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nutrientdocs
/
grounding-en

Text Classification
Transformers
ONNX
Safetensors
English
modernbert
grounding
hallucination-detection
fact-verification
nli
zero-shot-classification
document-ai
cross-encoder
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use nutrientdocs/grounding-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use nutrientdocs/grounding-en with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="nutrientdocs/grounding-en")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("nutrientdocs/grounding-en")
    model = AutoModelForSequenceClassification.from_pretrained("nutrientdocs/grounding-en")
  • Notebooks
  • Google Colab
  • Kaggle
grounding-en
1.59 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
hung-k-nguyen's picture
hung-k-nguyen
Update README.md
e81654f verified about 12 hours ago
  • onnx
    Public release 1 day ago
  • .gitattributes
    1.52 kB
    Public release 1 day ago
  • README.md
    4.5 kB
    Update README.md about 12 hours ago
  • config.json
    2.27 kB
    Public release 1 day ago
  • model.safetensors
    792 MB
    xet
    Public release 1 day ago
  • tokenizer.json
    3.58 MB
    Public release 1 day ago
  • tokenizer_config.json
    379 Bytes
    Public release 1 day ago