70 billion parameter LLaMA2 model training accelerated by 195% with best foundation model practice upgraded
<p>Initially triggered by ChatGPT, the large model boom is continuing to intensify. Tech giants and star startups are scrambling to contribute models for the competitive and diversified commercial market. Among these models, the LLaMA series has accumulated a vast amount of users and practical applications due to its basic capabilities and open ecology. For countless open-source model latecomers, it has become a benchmark model for imitation and comparison.</p>
<p>However, key bottlenecks still exist for AIGC-related enterprises, including questions about how developers can reduce pre-training costs of big models like LLaMA2, as well as how they can build these models practically using continual pre-training and fine-tuning.</p>
<p>As the world’s largest and most active community for large model development tools, Colossal-AI provides revolutionary <strong>LLaMA2 training efficiency for 8 to 512 GPUs, fine-tuning, and inference solutions</strong>. The 70 billion parameter training can be accelerated by 195%, and provides <strong>a fully-managed ML cloud platform solution</strong>, greatly reducing the cost of large model development and applications.</p>
<p><a href="https://medium.com/syncedreview/70-billion-parameter-llama2-model-training-accelerated-by-195-with-best-foundation-model-practice-74b12e0620c5"><strong>Visit Now</strong></a></p>