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:
- 2ebedc2f0c11f5dd53bf1afd5e582817c12e3b91cc6dd4d2eba0b4ace072bedb
- Size of remote file:
- 14.3 kB
- SHA256:
- aa7b58e226be6fd798fc829cbbd46a62cc5ad2b94b9940208313ebe40d2b737c
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