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CIIRC-NLP
/
alquistcoder-intention_recognition-final

Text Classification
Transformers
Safetensors
modernbert
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use CIIRC-NLP/alquistcoder-intention_recognition-final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use CIIRC-NLP/alquistcoder-intention_recognition-final with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="CIIRC-NLP/alquistcoder-intention_recognition-final")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("CIIRC-NLP/alquistcoder-intention_recognition-final")
    model = AutoModelForSequenceClassification.from_pretrained("CIIRC-NLP/alquistcoder-intention_recognition-final")
  • Notebooks
  • Google Colab
  • Kaggle
alquistcoder-intention_recognition-final
1.59 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
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id0st
Upload tokenizer
6f1249a verified 8 months ago
  • .gitattributes
    1.52 kB
    initial commit 8 months ago
  • README.md
    5.17 kB
    Upload ModernBertForSequenceClassification 8 months ago
  • config.json
    1.44 kB
    Upload ModernBertForSequenceClassification 8 months ago
  • model.safetensors
    1.58 GB
    xet
    Upload ModernBertForSequenceClassification 8 months ago
  • special_tokens_map.json
    694 Bytes
    Upload tokenizer 8 months ago
  • tokenizer.json
    3.58 MB
    Upload tokenizer 8 months ago
  • tokenizer_config.json
    20.9 kB
    Upload tokenizer 8 months ago