Instructions to use llfkf/path-to-save-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use llfkf/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("CompVis/stable-diffusion-v1-4", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("llfkf/path-to-save-model") prompt = "a photo of sks boy" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- a4c91839e7ccbd32e057a3c439fc5071389e90f22c49785fbc5f620fb78920d6
- Size of remote file:
- 6.59 MB
- SHA256:
- 3bdd1f97fad83e6ae8487db2f2efdf2949fa42c6dac89a8e50cae6ed0fbf7b62
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