TinyLlama vs. Llama 2

The TinyLlama project aims to pretrain a Llama model featuring 1.1 billion parameters, leveraging a vast dataset of 3 trillion tokens. With effective optimizations, this challenging endeavor can be accomplished in only 90 days, making use of 16 A100-40G GPUs for processing power. By preserving the same architecture and tokenizer as Llama 2, we ensure that TinyLlama remains compatible with a range of open-source projects built upon Llama. Moreover, the model's streamlined architecture, with its 1.1 billion parameters, renders it ideal for various applications that demand minimal computational power and memory. This adaptability allows developers to effortlessly incorporate TinyLlama into their current systems and processes, fostering innovation in resource-constrained environments. As a result, TinyLlama not only enhances accessibility but also encourages experimentation in the field of machine learning.

We are excited to unveil the latest version of our open-source large language model, which includes model weights and initial code for the pretrained and fine-tuned Llama language models, ranging from 7 billion to 70 billion parameters. The Llama 2 pretrained models have been crafted using a remarkable 2 trillion tokens and boast double the context length compared to the first iteration, Llama 1. Additionally, the fine-tuned models have been refined through the insights gained from over 1 million human annotations. Llama 2 showcases outstanding performance compared to various other open-source language models across a wide array of external benchmarks, particularly excelling in reasoning, coding abilities, proficiency, and knowledge assessments. For its training, Llama 2 leveraged publicly available online data sources, while the fine-tuned variant, Llama-2-chat, integrates publicly accessible instruction datasets alongside the extensive human annotations mentioned earlier. Our project is backed by a robust coalition of global stakeholders who are passionate about our open approach to AI, including companies that have offered valuable early feedback and are eager to collaborate with us on Llama 2. The enthusiasm surrounding Llama 2 not only highlights its advancements but also marks a significant transformation in the collaborative development and application of AI technologies. This collective effort underscores the potential for innovation that can emerge when the community comes together to share resources and insights.