
npm i @onepunya/hugging-face-loader 




```javascript
const trained = require('@onepunya/hugging-face-loader');
// Take the hugging face model for example: https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0 in huggingface.co

trained("cute girl", "hugging face key", "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0")
  .then(data => console.log(data)) // result is arraybuffer you can use "fs". to save the image
  .catch(err => console.error(err));
  
  npm i fs
  
fs.writeFileSync(data, `/image.jpg`)
```


## Kontak Pengembang Api

see available models and apikey at [hugging face](https://huggingface.co/)

- GitHub: [Link GitHub](https://github.com/onepunya)
- Whatsapp: [WhatsApp group](https://chat.whatsapp.com/FRL4FzReE0X4qf8Yy80RkW)

@onepunya/hugging-face-loader

onepunya

hugging-face-loader

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@onepunya/hugging-face-loader

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