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ZichenAI
/
layazh-zh

Text Classification
Transformers
Safetensors
Chinese
laya
system-one
calibrated-decisions
rlcd
chinese
classification
routing
scoring
guardrails
non-autoregressive
commercial-license-required
Model card Files Files and versions
xet
Community

Instructions to use ZichenAI/layazh-zh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ZichenAI/layazh-zh with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="ZichenAI/layazh-zh")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("ZichenAI/layazh-zh", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
layazh-zh / tokenizer
440 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
NovaAI
layazh-zh: Chinese System-1 decision model (Laya recipe, RoBERTa-large encoder + decision head); full-eval acc 0.6951 vs upstream 0.4783
f69ec12 verified 2 days ago
  • tokenizer.json
    439 kB
    layazh-zh: Chinese System-1 decision model (Laya recipe, RoBERTa-large encoder + decision head); full-eval acc 0.6951 vs upstream 0.4783 2 days ago
  • tokenizer_config.json
    394 Bytes
    layazh-zh: Chinese System-1 decision model (Laya recipe, RoBERTa-large encoder + decision head); full-eval acc 0.6951 vs upstream 0.4783 2 days ago