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Orchestrate private LLM fine-tuning end to end without accessing client data.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "fine-tuning-os" yet — see the docs or source repo.
Help me convert customer support chats into a fine-tuning dataset, with cleaning, redaction, and schema suggestions.
A usable dataset schema, cleaning rules, and redaction guidance.
Design a fine-tuning and evaluation workflow for an enterprise QA model, including training settings, metrics, and baselines.
A training plan, evaluation metrics, and an executable experiment workflow.
Help me package a fine-tuned model for delivery, including security checks, model packaging, release notes, and a deployment checklist.
A secure delivery checklist, release notes, and deployment-ready materials.
Build, debug, and manage software tasks with natural language across LLMs.
Create and run custom multi-language tools dynamically for MCP clients.
Secure file and directory operations for autonomous AI development workflows.
Quickly integrate OpenAI image and audio generation through MCP-wrapped APIs.
Expose OpenAPI endpoints as MCP tools for LLM-driven REST API access.
Turn any OpenAPI spec into a working MCP server.