Instructions to use codemanCheng/lora-trained-xl_demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use codemanCheng/lora-trained-xl_demo 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_demo") prompt = "a photo of sks cat" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- e1ede99b6cd485ccfb1ccb8503ec8dae002834f4b767d77a9d4dd253cc75b6c0
- Size of remote file:
- 23.7 MB
- SHA256:
- 5afb7d8a6772e99cb1ef5adece04408888157f8fb6f1b7f581a8665a5b5c953c
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