Instructions to use Muapi/tangfeng-netidol-face with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/tangfeng-netidol-face with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muapi/tangfeng-netidol-face") 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
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license: openrail++
library_name: diffusers
base_model: black-forest-labs/FLUX.1-dev
tags:
- lora
- text-to-image
- stable-diffusion
- flux
- flux.1-d
pipeline_tag: text-to-image
---
# Tangfeng Netidol Face

**Base model**: Flux.1 D
**Trained words**: upper body, 1girl, a young woman, a chinese female, straight neckline dudou, floral embroidery pattern wide sleeves, see through chiffon hanfu, see through chinese clothes, skinny and petite physique, moist eyes, hourglass figure, fair skin, hair ornament, hair flower, braided updo, long hair, forehead mark, facial mark, realistic, portrait, chinese palace, garden, willow, railings, waterside, rainbow gradient dress, gesture, sunset,
## 🧠 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/flux_dev_lora_image"
headers = {"Content-Type": "application/json", "x-api-key": os.getenv("MUAPIAPP_API_KEY")}
payload = {
"prompt": "masterpiece, best quality, 1girl, looking at viewer",
"model_id": [{"model": "civitai:895914@1002536", "weight": 1.0}],
"width": 1024,
"height": 1024,
"num_images": 1
}
print(requests.post(url, headers=headers, json=payload).json())
```
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