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Efficiency and Adaptability in Model Deployment
Model runtime efficiency is crucial for running large language models like LSTMs and transformer models effectively. Optimizing RAM usage, releasing models from memory when not in use, and using hardware accelerators are key considerations. The Onyx runtime, which is now native to Windows 11, offers excellent performance. To manage memory issues, the team incorporates Dart to C FFI, specifically for keeping T5 and LSTM models in memory. While smaller models are automatically updated and installed, larger models such as Loma require manual downloading due to varying user requirements and system capabilities, highlighting the importance of flexibility and adaptability in model deployment.