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tutorials · 1 min read

Tutorial: Fine-Tune a Model Through Bhogar AI

Walkthrough of fine-tuning an OpenAI or open-source model on your data through the Bhogar AI fine-tuning pipeline.

BABhogar AI TeamProduct & Engineering

Fine-tuning sounds intimidating; the actual workflow is short and well-trodden. This tutorial fine-tunes a model on your data.

Why it matters

You will prepare a small training set (200-500 examples), kick off a fine-tune through the platform, evaluate, and route a fraction of traffic to the new model.

How Bhogar AI approaches it

Prepare JSONL training set, register fine-tune job, monitor progress, run eval against base model, deploy with traffic-split routing.

  • Prepare JSONL training data (200-500 examples)
  • Register fine-tune job
  • Evaluate vs base model
  • Deploy with traffic-split
  • Monitor and iterate

What you get

A working fine-tuned model with measured uplift and safe rollout - in days not months.

See Bhogar on your own data

Book a 45-minute working session. We connect one of your sources, build one agent, run one governed workflow, and review the trace together.