---
license: other
license_name: bespoke-lora-trained-license
license_link: https://multimodal.art/civitai-licenses?allowNoCredit=False&allowCommercialUse=RentCivit&allowDerivatives=False&allowDifferentLicense=False
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
- migrated
- concept
- studio
- recording
- gold teeth
- rapping

base_model: runwayml/stable-diffusion-v1-5
instance_prompt:  recstudio
widget:
- text: ' '
  
  output:
    url: >-
      24380980.jpeg
- text: ' '
  
  output:
    url: >-
      24385885.jpeg
- text: ' '
  
  output:
    url: >-
      24384194.jpeg
- text: ' '
  
  output:
    url: >-
      24382058.jpeg

---

# Recording studio 

<Gallery />





## Model description

<p>trained on around 17 images from midjourney of characters in studio.</p><p> This is meant to re-create the concept of recording in Studio. </p><p></p><p>In the training data, there was a lot of emphasis on smoky rooms, gold chains, gold teeth, etc. so you may want to implement those in your promise. It could be a bit heavy handed so I don't know if I would have the weighting set to high try at a lower value around 6 first and work your way up.</p>

## Trigger words
You should use ` recstudio`, `evang` to trigger the image generation.
    

## Download model

Weights for this model are available in Safetensors format.

[Download](/brushpenbob/recording-studio/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('runwayml/stable-diffusion-v1-5', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('brushpenbob/recording-studio', weight_name='Recording_studio.safetensors')
image = pipeline('` recstudio`, `evang`').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)