Instructions to use kombuwa/angulimala with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kombuwa/angulimala 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("kombuwa/angulimala") prompt = "angulimala Chiseled Buddhist monk walking in rural india" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
angulimala
A Flux LoRA trained on a local computer with Fluxgym

- Prompt
- angulimala Chiseled Buddhist monk walking in rural india

- Prompt
- angulimala Chiseled Buddhist monk meditating under tree
Trigger words
You should use angulimala 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 kombuwa/angulimala
Base model
black-forest-labs/FLUX.1-dev