community-automations/drive-fine-tune

Research & Intel

PublicClaude subagent

OpenAI Fine-Tune Pipeline

Fine-tuning stalls on the boring parts: bad JSONL rows, duplicate examples, and babysitting the job. This pipeline handles the whole path from a Drive folder.

sonnet4 daysGoogle DriveOpenAIPythonWeights & Biases
ClaudeClaude
ROI for
README.md

Why this subagent

Fine-tuning stalls on the boring parts: bad JSONL rows, duplicate examples, and babysitting the job. This pipeline handles the whole path from a Drive folder.

It pulls your dataset, validates and cleans the format, splits train and validation, then launches the fine-tune and watches it finish. You get back the model ID and its validation loss, so the only thing you do is point it at the folder and choose a base model.

How it runs

    • Read

      Used at step 01 to kick off the pipeline.

    • Write

      Used at step 01 to kick off the pipeline.

    • WebFetch

      Used at step 01 to kick off the pipeline.

    • WebSearch

      Used at step 01 to kick off the pipeline.

Sample output

json
// Sample output
// (generated when the pipeline finishes)

Take a Drive dataset folder, validate and prepare it, launch an OpenAI fine-tune, and report the model ID and loss.

Unlock the rest

The full agent definition, install snippet, and starter task are gated for community members.

Members get the full `.md` agent file, the npm / pnpm install one-liners, a starter prompt that we've tuned against real runs, and the open-source repo when this automation ships there. One email, magic link, done.