Instructions to use ostris/primal_vae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ostris/primal_vae with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ostris/primal_vae", 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 config.json from ostris/primal_vae: direct link, hf CLI and curl.
- Browser
- Download file 223 Bytes
-
https://huggingface.co/ostris/primal_vae/resolve/main/config.json
- Command line
-
hf download hf://ostris/primal_vae/config.json
-
curl -L -o config.json https://huggingface.co/ostris/primal_vae/resolve/main/config.json
223 Bytes
| { | |
| "_class_name": "PrimalVAE", | |
| "_diffusers_version": "0.36.0", | |
| "auto_map": { | |
| "AutoModel": "modeling_primal_vae.PrimalVAE" | |
| }, | |
| "weights": [ | |
| "primal_vae_2x1.safetensors", | |
| "primal_vae_2x2.safetensors" | |
| ] | |
| } |