---
tags:
- autotrain
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
- lora
- template:sd-lora

base_model: stable-diffusion-v1-5/stable-diffusion-v1-5
instance_prompt: photo of ambika0 man
license: openrail++
---
# ModelsLab LoRA DreamBooth Training - stablediffusionapi/my-stablediffusion-lora-6484
These are LoRA adaption weights for stable-diffusion-v1-5/stable-diffusion-v1-5. The weights were trained on photo of ambika0 man using [ModelsLab](https://modelslab.com).
LoRA for the text encoder was enabled: False.

## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
```py
!pip install -q transformers accelerate peft diffusers
from diffusers import DiffusionPipeline
import torch

pipe_id = "Lykon/DreamShaper"
pipe = DiffusionPipeline.from_pretrained(pipe_id, torch_dtype=torch.float16).to("cuda")
pipe.load_lora_weights("stablediffusionapi/my-stablediffusion-lora-6484", weight_name="pytorch_lora_weights.safetensors", adapter_name="abc")
prompt = "abc of a hacker with a hoodie"
lora_scale = 0.9
image = pipe(
    prompt,
    num_inference_steps=30,
    cross_attention_kwargs={"scale": 0.9},
    generator=torch.manual_seed(0)
).images[0]
image
```