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Fine tuning

Provides a unified layer to fine tune LLMs. By training on a subset of your data, the model can produce more relevant and accurate outputs for your particular use cases.

Supported Providers​

Intellinode supports fine-tuning with openai provider in the current version.

Parameters​

To fine-tune a model for your application, you'll need configuration parameters including:

  • provider: The AI service provider ('openai').
  • apiKey: Your API key for accessing the provider.
  • trainingData: Your fine-tuning dataset, formatted as jsonl.
  • model: (Optional) The specific model you're fine-tuning if the provider supports multiple models.

Example​

This node example demonstrates initiating a fine-tuning task with openai provider:

Openai embedding

  1. Prepare the imports.
const { RemoteFineTuneModel, SupportedFineTuneModels, FineTuneInput } = require('intellinode');
const { createReadStream } = require("fs");
const FormData = require("form-data");

  1. Upload the tuning file.
// read the file
const filePath = './temp/training_data.jsonl'

const filePayload = new FormData();
filePayload.append('file', createReadStream(filePath));
filePayload.append('purpose', 'fine-tune');

// upload the file to openai platform
const file = await tuner.uploadFile(filePayload)
  1. Start the tuning task using the file id.
const input = new FineTuneInput({
    model: 'gpt-3.5-turbo',
    training_file: file.id
})

const result = await tuner.generateFineTune(input)
  1. List fine tuning tasks and results.
const list = await tuner.listFineTune()

const value = list.data.filter(b => b.id === result.id)
console.log('Fine tuning Model Result:\n', value, '\n');