Instructions to use ssdxc/lora_ckpt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ssdxc/lora_ckpt 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("ssdxc/lora_ckpt") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- bcbc7c5e797d7457d2d5a828340f4dc37d7cbf27b7631a5b511c53d5ab850497
- Size of remote file:
- 3.29 MB
- SHA256:
- 0e5b7b779bd033d1a21f932f064077100dbfcbc0a4f375836c533ffec80194ff
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