FinLang/finance embeddings investopedia This is the Investopedia embedding for finance application by the FinLang team. The model is trained using our open sourced finance dataset from https://huggingface.co/datasets/FinLang/investopedia embedding dataset This is a finetuned embedding model on top of BAAI/bge base en v1.5. It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search in RAG applications. This project is for research purposes only. Third party datasets may be subject to additional terms and conditions under their associated licenses. Plans The research paper will be published soon. We are working on a v2 version of the model where we are increasing the training corpus of financial data and using improved techniques for training embeddings. Usage (LLamaIndex) Simply specify the Finlang embedding during the indexing procedure for your Financial RAG applications. Usage (Sentence Transformers) Using this model becomes easy when you have sentence transformers installed (see https://huggingface.co/sentence transformers): Then you can use the model like this: Example code testing: Evaluation Results We e…
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