Instructions to use fofr/flux-trolley-problem with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fofr/flux-trolley-problem 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("fofr/flux-trolley-problem") prompt = "TROLLEY_PROBLEM" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- f337c6dee081447aef79f55180798265d60af0f06a1566c7492dbfffbd4ecfac
- Size of remote file:
- 172 MB
- SHA256:
- 91d4050cc55e88be7c68d7939cb618121a81174dc7c6c57411d9d8ee1f223a31
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.