Instructions to use veryVANYA/opus-ascii-flux with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use veryVANYA/opus-ascii-flux with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("veryVANYA/opus-ascii-flux") prompt = "ascii art, opus_ascii, will smith eating spaghetti" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Opus ASCII FLUX

- Prompt
- ascii art, opus_ascii, will smith eating spaghetti

- Prompt
- ascii art, opus_ascii, will smith eating spaghetti

- Prompt

- Prompt
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 𧨠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
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Model tree for veryVANYA/opus-ascii-flux
Base model
black-forest-labs/FLUX.1-dev