Instructions to use SidXXD/custom-diffusion-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SidXXD/custom-diffusion-model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SidXXD/custom-diffusion-model", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a <new1> morning glory--output_dir=model/single-F-5-morning-glory-FLOWER-2" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-250/optimizer.bin from SidXXD/custom-diffusion-model: direct link, hf CLI and curl.
- Browser
- Download file 457 MB
-
https://huggingface.co/SidXXD/custom-diffusion-model/resolve/main/checkpoint-250/optimizer.bin
- Command line
-
hf download hf://SidXXD/custom-diffusion-model/checkpoint-250/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/SidXXD/custom-diffusion-model/resolve/main/checkpoint-250/optimizer.bin
457 MB
- Xet hash:
- 731618c8631226a46dfb6e04d0801bcc90c6fb36d3d1507974e87a7ce1344e32
- Size of remote file:
- 457 MB
- SHA256:
- c41601fa4a65e632c785d5f6af70f22d55ad2b40fd84742eee627f5b2996a9cb
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