Fine-tuned Llama 3.1 8B outperforms GPT-4o-mini on invoice extraction

Nexus Labs conducted a shadow test comparing a fine-tuned Llama 3.1 8B model against OpenAI's gpt-4o-mini for invoice line-item extraction. The fine-tuned model demonstrated superior accuracy by 1.8 points and reduced per-call costs by 71%, despite an initial hallucination rate of 1.1% for a specific field. The testing utilized Bifrost's load balancing and custom plugin capabilities to mirror production traffic without impacting live responses, allowing for offline comparison of outputs. AI

IMPACT Demonstrates the viability of fine-tuned open-source models for specific enterprise tasks, potentially reducing costs and improving performance over general-purpose commercial models.

RANK_REASON The article details the use of a fine-tuned open-source model in a production setting, comparing its performance and cost against a commercial model, which falls under tool usage and evaluation.

Read on dev.to — LLM tag →

• Bifrost
• gpt-4o-mini
• LiteLLM
• Llama 3.1 8B
• Nexus Labs
• OpenAI
• Portkey

• model release
• product

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