Instructions to use SteveWCG/trained_green with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SteveWCG/trained_green 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_green") prompt = "A photo of a green-painted bike lane." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download image_2.png from SteveWCG/trained_green: direct link, hf CLI and curl.
- Browser
- Download file 1.74 MB
-
https://huggingface.co/SteveWCG/trained_green/resolve/main/image_2.png
- Command line
-
hf download hf://SteveWCG/trained_green/image_2.png
-
curl -L -o image_2.png https://huggingface.co/SteveWCG/trained_green/resolve/main/image_2.png
1.74 MB

- Xet hash:
- 98c4bbf6d6f0330d1cf8361a2292274ea79febe107526d155d2b4f611816e84e
- Size of remote file:
- 1.74 MB
- SHA256:
- 847cdb74b13633930f0ec2a1707142145234f1ad463f4808ad4f3d315302cc6a
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