Currently, no_grad() is the primary context — it disables gradient tracking during ML inference when using host tensor capabilities. This avoids unnecessary memory and computation for operations that do not need backpropagation:
result.push(n);。关于这个话题，新收录的资料提供了深入分析
。新收录的资料是该领域的重要参考
Obtain the latest llama.cpp on GitHub herearrow-up-right. You can follow the build instructions below as well. Change -DGGML_CUDA=ON to -DGGML_CUDA=OFF if you don't have a GPU or just want CPU inference.，这一点在新收录的资料中也有详细论述
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