Unlock the true potential of GPT-3 by training your own personalized model! By customizing your model with domain-specific data, you can create a powerful AI assistant tailored to your unique needs. Imagine having your own AI-powered blog writer that mimics your writing style, making it easier to maintain a consistent online presence. Or how about an AI that understands the intricacies of your codebase and helps you debug and optimize your code? Solo entrepreneurs can benefit immensely from a customized GPT-3 model that's trained to assist with tasks like customer support, personalized outreach, drafting proposals, and even generating marketing ideas. In short, training your own GPT-3 model opens up a world of possibilities and empowers you to supercharge your productivity, creativity, and efficiency! 🚀
Step 1: Install the OpenAI CLI
First, you need to install the OpenAI CLI on your machine. Open your terminal and run the following command:
pip install openai
Step 2: Set up your API key
Export your OpenAI API key as an environment variable:
export OPENAI_API_KEY=<your_api_key>
Step 3: Prepare your training data
Create a JSONL file containing your training examples. In this case, we're using blog-related prompts:
{"prompt": "What is Midjounrey?", "completion": "<an explanation of what Midjourney is>"}
{"prompt": "How does Midjounrey work?", "completion": "<an explanation of how Midjourney works>"}
{"prompt": "What are all of Midjounrey's parameters and what do they do?", "completion": "<a list of all parameters Midjourney has and explanations for each>"}
{"prompt": "Give me a list of amazing Midjounrey's prompts by the community?", "completion": "<a list of all your favorite Midjourney prompts>"}
Save this file as train_data.jsonl.
Step 4: Train your custom GPT-3 model with the Davinci model
Now, use the OpenAI CLI to train your custom GPT-3 model with the Davinci model as the base model. Replace <path_to_train_data.jsonl> with the path to your train_data.jsonl file.
openai api fine_tunes.create -m davinci --n_epochs 3 \
-t <path_to_train_data.jsonl>
Step 5: Training the model with additional data
If you want to train your model with more data, simply add new examples to your train_data.jsonl file and run the fine-tuning command again. The updated model will be trained on the new data.
Step 6: Use your custom model
Once your model is trained, you can use it with the OpenAI API. Replace <model_ID> with the ID of your custom model:
openai api completions.create -m <model_ID> \
--max-tokens 30 --temperature 0 --stop "###" \
-p "Your prompt here"
And that's it! 🎉 You've successfully trained a custom GPT-3 model using the OpenAI CLI, and you can now use it to generate more accurate and personalized results. Enjoy your supercharged GPT-3 model! Don't forget to follow for more exciting tips and tricks! 😊
Top comments (1)
That's excellent, thanks ... I didn't expect that it would be so simple to extend GPT-3. Do you know if we can expect more or less the same for GPT-4 ?