Instructions to use Boqiang/path-to-save-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Boqiang/path-to-save-model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Boqiang/path-to-save-model") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 0d7c44189b6b1524a68cd9cca0bc0537098b420472fcd0a41443dba1da43dfcc
- Size of remote file:
- 3.23 MB
- SHA256:
- 1e16676ca99322ae43e659894c8f6a03a156e87fb19311f60db593ea0184d089
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.