Instructions to use kliyer/LoRAdapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kliyer/LoRAdapter with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("kliyer/LoRAdapter") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
Upload 2 files
Browse files
sd15-depth-128-only-res/struct/lora-checkpoint.pt
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sd15-depth-128-only-res/struct/mapper-checkpoint.pt
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oid sha256:111a2ba22b5ffa43bdd65f5d59e6b47d3fcd722a401f125532cdf2c951ecbdf0
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