Instructions to use Muapi/juggernaut-cinematic-xl-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/juggernaut-cinematic-xl-lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muapi/juggernaut-cinematic-xl-lora") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
| license: openrail++ | |
| library_name: diffusers | |
| base_model: stabilityai/stable-diffusion-xl-base-1.0 | |
| tags: | |
| - lora | |
| - text-to-image | |
| - stable-diffusion-xl | |
| - sdxl | |
| - sdxl-1.0 | |
| pipeline_tag: text-to-image | |
| # Juggernaut Cinematic XL LoRA | |
|  | |
| **Base model**: SDXL 1.0 | |
| **Trained words**: Movie Still, Film Still, Cinematic, Cinematic Shot, Cinematic Lighting | |
| ## 🧠 Usage (Python) | |
| 🔑 **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys) | |
| ```python | |
| import requests, os | |
| url = "https://api.muapi.ai/api/v1/sdxl-lora-image" | |
| headers = {"Content-Type": "application/json", "x-api-key": os.getenv("MUAPIAPP_API_KEY")} | |
| payload = { | |
| "prompt": "masterpiece, best quality", | |
| "lora_model": "juggernaut-cinematic-xl-lora", | |
| "lora_strength": 1.0, | |
| "width": 1024, | |
| "height": 1024, | |
| "num_images": 1 | |
| } | |
| print(requests.post(url, headers=headers, json=payload).json()) | |
| ``` | |