How to Build a T4-Friendly Autonomous Data Science Agent with DeepAnalyze-8B, Sandboxed Code Execution, and Iterative Analysis

We build an autonomous data science agent around DeepAnalyze-8B and run it end to end. We prepare a stable Colab runtime, install the machine-learning dependencies, and load the tokenizer and model in 4-bit mode to fit limited GPU memory.

We add a sandboxed execution environment that lets the model generate Python, run it safely, observe results, and continue in an agentic loop. We then hand the agent a multi-file e-commerce workspace and let it clean, join, analyze, visualize, and summarize the data as an analyst-grade report.