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---
tags:
- autotrain
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
- lora
- template:sd-lora
base_model: stablediffusionapi/dreamshaperv8
instance_prompt: photo of sruthi
license: openrail++
---
# ModelsLab LoRA DreamBooth Training - stablediffusionapi/my-stablediffusion-lora-4303
These are LoRA adaption weights for stablediffusionapi/dreamshaperv8. The weights were trained on photo of sruthi 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-4303", 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
``` |