LoRA DreamBooth model

These are LoRA adaption weights for kpsss34/Stable-Diffusion-3.5-Small-Preview1. The weights were trained on the concept of a photo of m4k1m4 anime girl using DreamBooth.

Training details

  • Base model: kpsss34/Stable-Diffusion-3.5-Small-Preview1
  • Instance prompt: a photo of m4k1m4 anime girl
  • Validation prompt: a photo of m4k1m4 anime girl stands in the living room.
  • LoRA rank: 32
  • Learning rate: 0.0001
  • Training steps: 500
  • Resolution: 1024
  • Train text encoder: True
  • Datasets: 3 jpg and 3 txt (without 1:1)
  • VRAM USED: 14-15GB (Validation process+2-4GB)

Usage

import torch
from pipeline_stable_diffusion_3_S import StableDiffusion3SPipeline

model_id = "kpsss34/Stable-Diffusion-3.5-Small-Preview1"
pipe = StableDiffusion3SPipeline.from_pretrained(model_id, torch_dtype=torch.bfloat16)
pipe.load_lora_weights("kpsss34/SD35s_lora_test")
pipe.to("cuda")

# Now you can use the pipeline with the trained LoRA
image = pipe("a photo of m4k1m4 anime girl ", num_inference_steps=30, guidance_scale=5.0).images[0]
image.save("result.png")
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