Instructions to use SteveWCG/trained_narrow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SteveWCG/trained_narrow with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("SteveWCG/trained_narrow") prompt = "A photo of a 4-feet wide bike lane with a white solid line separating cyclists from moving car traffic." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 62da2181b54ba3b7db5647602124aa4266dd601cc45cae4f710fd7c9b65fa594
- Size of remote file:
- 127 MB
- SHA256:
- 25ae83b00a167e8c064be9b548c050b33d4d103b316d3f16197aa364c1b1be8c
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