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
YAML Metadata Error:"base_model" with value "../../pretrained/stable-diffusion-xl-base-1.0" is not valid. Use a model id from https://hf.co/models.
LoRA DreamBooth - carvychen/china_chic
These are LoRA adaption weights for ../../pretrained/stable-diffusion-xl-base-1.0. The weights were trained on chinachic1 using DreamBooth. You can find some example images in the following.
LoRA for the text encoder was enabled: True.
Special VAE used for training: ../../pretrained/sdxl-vae-fp16-fix.
- Downloads last month
- 1



