BloombergGPT: A Large Language Model for Finance
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Abstract
The use of NLP in the realm of financial technology is broad and complex, with applications ranging from sentiment analysis and named entity recognition to question answering. Large Language Models (LLMs) have been shown to be effective on a variety of tasks; however, no LLM specialized for the financial domain has been reported in literature. In this work, we present BloombergGPT, a 50 billion parameter language model that is trained on a wide range of financial data. We construct a 363 billion token dataset based on Bloomberg's extensive data sources, perhaps the largest domain-specific dataset yet, augmented with 345 billion tokens from general purpose datasets. We validate BloombergGPT on standard LLM…
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Keywords
- Computer science
- Variety (cybernetics)
- Construct (python library)
- Language model
- Machine learning
- Domain (mathematical analysis)
- Realm
- Artificial intelligence
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