Instructions to use Masterjp123/AnythingV5Nijimix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Masterjp123/AnythingV5Nijimix with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Masterjp123/AnythingV5Nijimix", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e537d8ae90ee617372cc78c52c1579c8e133b4e6dc437b7ed8b6705ffa56f7c1
- Size of remote file:
- 2.13 GB
- SHA256:
- ace957f270e5a712c50c4eb825679b9e474ada99866c6d6a1f5c92d8172e1838
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.