Instructions to use CapGo/duncify_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CapGo/duncify_test 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("CapGo/duncify_test") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 568d53d60aa0a7f4cd41db24067e03b490347610cb3b0e572d7b418769f4e57f
- Size of remote file:
- 314 MB
- SHA256:
- e080092fecc02f44ec0b38f0f59fef6b48af4ead227dc79b5420a690b4af4cf9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.