metadata

license: other
license_name: bespoke-lora-trained-license
license_link: >-
  https://multimodal.art/civitai-licenses?allowNoCredit=True&allowCommercialUse=Image&allowDerivatives=True&allowDifferentLicense=True
tags:
  - text-to-image
  - stable-diffusion
  - lora
  - diffusers
  - template:sd-lora
  - migrated
  - abstract
  - style
  - ai
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: opus_ascii
widget:
  - text: ascii art, opus_ascii, will smith eating spaghetti
    output:
      url: 31654319.jpeg
  - text: ascii art, opus_ascii, will smith eating spaghetti
    output:
      url: 31654332.jpeg
  - text: ' '
    output:
      url: 31654335.jpeg
  - text: ' '
    output:
      url: 31654340.jpeg

Opus ASCII FLUX

Prompt
ascii art, opus_ascii, will smith eating spaghetti

Model description

Trained on Claude Opus 3 ASCII art output latent space discovered by @dyot_meet_mat on twitter

Trigger words

You should use opus_ascii 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

device = "cuda" if torch.cuda.is_available() else "cpu"

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to(device)
pipeline.load_lora_weights('veryVANYA/opus-ascii-flux', weight_name='flux_opus_ascii.safetensors')
image = pipeline('`opus_ascii`').images[0]

For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers