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As large models such as the ERNIE 4.5 family continue to be open-sourced, interest in their inference performance and deployment efficiency has multiplied across both research and industry. FastDeploy 2.0, built on the PaddlePaddle framework, addresses this demand by offering an end-to-end toolkit for efficient deployment and high-performance inference of large models.

We introduce ERNIE 4.5, a new family of large-scale multimodal models comprising 10 distinct variants. The model family consist of Mixture-of-Experts (MoE) models with 47B and 3B active parameters, with the largest model having 424B total parameters, as well as a 0.3B dense model.