4 repos
Awesome GitHub RepositoriesModel Evaluation
Frameworks and metrics used to measure the accuracy, performance, and reliability of machine learning models.
Explore 4 awesome GitHub repositories matching artificial intelligence & ml · Model Evaluation. Refine with filters or upvote what's useful.
Awesome Model Evaluation GitHub Repositories
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- langchain-ai/langchain
LangChain is an orchestration framework designed for building, managing, and deploying applications powered by large language models. It provides a unified integration layer that normalizes disparate model provider APIs into a consistent set of primitives, enabling developers to build complex, multi-step AI workflows t
Pythonagentsaiai-agents - microsoft/generative-ai-for-beginners
This project is a comprehensive, open-source educational curriculum designed to guide developers through the mastery of generative artificial intelligence. It provides a structured learning path that covers foundational concepts, prompt engineering, and the practical application of large language models. The repository
Jupyter Notebookaiazurechatgpt - dair-ai/Prompt-Engineering-Guide
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 - ultralytics/ultralytics
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
Explore sub-tags
- Factuality BenchmarksMetrics and testing frameworks designed to measure the accuracy and truthfulness of model-generated content.
- LLM-as-a-Judge FrameworksTechniques and patterns for using large language models to evaluate the outputs of other models or systems.
- Model BenchmarkingProcesses for evaluating and comparing different language models.
- Model Capability AssessmentTools for benchmarking and selecting models based on specific requirements.