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Transformer Lab App: An Open Source Platform for Frontier AI/ML Workflows
Transformer Lab App is an open-source machine learning research platform designed for frontier AI/ML workflows. It provides a comprehensive toolkit for large language models, allowing users to train, tune, and chat on their own machines, whether locally, on-prem, or in the cloud. Backed by Mozilla, this cross-platform application simplifies experimentation with a wide range of models.
GenerativeAICourse: A Comprehensive Hands-On Generative AI Engineering Course
This repository offers a comprehensive, hands-on Generative AI course, starting from fundamental AI concepts to building production-grade applications. It focuses on AI engineering, covering topics like LLMs, RAG, AI agents, and prompt engineering with practical tutorials. The course aims to equip learners with the skills needed to build real-world AI solutions.
Lance: Modern Columnar Data Format for ML and LLMs
Lance is a modern columnar data format, implemented in Rust, designed for machine learning and large language model workflows. It offers significant performance improvements over Parquet for random access, includes vector indexing, and supports data versioning. Compatible with popular tools like Pandas, DuckDB, and PyTorch, Lance streamlines data management for ML applications.
Instructor: Structured Outputs for LLMs with Pydantic and Python
Instructor is a powerful Python library that simplifies extracting structured data from Large Language Models (LLMs). It integrates Pydantic for robust validation, type safety, and IDE support, eliminating the need for manual JSON parsing, error handling, and retries. This tool provides a streamlined and reliable way to get structured outputs from any LLM.
Stagehand: The AI Browser Automation Framework for Production
Stagehand is an innovative AI browser automation framework that expertly blends the precision of code with the adaptability of natural language. Designed for production environments, it empowers developers to choose between writing low-level Playwright code for specific tasks and leveraging high-level AI agents for dynamic interactions. This framework also enhances the automation process with features like action previewing, intelligent caching, and seamless integration with advanced computer use models.