Instructions to use wangjian21/VG_8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wangjian21/VG_8 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("wangjian21/VG_8") prompt = "Van Gogh's style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 8a09f8cd1cc7ff49bfded0a05e665b3680c1effa5724d671cc55ddbf00ec1ecd
- Size of remote file:
- 535 kB
- SHA256:
- c8f92dca0ea6c33d36813d402ea0cae9dac005e268d45c6479fc4b9f55734719
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.