Instructions to use bigshanedogg/Mage-Flow-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bigshanedogg/Mage-Flow-Base with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("bigshanedogg/Mage-Flow-Base", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Download vae/config.json from bigshanedogg/Mage-Flow-Base: direct link, hf CLI and curl.
- Browser
- Download file 183 Bytes
-
https://huggingface.co/bigshanedogg/Mage-Flow-Base/resolve/main/vae/config.json
- Command line
-
hf download hf://bigshanedogg/Mage-Flow-Base/vae/config.json
-
curl -L -o config.json https://huggingface.co/bigshanedogg/Mage-Flow-Base/resolve/main/vae/config.json
183 Bytes
| { | |
| "_class_name": "AutoencoderMageVAE", | |
| "_diffusers_version": "0.39.0", | |
| "auto_map": { | |
| "AutoModel": "autoencoder_mage_vae.AutoencoderMageVAE" | |
| }, | |
| "sample_posterior": true | |
| } |