256:
- d2dcc6c4ee6f7ce94db2414b0495599afda87b1c286c34f2c02ce6a6abcfacf0
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