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nhanv
/
VBHC-classify

Text Classification
Transformers
Safetensors
electra
Generated from Trainer
Model card Files Files and versions
xet
Community

Instructions to use nhanv/VBHC-classify with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use nhanv/VBHC-classify with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="nhanv/VBHC-classify")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("nhanv/VBHC-classify")
    model = AutoModelForSequenceClassification.from_pretrained("nhanv/VBHC-classify")
  • Notebooks
  • Google Colab
  • Kaggle
VBHC-classify
537 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 2 commits
hoang.dang1
update
824ead0 about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    1.17 kB
    update about 2 years ago
  • all_results.json
    406 Bytes
    update about 2 years ago
  • config.json
    2.04 kB
    update about 2 years ago
  • eval_results.json
    230 Bytes
    update about 2 years ago
  • model.safetensors
    535 MB
    xet
    update about 2 years ago
  • special_tokens_map.json
    125 Bytes
    update about 2 years ago
  • tokenizer.json
    1.4 MB
    update about 2 years ago
  • tokenizer_config.json
    1.27 kB
    update about 2 years ago
  • train_results.json
    196 Bytes
    update about 2 years ago
  • vocab.txt
    411 kB
    update about 2 years ago