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:
- bfa0d0578e93e5c71c0d0e94c40a45e1d175921906efe90a7622658bb9246473
- Size of remote file:
- 6.59 MB
- SHA256:
- f80660943b894453e830e7df9cf8dadb012bab90bd73e719b5baf9e089f05b47
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