Instructions to use TimAllen2024/princeeee-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TimAllen2024/princeeee-lora 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("TimAllen2024/princeeee-lora") prompt = "Emmi" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 40ff4be7946e385c1a3115fba15043dc57f6f6ee03d6f523a03ec27278b159d3
- Size of remote file:
- 173 MB
- SHA256:
- 367013f6e964eaf8b508b2c2d7cfba4f10efa68c4a8374fc84ccfed6e7bedd50
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.