Instructions to use danielpleus/daniel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use danielpleus/daniel 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("danielpleus/daniel") prompt = "a D4N1EL man in a bustling cafe " image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- ffed8787c4c415bf6aebf5f50af0bcf87bd6982cc1be75ab92773b93d2e45c93
- Size of remote file:
- 172 MB
- SHA256:
- 0ec5b91b4f63588724a48e697a6922266377e8e14ef6f03b39f55ba4a3741181
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.