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
Download checkpoint-1000/scheduler.bin from RadwaH/CustomDiffusionAgnes2: direct link, hf CLI and curl.
- Browser
- Download file 563 Bytes
-
https://huggingface.co/RadwaH/CustomDiffusionAgnes2/resolve/main/checkpoint-1000/scheduler.bin
- Command line
-
hf download hf://RadwaH/CustomDiffusionAgnes2/checkpoint-1000/scheduler.bin
-
curl -L -o scheduler.bin https://huggingface.co/RadwaH/CustomDiffusionAgnes2/resolve/main/checkpoint-1000/scheduler.bin
563 Bytes
- Xet hash:
- c74e72189736fcca821eb0bda7fab1ca95b94e380538c19bc81cd9f7aa7ea3c9
- Size of remote file:
- 563 Bytes
- SHA256:
- 7f5b7d685fdc59a9da7be1f1a8a92b8f94caf53a1cd058c132b32d0c98bb3705
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