Instructions to use codemanCheng/lora-trained-xl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use codemanCheng/lora-trained-xl 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("codemanCheng/lora-trained-xl") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee

- Xet hash:
- ac9671dd5dee10b8d2b24898c2337d64c35cab1b976fbec4a4d2a8c75ba22feb
- Size of remote file:
- 1.77 MB
- SHA256:
- dedd47652394e0ed89acb4cd5583e1c1ee04c27d629059ce84d58b53a2a86299
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