Instructions to use cocktailpeanut/crt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cocktailpeanut/crt 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("cocktailpeanut/crt") prompt = "a word \"hello world\" on a crt screen" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
crt
A Flux LoRA trained on a local computer with Fluxgym

- Prompt
- a word "hello world" on a crt screen

- Prompt
- a keyboard on a crt screen

- Prompt
- a robot on a crt screen
Trigger words
You should use crt screen to trigger the image generation.
Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, Forge, etc.
Weights for this model are available in Safetensors format.
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Model tree for cocktailpeanut/crt
Base model
black-forest-labs/FLUX.1-dev