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License | llama3 |
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Context window(in thousands) | 8192 |
Arena Elo | 1152 |
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MMLU | 68.4 |
MT Bench | N/A |
Llama 3 Instruct (8B) offers top-notch response quality, with high Arena Elo ratings and impressive MT Bench scores for translation. Its MMLU score is exceptional, indicating strong reasoning and knowledge.
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The cost per 1,000 tokens for the Llama 3 Instruct (8B) model with Telnyx Inference is $0.0002. For instance, if an enterprise were to analyze 1,000,000 customer chats, each averaging 1,000 tokens, the total cost would be $200.
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Llama 3 8B Instruct is a large language model (LLM) known for its improved accuracy and cost-effectiveness. It outperforms previous generations like Llama 2, boasting a 28% improvement over Llama 2 70B and a 200% improvement over Llama 2 7B models. This is due to its training on over 15 trillion tokens, advanced optimization techniques, and instruction tuning tailored for dialogue use cases.
The model enhances training efficiency through optimization techniques like data parallelization and an advanced training stack. This setup automates error detection, handling, and maintenance, significantly boosting training efficiency and reliability.
Llama 3 8B Instruct boasts unique features such as instruction tuning optimized for dialogue, support for over 30 languages, and an advanced tokenizer with a 128K token vocabulary. These features contribute to its superior performance in chat interactions, code generation, and other tasks.
Yes, Llama 3 8B Instruct balances performance with cost efficiency, making it an ideal choice for real-world applications. Its deployment is more cost-effective compared to larger models, catering to a variety of use cases without compromising on quality.
Quantizing Llama 3 8B can lead to performance degradation due to its high-quality training data and efficient utilization of floating-point precision. Careful quantization methods are essential to minimize impact on performance.
While Llama 3 shares similarities with GPT models, it sets itself apart through its extensive training data, optimization techniques, and instruction tuning. It outperforms other open-source models like Llama 2 and Vicuna, showcasing its superior accuracy and efficiency.
You can integrate Llama 3 8B Instruct into your connectivity apps and other projects through platforms like Telnyx. For more information on getting started, visit Telnyx.
Llama 3 8B Instruct excels in various tasks including chat interactions, code generation, summarization, and retrieval-augmented generation. Its advanced features make it suitable for a wide range of applications looking for high accuracy and cost-effective solutions.