Instructions to use linjieluo/lora_gill-tan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use linjieluo/lora_gill-tan with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("linjieluo/lora_gill-tan") prompt = "a photo of sks woman" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- ff1163b8ea33bf45737b918e25115a44a92543e87ff52a04e7498dd91439a9e7
- Size of remote file:
- 3.28 MB
- SHA256:
- 8d9227e6d8dbdd964aec2595d63900659f45719bdc00387e2720f2031a909ab6
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