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:
- 96493fc1f4fc8e0f522cbb170a45de6ed0abed9e3168c2b918917d7fcf3793e0
- Size of remote file:
- 6.59 MB
- SHA256:
- 86d17c71d4c881c4b0c0d89804a1dc24832a73a015f67e71ace9aca585c6195e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.