DemoPerforming Fine Tuning Part 2

After completing your fine-tuning job, you can immediately evaluate your custom model either from the command line or within a Python script. This guide walks you through both methods.

1. Test Your Fine-Tuned Model via CLI

Use the openai api completions.create command and specify your fine-tuned model’s ID, which you can copy from the fine-tuning job output:

openai api completions.create \
  -m "davinci:ft-janakiram-associates:sotu-qna-2023-08-05-17-12-17" \
  -p "When was the State of the Union presented?\n\n###\n\n" \
  --stop "['END','***']"

Example response:

When was the State of the Union presented?

### 

The State of the Union was presented on February 5, 2023.

Tip

Replace the model ID with your own fine-tuned model name. You can find it in the CLI output or in your OpenAI Dashboard.

2. Fine-Tuning Workflow Overview

Here’s a quick summary of the end-to-end fine-tuning process:

Step	Description	CLI Example
1	Prepare the dataset (clean & format JSONL)	`openai tools fine_tunes.prepare_data -f data.jsonl`
2	Upload and preprocess	Handled automatically by the API
3	Create and monitor the fine-tune job	`openai api fine_tunes.create -t data_prepared.jsonl -m davinci`
4	Test your deployed custom model	Use CLI (`completions.create`) or integrate via code

For detailed instructions, see the OpenAI Fine-Tuning Guide.

3. Test Your Model in Python

This Python example demonstrates:

Configuring your API key
Adding a suffix to control responses
Looping through multiple prompts
Printing questions with answers

import os
import openai

# ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]