Text Classification
Transformers
PyTorch
TensorFlow
JAX
Safetensors
English
bert
financial-sentiment-analysis
sentiment-analysis
finance
Instructions to use ProsusAI/finbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProsusAI/finbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ProsusAI/finbert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ProsusAI/finbert") model = AutoModelForSequenceClassification.from_pretrained("ProsusAI/finbert", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
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- sentiment analysis
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FinBERT is a pre-trained NLP model to analyze sentiment of financial text. It is built by further training the BERT language model in the finance domain, using a large financial corpus and thereby fine-tuning it for financial sentiment classification. For the details, please see [FinBERT: Financial Sentiment Analysis with Pre-trained Language Models](https://arxiv.org/abs/1908.10063).
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- financial sentiment analysis
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- sentiment analysis
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widget:
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- text: "Stocks rallied and the British pound gained."
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---
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FinBERT is a pre-trained NLP model to analyze sentiment of financial text. It is built by further training the BERT language model in the finance domain, using a large financial corpus and thereby fine-tuning it for financial sentiment classification. For the details, please see [FinBERT: Financial Sentiment Analysis with Pre-trained Language Models](https://arxiv.org/abs/1908.10063).
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