Instructions to use NewbeeDD/david-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use NewbeeDD/david-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("NewbeeDD/david-lora") prompt = "David" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 462bcaef0ef08c2cb1d06ff574d0b68e9cb8bc7195983dc231faa1b9e1defd3b
- Size of remote file:
- 173 MB
- SHA256:
- df15ec4d675ac20d1dd2008a158333c2461feceeae4ef777dbea246cc574ceed
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