Showing 121-140 of 230 projects
Reference implementations of MLPerfยฎ training benchmarks for evaluating machine learning performance.
RLBench is a large-scale benchmark and learning environment for reinforcement learning agents.
A benchmarking toolkit for fair and scalable time series forecasting, focused on long-term traffic prediction.
A rigorous benchmark for evaluating the code quality and efficiency of large language models like GPT-4.
RoboVerse is a unified platform, dataset, and benchmark for scalable and generalizable robot learning.
A simple, fast, and accurate C++ microbenchmarking library that can be included as a single header file.
Benchmark for Go HTTP request router and web framework performance
A comprehensive and fair benchmark for time series forecasting methods, including deep learning and statistical techniques.
A quickstart and benchmark for PyTorch distributed training, useful for ML/AI developers.
An open-source toolbox and benchmark for model compression and acceleration in PyTorch.
A benchmark for evaluating the performance of large language models (LLMs) on complex terminal-based tasks.
Benchmarks for evaluating Go serialization methods for performance and efficiency.
A PyTorch-based framework for reproducible deep learning studies with 26 knowledge distillation methods.
A survey paper on evaluating large language models (LLMs) for developers building AI-powered applications.
A comprehensive benchmark for JavaScript minification tools, comparing performance and size metrics.
A simple open-source disk benchmark tool for Linux distros, focused on performance testing.
A powerful vision-language foundation model designed to advance multimodal AI understanding and reasoning.
A comprehensive benchmark for document parsing and evaluation, designed for CVPR 2025.
A collection of prebuilt iperf3 binaries for Windows, enabling developers to easily benchmark their network limits.
A benchmark for evaluating knowledge transfer in lifelong robot learning using AI tools.
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