The Second Generation of Meta's Open-Source and Commercial-Grade Large Language Model
Get StartedLlama 2 comes in 70 billion, 130 billion, and 700 billion parameter variants, allowing you to choose the one that fits your needs best.
Llama 2 has been pretrained on 2 trillion tokens, with a context length twice that of Llama 1 (4096 tokens), providing a more comprehensive understanding of language.
The model has undergone fine-tuning with over a million human-annotated examples, ensuring its reliability and usability in real-world scenarios.
Llama2 achieves state-of-the-art results on many NLP benchmarks, outperforming previous models. However, some errors are still to be expected.
Llama2 can be used for a variety of NLP tasks like summarization, translation, question answering, and more. Its commercial-grade capabilities make it suitable for real-world applications.
Meta has implemented safety measures into Llama2, but users should still be cautious and monitor its outputs. Do not deploy it in high-stakes environments without thorough testing.
Llama2 was trained on a massive diverse dataset of public online content using self-supervision. It also received task-specific fine-tuning on human annotations.
Yes, Llama2 is designed to be customizable. You can fine-tune it on your own data and tasks to adapt it for your needs.
Llama2 is released under the CC-BY-NC 4.0 license, allowing commercial use with attribution.
There are three model sizes available: 7 billion, 13 billion, and 70 billion parameters. The larger models are more powerful but require more compute.
Yes, Llama2 was trained on data in over 100 languages, giving it broad multilingual capabilities.
Check out the technical paper at https://arxiv.org/abs/2212.01513 for details on Llama2's architecture, training, and capabilities.
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