Instructions to use quasar529/ft-sd15-class-instance with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use quasar529/ft-sd15-class-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-class-instance") prompt = "an identification photo of iom person" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 181e89cfbc01af5fa1e39dbe1bf9ecd756fffbf69b9fd328766e9503246f8097
- Size of remote file:
- 6.64 MB
- SHA256:
- 7319b87914d5170d7bca49bc89df515844e2d027738f1f589929c0669def0352
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