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ahmedrachid
/
FinancialBERT-Sentiment-Analysis

Text Classification
Transformers
PyTorch
English
bert
financial-sentiment-analysis
sentiment-analysis
text-embeddings-inference
Model card Files Files and versions
xet
Community
6

Instructions to use ahmedrachid/FinancialBERT-Sentiment-Analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ahmedrachid/FinancialBERT-Sentiment-Analysis with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="ahmedrachid/FinancialBERT-Sentiment-Analysis")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("ahmedrachid/FinancialBERT-Sentiment-Analysis")
    model = AutoModelForSequenceClassification.from_pretrained("ahmedrachid/FinancialBERT-Sentiment-Analysis")
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
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Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Request: DOI

#6 opened over 1 year ago by
stani000

Add evaluation results on the sentences_allagree config and train split of financial_phrasebank

#5 opened over 2 years ago by
autoevaluator

Does the program support num_labels = 2?

1
#4 opened over 2 years ago by
ewmiao

Adding `safetensors` variant of this model

#3 opened about 3 years ago by
SFconvertbot

Accuracy

👍 2
#2 opened almost 4 years ago by
ehrencrona
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