---
license: other
license_name: bespoke-lora-trained-license
license_link: https://multimodal.art/civitai-licenses?allowNoCredit=True&allowCommercialUse=Rent&allowDerivatives=True&allowDifferentLicense=False
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
- migrated
- concept
- pokemon
- irl
- pokemongo

base_model: stabilityai/stable-diffusion-xl-base-1.0
instance_prompt: PokIRL
widget:
- text: ' '
  
  output:
    url: >-
      23354114.jpeg
- text: ' '
  
  output:
    url: >-
      23354116.jpeg
- text: ' '
  
  output:
    url: >-
      23354088.jpeg
- text: ' '
  
  output:
    url: >-
      23354123.jpeg
- text: ' '
  
  output:
    url: >-
      23354105.jpeg
- text: ' '
  
  output:
    url: >-
      23354102.jpeg
- text: ' '
  
  output:
    url: >-
      23354111.jpeg

---

# PokIRL [SDXL] 

<Gallery />



([CivitAI](https://civitai.com/models/))

## Model description

<p>PokIRL (Pokemon In-Real-Life) is inspired by Pokemon GO's "AR" mode where you can take picture of Pokemon in your "Real life" environment.</p><p>If you want to make a Pokemon version  of a known person or artwork, use LoRA weight scale of &gt;1 (e.g. 1.4), otherwise a  LoRA weight scale of 1.0 works kind of fine.</p>

## Trigger words
You should use `PokIRL` to trigger the image generation.
    

## Download model

Weights for this model are available in Safetensors format.

[Download](/Norod78/pokirl-sdxl/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('Norod78/pokirl-sdxl', weight_name='PokIRL_SDXL-000009.safetensors')
image = pipeline('`PokIRL`').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)