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:
- 248fe61fdf48d0d66d2fa8f1eced251d77eb9233a967aef7a7b497a632f84547
- Size of remote file:
- 14.4 kB
- SHA256:
- afcc5357c47076e5e4499b6b5c654c3ed0b756caa26c5cae66a63b6f1cd543c1
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