Instructions to use whosouravsharma/diffusiondb-sd15-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use whosouravsharma/diffusiondb-sd15-lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("whosouravsharma/diffusiondb-sd15-lora") prompt = "a anthropomorphic lion wizard, diffuse lighting, fantasy, intricate, elegant, highly detailed, lifelike, photorealistic, digital painting, artstation, illustration, concept art, smooth, sharp focus, naturalism, trending on byron's - muse, by greg rutkowski and greg staples" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoints/checkpoint-2500/optimizer.pt from whosouravsharma/diffusiondb-sd15-lora: direct link, hf CLI and curl.
- Browser
- Download file 51.2 MB
-
https://huggingface.co/whosouravsharma/diffusiondb-sd15-lora/resolve/main/checkpoints/checkpoint-2500/optimizer.pt
- Command line
-
hf download hf://whosouravsharma/diffusiondb-sd15-lora/checkpoints/checkpoint-2500/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/whosouravsharma/diffusiondb-sd15-lora/resolve/main/checkpoints/checkpoint-2500/optimizer.pt
51.2 MB
- Xet hash:
- 41e073d8d7e43982bef72399d5696812ef2a1abab474322bcf1e4a02788c9be2
- Size of remote file:
- 51.2 MB
- SHA256:
- 8bca4891b526c29892fae0f6fd880b430c1cac4216dbad75693739702280e54c
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