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:
- c3502b4b135d3f76f5dc120b2cb52f409ae84fe9f99655c2efdd8add248114ba
- Size of remote file:
- 3.23 MB
- SHA256:
- c96b1e3d10a13cf9b10de5cfbc49f4d126aec1a1f69caf008b06c4ed0ae10f40
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.