How to use from the
Use from the
Diffusers library
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
from diffusers.utils import load_image

# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-inpainting", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("ShreyashDhoot/v2")

prompt = "Turn this cat into a dog"
input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")

image = pipe(image=input_image, prompt=prompt).images[0]

ShreyashDhoot/v2

Last updated: 2026-04-28 06:34

Model Description

KTO fine-tuned Stable Diffusion inpainter with LoRA for safety alignment. Base model: runwayml/stable-diffusion-inpainting

Checkpoints

  • checkpoint--1000
  • checkpoint--250
  • checkpoint--500
  • checkpoint--750

Example Eval Outputs

eval_step1000_sample0.png eval_step1000_sample1.png eval_step1000_sample10.png eval_step1000_sample11.png eval_step1000_sample12.png eval_step1000_sample13.png eval_step1000_sample14.png eval_step1000_sample15.png


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