Instructions to use Muapi/juggernaut-reborn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/juggernaut-reborn with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Muapi/juggernaut-reborn", 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
Juggernaut Reborn
Base model: SD 1.5
Originally published by stablediffusionapi. Mirrored here for use with muapi.ai โ a unified API for generative media.
๐ง Usage via muapi.ai
๐ Get your MUAPI key from muapi.ai/access-keys
import requests, os
url = "https://api.muapi.ai/api/v1/sd-image"
headers = {"Content-Type": "application/json", "x-api-key": os.getenv("MUAPIAPP_API_KEY")}
payload = {
"prompt": "masterpiece, best quality",
"model": "juggernaut-reborn",
"width": 512,
"height": 512,
"num_images": 1
}
print(requests.post(url, headers=headers, json=payload).json())
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