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Kenpache
/
finbert-multilingual-v2

Text Classification
Transformers
Safetensors
modernbert
finance
financial-sentiment
sentiment-analysis
multilingual
financial-news
fintech
trading
market-sentiment
mmbert
cross-lingual
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use Kenpache/finbert-multilingual-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Kenpache/finbert-multilingual-v2 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="Kenpache/finbert-multilingual-v2")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("Kenpache/finbert-multilingual-v2")
    model = AutoModelForSequenceClassification.from_pretrained("Kenpache/finbert-multilingual-v2", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
finbert-multilingual-v2
1.26 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
Kenpache's picture
Kenpache
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  • .gitattributes
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  • README.md
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  • config.json
    2.1 kB
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  • model.safetensors
    1.23 GB
    xet
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  • tokenizer.json
    34.4 MB
    xet
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  • tokenizer_config.json
    573 Bytes
    Add files using upload-large-folder tool about 14 hours ago