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
Download code/laya-server/frontend/components.json from x6nux/laya-ad: direct link, hf CLI and curl.
- Browser
- Download file 387 Bytes
-
https://huggingface.co/x6nux/laya-ad/resolve/main/code/laya-server/frontend/components.json
- Command line
-
hf download hf://x6nux/laya-ad/code/laya-server/frontend/components.json
-
curl -L -o components.json https://huggingface.co/x6nux/laya-ad/resolve/main/code/laya-server/frontend/components.json
387 Bytes
| { | |
| "$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" | |
| } | |