Open Source Breakthrough: Tenyx’s Llama3 70B Model Outperforms GPT-4

Open Source Breakthrough: Tenyx’s Llama3 70B Model Outperforms GPT-4

In a significant development for the AI industry, Tenyx has announced the release of its latest model, Llama3-TenyxChat-70B, which not only matches but surpasses the performance metrics of OpenAI's GPT-4-0314 on several benchmarks. This milestone is particularly noteworthy as it marks the first time an open-source model enhanced by proprietary learning technology has outperformed any variant of GPT-4.

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A New Era in Language Model Performance

Llama3-TenyxChat-70B, a product of Tenyx’s cutting-edge fine-tuning approach, has achieved the highest rankings, among open-sourced models, on the MT-Bench evaluation, consisting of 80 complex multi-turn questions across diverse domains such as Writing, Reasoning, and STEM. This has proven to be a formidable benchmark, pushing the limits of what AI models can understand and how effectively they can respond.

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Tenyx’s proprietary technology utilizes the Direct Preference Optimization (DPO) framework, enabling the model to retain a high level of performance without succumbing to the common pitfalls of catastrophic forgetting—a significant issue where models lose their ability to recall previously learned information upon training on new data.

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A Technical Innovation in Adaptability & Reasoning 

The backbone of Llama3-TenyxChat-70B's success lies in its learning paradigm, which involves selective updating of model parameters to prevent the overwriting of existing knowledge. This method not only preserves the model's foundational knowledge but also enhances its capabilities.

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Llama3-TenyxChat-70B was trained with only eight A100 GPUs, demonstrating both efficiency and scalability in harnessing AI power for practical applications. This approach ensures that the TenyxChat model remains a top contender in the realm of language models by maintaining a balance between performance and computational efficiency.

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Notably, our approach significantly boosts the math and reasoning abilities of large language models (LLMs), a critical improvement given that the source of their emergent reasoning capabilities is still unknown. 

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1. On the MT bench benchmark, we improved the overall performance of  Llama3-70B from 7.96 to 8.15 across all categories (the scores range from 0 to 10). These are known to be challenging tasks to enhance. In fact, models are trained for months to get these capabilities. In contrast, with our approach trained for 15 hours on a well-known open-source dataset, we achieve this feat, notably improving reasoning by 1.3 points (from 5.4 to 6.7). 

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2. On the Open-LLM Leaderboard, several datasets are evaluated. We highlight the improvement in math capabilities through GSM8K (https://arxiv.org/pdf/2110.14168v1). This evaluation dataset consists of 8.5k linguistically diverse grade school math problems (therefore again a math-reasoning dataset). For this dataset, the state-of-the art model on the leaderboard is currently Llama3-70B with a score of 85.44, our fine-tuned model achieves 91.21, Therefore, our model is now state-of-the art of for this dataset by a large margin. It is again, important to consider that only 15 hours of training were capable of increasing by almost 6 points of percentage the base model on this math dataset. 

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Implications for the Future of AI

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The achievements of Llama3-TenyxChat-70B signal a promising direction for the future of AI development, particularly in the open-source community. By demonstrating that open-source models can exceed the capabilities of proprietary models like GPT-4, Tenyx is setting a new standard in the AI industry. This breakthrough is expected to spur further innovations and encourage a more collaborative environment where developers can build upon each other’s work to push the boundaries of what AI can achieve.

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As we celebrate this achievement, it's essential to recognize the broader implications for AI safety and efficacy. The ability of Llama3-TenyxChat-70B to perform at such a high level without compromising on safety or proficiency is a testament to the robustness of Tenyx's previous fine-tuning methodology. It is a step forward in creating more reliable, efficient, and accessible AI tools for everyone, marking a new chapter in the democratization of AI technology.

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Tenyx's commitment to enhancing and refining AI capabilities is designed to drive the industry forward, making advanced AI tools more accessible and effective for a wide range of applications. As we look to the future, the role of open-source models in leading AI innovation has never been more apparent.