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Awesome GitHub RepositoriesModel Optimization Toolkits
Software suites for improving the performance and efficiency of trained machine learning models.
Distinguishing note: Covers broader optimization techniques including quantization and memory management, distinct from pure inference runtimes.
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- karpathy/nanochat
karpathy/nanochat
43,699View on GitHubNanochat is a lightweight execution environment designed for training and running language models on standard consumer hardware. It functions as both a neural network training framework and an inference engine, enabling users to perform backpropagation-based training and model execution directly on general-purpose processors without the need for dedicated graphics hardware. The project distinguishes itself through a suite of optimization tools that prioritize efficiency on local machines. By utilizing memory-mapped weight loading and CPU-optimized vector math, it maximizes throughput for inte
A set of optimization tools that adjust numerical precision for weights and activations to balance memory consumption and computational speed during inference.
Python
