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Symflower Launches DevQualityEval: A New Benchmark for Enhancing Code Quality in Large Language Models Symflower has recently introduced DevQualityEval, an innovative evaluation benchmark and framework designed to elevate the code quality generated by large language models (LLMs). This release will allow developers to assess and improve LLMs’ capabilities in real-world software development scenarios. DevQualityEval offers a standardized benchmark and framework that allows developers to measure & compare the performance of various LLMs in generating high-quality code. This tool is useful for evaluating the effectiveness of LLMs in handling complex programming tasks and generating reliable test cases. By providing detailed metrics and comparisons, DevQualityEval aims to guide developers and users of LLMs in selecting suitable models for their needs. The framework addresses the challenge of assessing code quality comprehensively, considering factors such as code compilation success, test coverage, and the efficiency of generated code. This multi-faceted approach ensures that the benchmark is robust and provides meaningful insights into the performance of different LLMs. Read our full take on 'DevQualityEval': https://lnkd.in/guRuBjaB GitHub: https://lnkd.in/grssvCVR Symflower #artificialintelligence #ai #datascience #llms
Asif Razzaq, interesting tool for developer assessment. How accurate is it?
Benchmarking LLMs to check how well they write quality code as CTO and Founder at Symflower. Only connect if you want to talk about using Symflower or one of my projects. No sales/leads, no HR search. Seriously!
2moThanks for mentioning! We released a new version https://www.linkedin.com/feed/update/urn:li:activity:7204389845278822400/ and are on our way to write a new deep dive for that new version. In case you are using an LLM or are even creating/fine-tuning one: would love your feedback on the direction of the eval. Ping me!