Text Classification
Transformers
Safetensors
Chinese
spam-detection
advertising-detection
ad-classification
chinese
modernbert
mmbert
multi-task
four-head
Instructions to use x6nux/laya-ad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use x6nux/laya-ad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="x6nux/laya-ad")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("x6nux/laya-ad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 770 Bytes
0cd599e | 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 | {
"name": "laya-server",
"private": true,
"version": "0.1.0",
"license": "Apache-2.0",
"type": "module",
"scripts": {
"dev": "vite --host 127.0.0.1",
"build": "tsc -b && vite build",
"lint": "eslint ."
},
"dependencies": {
"@tailwindcss/vite": "^4.1.0",
"class-variance-authority": "^0.7.1",
"cn": "^0.3.2",
"lucide-react": "^0.468.0",
"radix-ui": "^1.6.7",
"react": "^19.1.0",
"react-dom": "^19.1.0",
"tailwindcss": "^4.1.0"
},
"devDependencies": {
"@types/node": "^24.0.0",
"@types/react": "^19.1.0",
"@types/react-dom": "^19.1.0",
"@vitejs/plugin-react": "^5.0.0",
"typescript": "^5.9.0",
"vite": "^7.1.0"
},
"packageManager": "pnpm@11.19.0"
}
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