Model Tuning Without Labeled Data! Directly Elevating Llama 3.3 70B to GPT-4o Level
Boost LLMs like Llama 3.3 70B to GPT-4o level with Databricks' TAO—no labeled data needed! Unlock enterprise AI tuning at lower costs.
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At this stage, the difficulty in fine-tuning large language models (LLMs) lies in the fact that people typically lack high-quality labeled data.
Recently, the AI company Databricks introduced a new tuning method called TAO, which requires only input data and no labeled data to complete the process.
Even more surprisingly, TAO outperforms supervised fine-tuning based on labeled data in terms of performance.
As is well known, LLMs struggle to adapt to new enterprise-level tasks. Prompting is prone to errors and offers limited quality improvements, while fine-tuning requires large amounts of labeled data, which is unavailable for most enterprise tasks.