Lead story
Models & availability
Latest
Lead story
Models & availability
Latest
A case study from Capital Fund Management (CFM) leveraging open-source LLMs and the Hugging Face Ecosystem for Named Entity Recognition (NER) on financial data, achieving up to 6.4% accuracy improvement and 80x cost reduction by fine-tuning small models with LLM-assisted labeling.
From the source
By leveraging LLM-assisted labeling with HF Inference Endpoints and refining data with Argilla, the team improved accuracy by up to 6.4% and reduced operational costs, achieving solutions up to 80x cheaper than large LLMs alone.
huggingface.co