README.md

---
license: other
license_name: bespoke-lora-trained-license
license_link: https://multimodal.art/civitai-licenses?allowNoCredit=False&allowCommercialUse=RentCivit&allowDerivatives=True&allowDifferentLicense=False
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
- migrated
- photorealistic
- realism
- base model
- eyes
- woman
- girls
- realistic
- pretty
- eye

base_model: stabilityai/stable-diffusion-xl-base-1.0
instance_prompt: 
widget:
- text: ' '
  
  output:
    url: >-
      24333209.jpeg
- text: ' '
  
  output:
    url: >-
      24333146.jpeg
- text: ' '
  
  output:
    url: >-
      24271280.jpeg
- text: ' '
  
  output:
    url: >-
      24272502.jpeg
- text: ' '
  
  output:
    url: >-
      24272914.jpeg
- text: ' '
  
  output:
    url: >-
      24281303.jpeg
- text: ' '
  
  output:
    url: >-
      24415396.jpeg
- text: ' '
  
  output:
    url: >-
      24417334.jpeg
- text: ' '
  
  output:
    url: >-
      24627863.jpeg
- text: ' '
  
  output:
    url: >-
      24627775.jpeg

---

# Her Eyes 

<Gallery />





## Model description

<p>This is a test version of "Her Eyes" LoRA, if you get unexpectedly bad results or images please share them with me "The creator" directly to improve this LoRA on an upcoming update.</p><p>Your support drives our ability to create better, more enjoyable and controllable diffusion models and adapter that fit all your AI image generation needs.</p>



## Download model

Weights for this model are available in Safetensors format.

[Download](/Tech-Meld/her-eyes/tree/main) them in the Files & versions tab.

## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)

```py
from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('Tech-Meld/her-eyes', weight_name='Her_Eyes.safetensors')
image = pipeline('Your custom prompt').images[0]
```

For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)