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: 387 Bytes
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"$schema": "https://ui.shadcn.com/schema.json",
"style": "new-york",
"rsc": false,
"tsx": true,
"tailwind": {"config": "", "css": "src/index.css", "baseColor": "neutral", "cssVariables": true, "prefix": ""},
"aliases": {"components": "@/components", "utils": "@/lib/utils", "ui": "@/components/ui", "lib": "@/lib", "hooks": "@/hooks"},
"iconLibrary": "lucide"
}
|