Instructions to use Hemanth-thunder/stable_diffusion_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Hemanth-thunder/stable_diffusion_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("Hemanth-thunder/stable_diffusion_lora", dtype=torch.bfloat16, device_map="cuda") prompt = "hmat" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
base_model: SG161222/Realistic_Vision_V1.4
instance_prompt: hmat
tags:
- text-to-image
- diffusers
- autotrain
inference: true
DreamBooth trained by AutoTrain
Test enoder was trained.