codara-model-trainer 0.1

OpenAI Model Trainer and Formatter

FineTuningDataCreator Package

Overview

The FineTuningDataCreator is a Python package designed to assist in creating datasets for fine-tuning machine learning models, particularly language models. It simplifies the process of gathering and formatting training data in a JSON Lines (JSONL) format.

Features

• Easy creation of training data sets in JSONL format.
• Methods to set system instructions, training prompts, and generative responses.
• Automatically handles file creation and appending data in the correct format.

Installation

No specific installation is required apart from having Python installed. The script uses standard Python libraries os and json.

Usage

1. Import the package:

   from fine_tuning_data_creator import FineTuningDataCreator
   

2. Create an instance of FineTuningDataCreator:

   data_creator = FineTuningDataCreator()
   

3. Set system content, training prompts, and generative responses as needed:

   data_creator.agent_instructions("System instructions here")
   data_creator.training_prompt("User prompt here")
   gpt_response = openai_api_call("User prompt here")
   data_creator.generative_response(gpt_response)
   

4. Create the data set:

   data_creator.create_data_set()
   

The data will be saved in the model-training/fine-tune-data-set.jsonl file.

Structure of Data

The data is structured in JSON Lines format, where each line is a valid JSON object. An example of the data structure:

{
  "messages": [
    {"role": "system", "content": "System instructions here"},
    {"role": "user", "content": "User prompt here"},
    {"role": "assistant", "content": "Model response here"}
  ]
}