Instructions to use Muapi/sailor-mercury with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/sailor-mercury with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("OnomaAIResearch/Illustrious-xl-early-release-v0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muapi/sailor-mercury") 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
File size: 1,390 Bytes
c3bc601 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 | ---
license: openrail++
library_name: diffusers
base_model: OnomaAIResearch/Illustrious-xl-early-release-v0
tags:
- lora
- text-to-image
- stable-diffusion-xl
- illustrious
- illustrious
pipeline_tag: text-to-image
---
# Sailor Mercury

**Base model**: Illustrious
**Trained words**: sailor mercury,blue eyes,blue hair,short hair,parted bangs,medium breasts,tiara,blue back bow,blue sailor collar,blue skirt,(0light blue bow:2),long back bow,choker,earrings,gloves,jewelry,heart brooch,magical girl,miniskirt,pleated skirt,sailor collar,sailor senshi uniform,leotard,skirt,stud earrings,sleeveless,, mizuno ami,solo,blue eyes,blue hair,short hair,medium breasts,skirt,blue skirt,blue sailor collar,school uniform,sailor collar,pleated skirt,blue back bow,serafuku,short sleeves,puffy sleeves,red bow,puffy short sleeves,
## 🧠 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": "sailor-mercury",
"lora_strength": 1.0,
"width": 1024,
"height": 1024,
"num_images": 1
}
print(requests.post(url, headers=headers, json=payload).json())
```
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