Playmaker vs. Restructured vs. StarCoder vs. Wing Python IDE Comparison Chart

Playmaker is a document automation platform that transforms unstructured data from various sources, such as PDFs, images, spreadsheets, and web data, into actionable, structured formats. It offers over 100 templated document workflows, including financial statements, purchase orders, invoices, and contracts, enabling users to streamline processes like data extraction, validation, and integration with other applications. Users can import documents via email, API, or manual upload, and the platform converts this unstructured data into clear, tabular formats suitable for powering workflows across more than 300 applications. Playmaker emphasizes security and compliance, with data stored and processed exclusively in the European Union and the United States, adherence to regulations like GDPR and CCPA, and features such as AES-256 encryption and role-based access control.

StarCoder and StarCoderBase are Large Language Models for Code (Code LLMs) trained on permissively licensed data from GitHub, including from 80+ programming languages, Git commits, GitHub issues, and Jupyter notebooks. Similar to LLaMA, we trained a ~15B parameter model for 1 trillion tokens. We fine-tuned StarCoderBase model for 35B Python tokens, resulting in a new model that we call StarCoder. We found that StarCoderBase outperforms existing open Code LLMs on popular programming benchmarks and matches or surpasses closed models such as code-cushman-001 from OpenAI (the original Codex model that powered early versions of GitHub Copilot). With a context length of over 8,000 tokens, the StarCoder models can process more input than any other open LLM, enabling a wide range of interesting applications. For example, by prompting the StarCoder models with a series of dialogues, we enabled them to act as a technical assistant.