Popular GitHub Repositories for Recruitment Test

? An exciting game of programming and Artificial Intelligence

Test your prompts, agents, and RAGs. Red teaming, pentesting, and vulnerability scanning for LLMs. Compare performance of GPT, Claude, Gemini, Llama, and more. Simple declarative configs with command line and CI/CD integration.

Evidently is ??an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

Qodo-Cover: An AI-Powered Tool for Automated Test Generation and Code Coverage Enhancement! ????

Open source data anonymization and synthetic data platform for developers. Anonymize your production data and sync it across your environments so that developers can safely use it.

Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.

a delightful machine learning tool that allows you to train, test, and use models without writing code

Curated tutorials and resources for Large Language Models, Text2SQL, Text2DSL、Text2API、Text2Vis and more.

An open source framework for building AI-powered apps with familiar code-centric patterns. Genkit makes it easy to develop, integrate, and test AI features with observability and evaluations. Genkit works with various models and platforms.

Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!

UpTrain is an open-source unified platform to evaluate and improve Generative AI applications. We provide grades for 20+ preconfigured checks (covering language, code, embedding use-cases), perform root cause analysis on failure cases and give insights on how to resolve them.

☔ 敏捷开发最强大易用的接口工具，机器学习零代码测试与 AI 问答、生成代码与静态检查、生成文档与光标悬浮注释，腾讯、华为、SHEIN、传音、工行等使用 ☔ The most advanced tool for HTTP API. Machine learning no-code testing and AI assistant, generating codes and static analysis, generating comments and floating hints. Used by Tencent, Huawei, SHEIN, TRANSSION, ICBC, etc.

The Declarative Data Generator

A secure sandbox environment for malware developers and red teamers to test payloads against detection mechanisms before deployment. Integrates with LLM agents via MCP for enhanced analysis capabilities.

Image Test Time Augmentation with PyTorch!

We introduced a new model designed for the Code generation task. Its test accuracy on the HumanEval base dataset surpasses that of GPT-4 Turbo (April 2024) and GPT-4o.

Toolkit for fine-tuning, ablating and unit-testing open-source LLMs.

Tensorflow implementation of YOLO, including training and test phase.

tensorflow implementation of 'YOLO : Real-Time Object Detection'(train and test)

TTRL: Test-Time Reinforcement Learning