ReaderLM-v2 is a 1.5B parameter language model developed by Jina AI, designed for converting raw HTML into clean markdown and JSON with high accuracy and improved handling of longer contexts. It supports multilingual text in 29 languages and offers advanced features such as direct HTML-to-JSON extraction. The model improves upon its predecessor by addressing issues like repetition in long sequences and enhancing markdown syntax generation.
ReaderLM-v2 is a 1.5B parameter language model designed to convert raw HTML into beautifully formatted markdown or JSON. It supports multilingual input and offers improved longer context handling, stability, and advanced markdown generation capabilities.
Learn how GPU acceleration can significantly speed up JSON processing in Apache Spark, reducing runtime and costs for enterprise data applications.
MarkItDown is a utility for converting various files to Markdown, including PDF, PowerPoint, Word, Excel, Images, Audio, HTML, text-based formats, and ZIP files.
GitHub Models now allows developers to retrieve structured JSON responses from models directly in the UI, improving integration with applications and workflows. Supported models include OpenAI (except for o1-mini and o1-preview) and Mistral models.
A new plugin for sqlite-utils CLI tool called sqlite-utils-ask allows users to ask human-language questions directly of SQLite databases and CSV/JSON files, using an LLM to generate SQL queries and execute them.
Docling is a tool that parses documents and exports them to desired formats like Markdown and JSON. It supports various document formats and provides advanced PDF understanding, metadata extraction, and integration with LlamaIndex and LangChain for RAG / QA applications.
Docling is a tool that parses documents and exports them to desired formats like Markdown and JSON. It supports various document formats including PDF, DOCX, PPTX, Images, HTML, AsciiDoc, and Markdown.
A new plugin for LLM, llm-jq, generates and executes jq programs based on human-language descriptions, allowing users to manipulate JSON data without needing to write jq syntax.
The author records a screen capture of their Gmail account and uses Google Gemini to extract numeric values from the video.