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", torch_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
- Xet hash:
- e8dc2547b12bec4e995026997b8f6955b18aa58db7b9d7b6a42c1b57535ef7f8
- Size of remote file:
- 127 MB
- SHA256:
- d77f5569a2dcc87a66a7ac55a075ec352104eb5ffa42b04634354e517b781c2a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.