Text Classification
Transformers
PyTorch
TensorFlow
JAX
Safetensors
English
bert
financial-sentiment-analysis
sentiment-analysis
text-embeddings-inference
Instructions to use Narsil/finbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Narsil/finbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Narsil/finbert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Narsil/finbert") model = AutoModelForSequenceClassification.from_pretrained("Narsil/finbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from Narsil/finbert: direct link, hf CLI and curl.
- Browser
- Download file 1.88 kB
-
https://huggingface.co/Narsil/finbert/resolve/main/README.md
- Command line
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hf download hf://Narsil/finbert/README.md
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curl -L -o README.md https://huggingface.co/Narsil/finbert/resolve/main/README.md
1.88 kB
| language: en | |
| tags: | |
| - financial-sentiment-analysis | |
| - sentiment-analysis | |
| widget: | |
| - text: Stocks rallied and the British pound gained. | |
| duplicated_from: ProsusAI/finbert | |
| 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. [Financial PhraseBank](https://www.researchgate.net/publication/251231107_Good_Debt_or_Bad_Debt_Detecting_Semantic_Orientations_in_Economic_Texts) by Malo et al. (2014) is used for fine-tuning. For more details, please see the paper [FinBERT: Financial Sentiment Analysis with Pre-trained Language Models](https://arxiv.org/abs/1908.10063) and our related [blog post](https://medium.com/prosus-ai-tech-blog/finbert-financial-sentiment-analysis-with-bert-b277a3607101) on Medium. | |
| The model will give softmax outputs for three labels: positive, negative or neutral. | |
| --- | |
| About Prosus | |
| Prosus is a global consumer internet group and one of the largest technology investors in the world. Operating and investing globally in markets with long-term growth potential, Prosus builds leading consumer internet companies that empower people and enrich communities. For more information, please visit www.prosus.com. | |
| Contact information | |
| Please contact Dogu Araci dogu.araci[at]prosus[dot]com and Zulkuf Genc zulkuf.genc[at]prosus[dot]com about any FinBERT related issues and questions. | |
| --- | |
| FinBERT in Use (New!) | |
| We are delighted to hear the use of FinBERT at many other organisations. Please, let us know your use-case if you have FinBERT deployed and we add you to this list: | |
| - Prosus | |
| - Huggingface | |
| - Moodys Analytics | |
| - ING | |
| API Implementations | |
| - [Multilingual Rapid API](https://rapidapi.com/financial-sentiment-financial-sentiment-default/api/finbert3/) |