2026 Guide: Pure‑CPU Open‑Source Chinese TTS Models Optimized for Performance

This article reviews the most capable open‑source Chinese text‑to‑speech models that run entirely on CPU in 2026, compares their quantization and speed features, recommends acceleration engines, outlines five hard‑won optimization rules, and provides a concise selection guide for various deployment scenarios.

CPU inferenceChinese TTSONNX Runtime

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2026 Guide: Pure‑CPU Open‑Source Chinese TTS Models Optimized for Performance

Code Wrench

Oct 16, 2025 · Artificial Intelligence

Build a Go‑Powered Stock Trend Predictor with ONNX Runtime in Minutes

This guide walks you through setting up an Ubuntu environment, training a LightGBM stock‑movement model in Python, exporting it to ONNX, and deploying fast, cross‑platform inference in Go using ONNX Runtime, complete with code snippets and project structure.

AIGoLightGBM

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Build a Go‑Powered Stock Trend Predictor with ONNX Runtime in Minutes

DataFunSummit

Sep 1, 2025 · Artificial Intelligence

How We Cut ERNIE Model Resource Use by 75% with Pruning, Structured Slimming, and ONNX Runtime

In this detailed engineering guide we diagnose a heavyweight ERNIE‑Base text‑classification service consuming 128 CPU cores and 96 GB RAM, then apply a three‑step optimization—model selection, structured pruning with PaddleSlim, and engine migration to ONNX Runtime—achieving a 75% reduction in resource usage while keeping recall above 99.5% and boosting inference speed by over 20%.

AI model optimizationModel PruningONNX Runtime

0 likes · 11 min read

How We Cut ERNIE Model Resource Use by 75% with Pruning, Structured Slimming, and ONNX Runtime

Network Intelligence Research Center (NIRC)

Apr 28, 2025 · Artificial Intelligence

Export a PyTorch Model to ONNX and Extract Intermediate Layer Features

This article walks through exporting a PyTorch image‑classification model to ONNX, identifying a hidden layer node, adding it as an output, and using ONNX Runtime to retrieve both the final prediction and the intermediate feature tensor.

ONNXONNX RuntimePyTorch

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Export a PyTorch Model to ONNX and Extract Intermediate Layer Features