Machine Learning TabFM: Zero-Shot Table Predictions That Beat XGBoost
Run Google's TabFM on real tabular data. No tuning, no feature engineering, one forward pass.
How-to content for builders, indie hackers, and AI engineers. Less theory, more shipped code.
Machine Learning Run Google's TabFM on real tabular data. No tuning, no feature engineering, one forward pass.
Tutorials Use GPT-5.6's Responses API so the model writes JavaScript to run your tools in one call.
Tutorials Install Nous Research's self-improving agent, run it on a local model, and build a reusable skill.
Tutorials Use GPT-5.6 Sol's new max reasoning effort and ultra subagents via the Responses API.
Tutorials A runnable Python governor that caps LLM spend per user and auto-downgrades models.
Tutorials Stream Gemini's thought summaries live, control reasoning effort, and track thinking-token cost.
Tutorials Cut MCP agent context up to 99% by exposing tools as a code API the model calls in code.
Tutorials Port your MCP server to the stateless 2026-07-28 spec using the explicit-handle pattern.
Tutorials Build a frugal tool-calling coding agent on NVIDIA's open Nemotron 3 Nano via OpenRouter in Python.
Tutorials Let a cheap executor model consult a stronger advisor mid-task in one Messages API call.
Tutorials Build a provider-agnostic LLM failover client in Python that survives outages and model removals.
Tutorials Gemini's image preview models die June 25. Swap to the Nano Banana 2 GA IDs with verified Python.