Instructions to use wangjian21/VG_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wangjian21/VG_v2 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_v2") prompt = "Van Gogh" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 369c7ed7c521ab26ac19bef9a5e81f0a894f598e984bd2350813e79aee3cd6fc
- Size of remote file:
- 602 kB
- SHA256:
- 060121d8c2d9144b512fb08eb6781b20db8a2e65f652d6973cb09803303a3984
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.