DS-1000

benchmark

[ICML 2023] Data and code release for the paper "DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation".

How to download and setup DS-1000

Open terminal and run command

git clone https://github.com/xlang-ai/DS-1000.git

git clone is used to create a copy or clone of DS-1000 repositories. You pass git clone a repository URL.
it supports a few different network protocols and corresponding URL formats.

Also you may download zip file with DS-1000 https://github.com/xlang-ai/DS-1000/archive/master.zip

Or simply clone DS-1000 with SSH

[email protected]:xlang-ai/DS-1000.git

If you have some problems with DS-1000

You may open issue on DS-1000 support forum (system) here: https://github.com/xlang-ai/DS-1000/issues

Similar to DS-1000 repositories

Here you may see DS-1000 alternatives and analogs

netdata primesieve fashion-mnist FrameworkBenchmarks BenchmarkDotNet jmeter awesome-semantic-segmentation sysbench hyperfine tsung benchmark_results across web-frameworks php-framework-benchmark jsperf.com go-web-framework-benchmark huststore phoronix-test-suite Attabench ann-benchmarks sbt-jmh caffenet-benchmark chillout IocPerformance prophiler TBCF NBench sympact awesome-http-benchmark BlurTestAndroid