Instructions to use carvychen/china_chic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use carvychen/china_chic 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("carvychen/china_chic") prompt = "chinachic1" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee

- Xet hash:
- 21091149cf0c35698df1601f11b417e2ed8b0e18f4b9ca8440f782fb936ed222
- Size of remote file:
- 1.58 MB
- SHA256:
- 1d455b3888a32c1711838164f9691f7d64a263d2d9e372637e4a9ff57eba698a
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