metadata

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

Model description

trained on around 17 images from midjourney of characters in studio.

This is meant to re-create the concept of recording in Studio.

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.

Trigger words

You should use recstudio, evang to trigger the image generation.

Download model

Weights for this model are available in Safetensors format.

Download them in the Files & versions tab.

Use it with the 🧨 diffusers library

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