Instructions to use theqore/rumbidzai-venge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use theqore/rumbidzai-venge 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("theqore/rumbidzai-venge") prompt = "R00v33" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Rumbidzai Venge
A Flux LoRA trained on a local computer with Fluxgym

- Prompt
- R00v33

- Prompt
- R00v33 in court
Trigger words
You should use R00v33 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 theqore/rumbidzai-venge
Base model
black-forest-labs/FLUX.1-dev