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ML Intern

ML Intern is an open-source AI agent from Hugging Face that autonomously researches academic papers, builds datasets, writes code, and ships production-quality machine learning workflows. Unlike standard agents, ML Intern deeply understands the Hugging Face ecosystem — it reads papers on arXiv, walks citation graphs, finds the right datasets, and executes the full LLM post-training loop from literature review to model training. Released in April 2026 and still trending in June, it is designed for ML researchers and engineers who want to automate the repetitive parts of the research-to-production pipeline. The agent is available as a GitHub repository and a Hugging Face Space, and has been featured in multiple benchmarks showing it can match or exceed Claude Code on scientific reasoning tasks. It represents a significant step toward autonomous ML engineering.

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codemap is an MIT-licensed project brain for AI coding tools that gives LLMs instant architectural context from your codebase without burning tokens. It generates a fast tree/context view, dependency flow, dependency blast-radius analysis, and a layered handoff format for cross-agent continuation, then exposes everything through a JSON context bundle and an MCP server compatible with Claude Code and Codex. A built-in Codex plugin and community skill registry make it easy to install and share. Developers use codemap to onboard agents to large repos in seconds, keep session continuity across handoffs, and scope the impact of a change before running it.

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