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huggingface/evaluation-guidebook

0
View on GitHub↗
2,125 stars·124 forks·Jupyter Notebook·10 views

Evaluation Guidebook

Sharing both practical insights and theoretical knowledge about LLM evaluation that we gathered while managing the Open LLM Leaderboard and designing lighteval!

Features

  • Model Evaluation - Guide for ensuring model performance on specific tasks.

Star history

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How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Projects sharing features with Evaluation Guidebook

These projects share indexed features with Evaluation Guidebook. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • nvidia/isaac-gr00tNVIDIA avatar

    NVIDIA/Isaac-GR00T

    6,222View on GitHub↗
    Jupyter Notebook
    View on GitHub↗6,222
  • sjwhitworth/golearnsjwhitworth avatar

    sjwhitworth/golearn

    9,438View on GitHub↗

    GoLearn is a machine learning library for the Go programming language. It provides a supervised learning framework and a toolkit for building, training, and evaluating predictive models through a standardized interface. The project implements a data frame system that loads CSV files into structured grids for matrix operations. It includes a preprocessing library for discretizing continuous variables and a model evaluation toolkit that utilizes confusion matrices and cross-validation to measure precision and recall. The library covers data engineering and management, including the ability to

    Go
    View on GitHub↗9,438
  • ageron/handson-mlageron avatar

    ageron/handson-ml

    25,608View on GitHub↗

    This is a machine learning educational repository consisting of a collection of notebooks and code examples. It provides practical implementations of diverse machine learning algorithms and workflows, ranging from traditional scientific computing to deep learning. The project features specific implementations of Scikit-Learn models, such as decision trees, random forests, and support vector machines, as well as TensorFlow examples for building neural networks, convolutional layers, and recurrent architectures. It also includes tutorials on reinforcement learning development and the creation o

    Jupyter Notebook
    View on GitHub↗25,608
  • alibaba-damo-academy/medevalkitalibaba-damo-academy avatar

    alibaba-damo-academy/MedEvalKit

    239View on GitHub↗

    MedEvalKit: A Unified Medical Evaluation Framework

    Python
    View on GitHub↗239
Compare all 30 related projects→

Frequently asked questions

What does huggingface/evaluation-guidebook do?

Sharing both practical insights and theoretical knowledge about LLM evaluation that we gathered while managing the Open LLM Leaderboard and designing lighteval!

What are the main features of huggingface/evaluation-guidebook?

The main features of huggingface/evaluation-guidebook are: Model Evaluation.

Which projects share features with huggingface/evaluation-guidebook?

Projects with overlapping indexed features include: sjwhitworth/golearn — GoLearn is a machine learning library for the Go programming language. It provides a supervised learning framework and… nvidia/isaac-gr00t. ageron/handson-ml — This is a machine learning educational repository consisting of a collection of notebooks and code examples. It… alibaba-damo-academy/medevalkit — MedEvalKit: A Unified Medical Evaluation Framework. confident-ai/deepeval — Deepeval is a framework for testing and evaluating large language model applications. It provides a suite of tools for… cluebenchmark/supercluelyb — SuperCLUE琅琊榜:中文通用大模型匿名对战评价基准.