Instructions to use quasar529/ft-sd15-instance with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use quasar529/ft-sd15-instance 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("quasar529/ft-sd15-instance") prompt = "an identification photo of iom man" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 317f7863b02bf699c7d5d52422e415c8ce68bf84acdcce0c0a546c7e7f4072d3
- Size of remote file:
- 6.64 MB
- SHA256:
- 1eae35c2eb9ad7ced3abaf6abb634467c75510541c894f04525983d8061e2984
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.