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

- Prompt
- 0rb on a table

- Prompt
- 0rb half full of beer sitting next to a can of beer, beer can is "Pineapple Delight IPA", on table at the beach

- Prompt
- a juice orb filled with orange beer sitting on a table
Trigger words
Trained on '0rb' but 'juice orb' might also help
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 iliketoasters/juice-orb
Base model
black-forest-labs/FLUX.1-dev