Instructions to use SteveWCG/trained-6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SteveWCG/trained-6 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-6") prompt = "A photo of a narrow pathway accommodates a bike lane, fully surrounded by greenery on both sides, within the suburban area. " image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download image_0.png from SteveWCG/trained-6: direct link, hf CLI and curl.
- Browser
- Download file 2.16 MB
-
https://huggingface.co/SteveWCG/trained-6/resolve/main/image_0.png
- Command line
-
hf download hf://SteveWCG/trained-6/image_0.png
-
curl -L -o image_0.png https://huggingface.co/SteveWCG/trained-6/resolve/main/image_0.png
2.16 MB

- Xet hash:
- b52ec234d2b33c1426a82f7662dd88d51d8c60cc6e08b38f135d058858e2f3c6
- Size of remote file:
- 2.16 MB
- SHA256:
- 2c4d4054d362a5c6eab6610058d23b777e7a29414091a7a0e73ec2d9c95c80e5
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