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How to post-train a model for your own task and data with Aibuildai LLM Posttrain Agent

Point a run at a folder with your task statement and data files, then start post-training.

Who it is forA developer at a company who has proprietary data and a scoring script and wants the agent to tune a base model for that use case.

The problemHand-running many post-training experiments is expensive, and each change needs a fresh evaluation.

The outcomeA run that reads your task folder, writes its own score program, and produces a deliverable model package or task-defined result.

What you need first

  • Linux x86_64 with a systemd user session and Python 3.11 to 3.13
  • A C toolchain (gcc, make) with zlib and readline headers, plus bwrap (bubblewrap) with unprivileged user namespaces enabled
  • A Claude Code login or an Anthropic API key, or an Anthropic-compatible endpoint and its key
  • A CUDA GPU is recommended
  • Network access to GitHub releases and ftp.postgresql.org

Steps

  1. Complete the install steps for the repo and set AIBUILDAI_API_KEY or sign in with claude auth login
  2. Print the starter config with aibuildai config > task.yaml, or copy examples/gsm8k-qwen3-1.7b-base.yaml
  3. Set run.data_root in task.yaml to your task folder with the statement, the data files, and any readme
  4. Start the run with aibuildai run task.yaml
  5. Open the printed workspace URL to follow the run and check the private and deliverable folders when it ends

Prompt for your agent

Using the aibuildai-llm-posttrain-agent repo, create a task.yaml with run.data_root set to <task_folder>, then run `aibuildai run task.yaml`. Expected output: a deliverable directory and a score program under private/. Verify that the score program exists and reads the task folder before the run starts.

Caveat. The README says a serious run needs larger budgets than the example, so plan for longer runtimes and check the cost limit, which is a soft limit.

Use this in your AI agent

Ask your agent

Using the Deduped MCP, get the setup steps for aibuildai-inc/aibuildai-llm-posttrain-agent and "Post-train a model for your own task and data"

Add Deduped to Claude Code once

claude mcp add --transport http deduped https://dedupedai.com/mcp

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