Instructions to use jeremytai/techlinedrawing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jeremytai/techlinedrawing 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("jeremytai/techlinedrawing") prompt = "techlinedrawing, 70s era bicycle" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Add generated example
#4
by jeremytai - opened
Generated example for model jeremytai/techlinedrawing.
Prompt: techlinedrawing, a long - sleeved cycling jacket cycling jacket, drawn image, illustration, clean ink, full product shot, jacket, 3/4 profile from front,
jeremytai changed pull request status to merged