I think the documentation only explains how to use the model through an API but that does not allow much flexibility nor automation.
I think the documentation only explains how to use the model through an API but that does not allow much flexibility nor automation.
The general flow of fine tuning Open AI models consists of creating an account, having a valid API key and then uploading the data for fine tuning using the CLI tool, as described here: https://beta.openai.com/docs/guides/fine-tuning
Then to test against question answering benchmarks, like SQuAD you simply dowload the dataset, create a script that takes the questions (see below json snippet) and feeds to your model by calling the API as described here (using curl): https://beta.openai.com/docs/api-reference/making-requests
"question": "What century did the Normans first gain their separate identity?",
"id": "56ddde6b9a695914005b962c",
"answers": [
{
"text": "10th century",
"answer_start": 671
},
{
"text": "the first half of the 10th century",
"answer_start": 649
},
{
"text": "10th",
"answer_start": 671
},
{
"text": "10th",
"answer_start": 671
}
],
"is_impossible": false