Archives for large language models - Page 6
“Training GPT-3 with 175 billion parameters would require approximately 36 years with 8 V100 GPUs.” Training large machine learning models calls for huge compute power (~in hundreds of exaflops), efficient memory management for a reduced memory footprint and other tweaks. But, language models have grown at a great pace. In a span of two years,…
The post How To Take Full Advantage Of GPUs In Large Language Models appeared first on Analytics India Magazine.
GPT-3’s Cheap Chinese Cousin
Chinese company Huawei has developed PanGu Alpha, a 750-gigabyte model that contains up to 200 billion parameters.
The post GPT-3’s Cheap Chinese Cousin appeared first on Analytics India Magazine.
Behind NVIDIA’s Megatron
The team performed training iterations on models with a trillion parameters at 502 petaFLOP/s on 3072 GPUs by combining three techniques.
The post Behind NVIDIA’s Megatron appeared first on Analytics India Magazine.