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x6nux
/
laya-ad

Text Classification
Transformers
Safetensors
Chinese
spam-detection
advertising-detection
ad-classification
chinese
modernbert
mmbert
multi-task
four-head
Model card Files Files and versions
xet
Community

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
laya-ad
3.47 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 9 commits
x6nux's picture
x6nux
README: 路由说明改为四头口径(scope/severity 头)
c4a7829 verified 8 days ago
  • bf16
    laya-ad v2.2: six precision dirs 8 days ago
  • code
    README: 路由说明改为四头口径(scope/severity 头) 8 days ago
  • fp16
    laya-ad v2.2: six precision dirs 8 days ago
  • fp32
    laya-ad v2.2: six precision dirs 8 days ago
  • fp8
    laya-ad v2.2: six precision dirs 8 days ago
  • int4
    laya-ad v2.2: six precision dirs 8 days ago
  • int8
    laya-ad v2.2: six precision dirs 8 days ago
  • .gitattributes
    133 Bytes
    laya-ad v2: one dual-head model (binary + 7-class kind), six precision dirs 9 days ago
  • README.md
    10.9 kB
    README: 指标说明(测试集来源、每个指标定义与读法、四头对应的生产决策) 8 days ago