Instructions to use Gitanjali1801/Stable_diffusion_baseline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Gitanjali1801/Stable_diffusion_baseline with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Gitanjali1801/Stable_diffusion_baseline") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee

- Xet hash:
- 9306b42aa1ce44e3acad0d4b8f1220abe722d6b4daa33cbeb987de264ae8361f
- Size of remote file:
- 1.51 MB
- SHA256:
- 87836f16103f6797d144a8e31636ed4f0104eaa410859840d71213cb3ec7c4b4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.