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
Commit History
8 days ago
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laya-ad v2.2: six precision dirs
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9 days ago
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laya-ad v2.1: six precision dirs
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chore: remove __pycache__ from v2 code
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laya-ad v2: one dual-head model (binary + 7-class kind), six precision dirs
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10 days ago
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laya-ad v1.1:六精度权重 + 模型卡 + 项目代码快照
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