Instructions to use codemanCheng/lora-trained-xl_350 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use codemanCheng/lora-trained-xl_350 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_350") prompt = "a photo of sks cat" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee

- Xet hash:
- 108a8bf789ada242467710672de0891c415be524eae8c876f7def6aa3408d460
- Size of remote file:
- 1.44 MB
- SHA256:
- 8adee61f7b20c385bd72b02bc30fea2ff53a6d03897f61fd536401120d3229d9
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