ceadar-ie/FinanceConnect-13B
FinanceConnect-13B is a 13 billion parameter chat model developed by CeADAR Connect Group, built on the Llama2-13B architecture with a 4096-token context length. It is fine-tuned on FinTalk-19k and Alpaca datasets, specializing in finance and economic discussions. This model serves as a valuable resource for finance professionals, researchers, and enthusiasts, demonstrating strong performance on financial benchmarks like FPB and MMLU.
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FinanceConnect-13B: A Specialized Financial LLM
FinanceConnect-13B is an open-source, 13 billion parameter chat model developed by CeADAR Connect Group, specifically designed for finance and economic discussions. Built upon the Llama2-13B architecture, it has been extensively fine-tuned using the FinTalk-19k and Alpaca datasets, making it a highly specialized resource for the financial industry.
Key Capabilities
- Domain Specialization: Optimized for conversations and content generation related to finance and economics.
- Performance: Achieves competitive benchmark scores, notably outperforming BloombergGPT 50B on MMLU (52.08 vs 39.8) and FPB (57.2 vs 51.1) at a significantly lower cost.
- Accessibility: Offers a straightforward Python API for integration and content generation.
- Efficiency: Designed for efficient performance on both CPU and GPU platforms.
Use Cases
- Financial Research: Aiding researchers with insights and information on financial topics.
- Professional Support: Assisting finance professionals with domain-specific queries.
- Educational Tool: Providing enthusiasts with detailed explanations and discussions on economic concepts.
Limitations
- Primarily focused on financial tasks; not optimized for general conversations or non-financial domains.
- May contain biases from its training datasets (FinTalk-19k, Alpaca).
- Lacks human-like understanding and has a knowledge cut-off based on its last training update.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.