Instructions to use uwcc/JunkBot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use uwcc/JunkBot 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("uwcc/JunkBot") prompt = "A church in a field on a sunny day, [trigger] style." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 9d78a289ef4ac6a09904de28e933eb17a97a67f4a45f950d5b7bfd40da1b7fb2
- Size of remote file:
- 172 MB
- SHA256:
- e03451381470f2d48ce4289027acf00f7464261d7281d9f1acff08032ad507ce
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.