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LHF
/
FinEAS

Text Classification
Transformers
PyTorch
English
bert
finance
sentiment analysis
regression
sentence bert
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use LHF/FinEAS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use LHF/FinEAS with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="LHF/FinEAS")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("LHF/FinEAS")
    model = AutoModelForSequenceClassification.from_pretrained("LHF/FinEAS")
  • Notebooks
  • Google Colab
  • Kaggle
FinEAS
439 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 8 commits
asier-gutierrez's picture
asier-gutierrez
Update README.md
61006c8 over 4 years ago
  • .gitattributes
    1.18 kB
    initial commit over 4 years ago
  • README.md
    2.58 kB
    Update README.md over 4 years ago
  • config.json
    851 Bytes
    model over 4 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

    • "torch.LongStorage",
    • "collections.OrderedDict",
    • "torch.FloatStorage",
    • "torch._utils._rebuild_tensor_v2"

    What is a pickle import?

    438 MB
    xet
    model over 4 years ago
  • special_tokens_map.json
    112 Bytes
    model over 4 years ago
  • tokenizer.json
    466 kB
    model over 4 years ago
  • tokenizer_config.json
    449 Bytes
    model over 4 years ago
  • vocab.txt
    232 kB
    model over 4 years ago