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:
- 0bdb7fa8e991d712f6e621bd783d77deecc4fe437504fa7e18f013ccbbb2c67d
- Size of remote file:
- 6.59 MB
- SHA256:
- 823d3cc014decd4660c78410b56402b2f6feba965f4d3ae752cc6a925d4b7381
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