Instructions to use wangjian21/VG_16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wangjian21/VG_16 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_16") prompt = "Van Gogh's style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- d0c4a39f4364a2453f2d1fdb710dc90febc8b69433a7fde42c8ff97faac21334
- Size of remote file:
- 527 kB
- SHA256:
- d7a50f837c6008ecd96b959eb18ee6c74a96619794173fe89aacf1440d196744
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.