Instructions to use Viggle/Meridian with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Viggle/Meridian with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Viggle/Meridian", 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
Download assets/fixed_embed_90.pt from Viggle/Meridian: direct link, hf CLI and curl.
- Browser
- Download file 5.08 MB
-
https://huggingface.co/Viggle/Meridian/resolve/main/assets/fixed_embed_90.pt
- Command line
-
hf download hf://Viggle/Meridian/assets/fixed_embed_90.pt
-
curl -L -o fixed_embed_90.pt https://huggingface.co/Viggle/Meridian/resolve/main/assets/fixed_embed_90.pt
5.08 MB
- Xet hash:
- 2a8383396b450d5ece85718f0199b87cd260768f463cc16d4df61a2adc210077
- Size of remote file:
- 5.08 MB
- SHA256:
- a64703d16844bdda2724d3a262eafcfaf35522b97633a1d0743477350fd1eba3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.