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Model Evaluation and Analysis · Awesome GitHub Repositories

9 repos

Awesome GitHub RepositoriesModel Evaluation and Analysis

Tools and frameworks for measuring, benchmarking, and monitoring the performance and quality of machine learning models.

Explore 9 awesome GitHub repositories matching artificial intelligence & ml · Model Evaluation and Analysis. Refine with filters or upvote what's useful.

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Awesome Model Evaluation and Analysis GitHub Repositories

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  • mlabonne/llm-course

    mlabonne/llm-course

    75,340GitHubView on GitHub↗

    This project is a comprehensive educational curriculum and engineering handbook focused on the lifecycle of large language models. It serves as a structured knowledge base for machine learning practitioners, covering the fundamental mathematical and architectural principles of transformer-based sequence modeling, as we

    courselarge-language-modelsllm
  • dair-ai/Prompt-Engineering-Guide

    dair-ai/Prompt-Engineering-Guide

    70,526GitHubView on GitHub↗

    This project is a comprehensive educational resource and knowledge base dedicated to the development and application of large language models and autonomous agentic systems. It provides a structured framework for understanding prompt engineering, context management, and the architectural patterns required to build task

    MDXagentagentsai-agents
  • OpenHands/OpenHands

    OpenHands/OpenHands

    67,974GitHubView on GitHub↗

    OpenHands is an autonomous agent framework designed for software engineering workflows. It provides a modular platform for orchestrating AI agents that reason, plan, and execute tasks within isolated, containerized development environments. By integrating with standard version control and development tools, the system

    Pythonagentartificial-intelligencechatgpt
  • scikit-learn/scikit-learn

    scikit-learn/scikit-learn

    65,178GitHubView on GitHub↗

    Scikit-learn is a machine learning library for predictive data analysis that provides a collection of algorithms for supervised and unsupervised learning. It functions as a comprehensive toolkit for data preprocessing, dimensionality reduction, and model selection, allowing users to classify data objects, predict conti

    Pythondata-analysisdata-sciencemachine-learning
  • FoundationAgents/MetaGPT

    FoundationAgents/MetaGPT

    64,304GitHubView on GitHub↗

    MetaGPT is an agentic workflow engine and multi-agent orchestration framework designed to automate complex software engineering and data analysis tasks. It functions as an automated software factory that transforms high-level natural language requirements into functional web applications, technical documentation, and p

    Pythonagentgptllm
  • keras-team/keras

    keras-team/keras

    63,858GitHubView on GitHub↗

    Keras is a high-level deep learning framework designed for constructing and training neural networks through the composition of modular, functional layers. It serves as a comprehensive modeling toolkit that provides standardized procedures for defining, evaluating, and deploying complex architectures. By utilizing a di

    Pythondata-sciencedeep-learningjax
  • ultralytics/yolov5

    ultralytics/yolov5

    56,830GitHubView on GitHub↗

    YOLOv5 is a comprehensive computer vision framework designed for end-to-end deep learning, specializing in real-time object detection, image classification, and instance segmentation. It provides a unified toolkit that manages the entire lifecycle of a model, from initial dataset configuration and hyperparameter tuning

    Pythoncoremldeep-learningios
  • ultralytics/ultralytics

    ultralytics/ultralytics

    53,426GitHubView on GitHub↗

    Ultralytics is a comprehensive computer vision framework designed for training, validating, and deploying deep learning models across a wide range of visual recognition tasks. It provides a unified interface for core operations including object detection, instance segmentation, pose estimation, and image classification

    Pythonclicomputer-visiondeep-learning
  • unslothai/unsloth

    unslothai/unsloth

    52,461GitHubView on GitHub↗

    Unsloth is a high-performance training and inference platform designed to optimize the lifecycle of large language and multimodal models. It provides a comprehensive engine for fine-tuning, executing, and managing models locally, with a focus on reducing memory consumption and increasing compute speed on consumer-grade

    Pythonagentdeepseekdeepseek-r1

Explore sub-tags

  • AI Design PatternsConceptual frameworks for structuring AI interactions, including the selection between deterministic workflows and autonomous agentic behaviors.
  • AI Evaluation Frameworks2 sub-tagsSystems that automate the assessment of artificial intelligence outputs and reasoning quality through comparative analysis or secondary model verification.
  • Artificial Intelligence Benchmarks3 sub-tagsStandardized tests and metrics used to measure the performance, reasoning capabilities, and context handling of artificial intelligence models.
Language Model Observability2 sub-tags
Tools for monitoring and tracking operational data such as token consumption, financial costs, and response latency in language model deployments.
  • Machine Learning Evaluation2 sub-tagsTools for assessing and comparing the performance metrics of trained machine learning models through validation and comparative analysis.
  • Model Analysis2 sub-tagsFrameworks for benchmarking model accuracy and speed while providing guidance on prompt engineering and generative consistency.
  • Stuck Agent DetectionMechanisms that identify and flag repetitive or circular action patterns in agent execution flows.