Instructions to use willhx/train_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use willhx/train_lora 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("willhx/train_lora") prompt = "a photo of sofa" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download image_1.png from willhx/train_lora: direct link, hf CLI and curl.
- Browser
- Download file 356 kB
-
https://huggingface.co/willhx/train_lora/resolve/main/image_1.png
- Command line
-
hf download hf://willhx/train_lora/image_1.png
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curl -L -o image_1.png https://huggingface.co/willhx/train_lora/resolve/main/image_1.png
356 kB
