#OpenNMT

CTranslate2 facilitates efficient Transformer model inference with techniques like weight quantization and layer fusion, optimizing memory usage on both CPU and GPU. Supporting encoder-decoder, decoder-only, and encoder-only model types, it integrates seamlessly with multiple frameworks. Features include fast execution, reduced precision support, and minimal storage needs. The library's capabilities, such as automatic CPU selection, parallel processing, and ease of use in Python and C++, make it a reliable option for production use, distinctly outperforming general-purpose deep learning frameworks.