OpenAI expands its custom model training program for developers
OpenAI has recently announced an expanded version of its custom model to get more control over the fine-tuning API. With this, the developers can now generate more tailored API solutions for the enterprise.
Last year at the inaugural developer conference, OpenAI launched its custom model. At that time the company claimed that around 2 million developers developed their API for developing solutions for different complex problems. OpenAI announced an AI assistant for the developers so that they can build their own “agent-like experiences.” the company said,” Developers can make agents that retrieve outside knowledge or call programming functions for a specific action. The use cases range includes an assistant for coding to an AI-powered vacation planner.” Here is the OpenAI Expanded Custom model:
This new announcement includes many features for the developers like checkpoint creation, fine-tuning dashboards, and many more. Below is a detailed overview of these features to help you get started.
Also read: OpenAI built a voice ai tool
New fine-tuning API and custom features:
Fine-tuning offers better training for the model so that it can generate better code in any particular language. Now with the new features, it can automatically generate a full fine-tuned model checkpoint, even in the case of overfitting. Offering a side playground to check the quality and performance of the model.
The new custom model is beyond the fine-tuning features. This also includes advanced features like “Hyperparameter Configuration”, “Comprehensive Validation Metrics” and “Third-party Integration”, so that developers can easily share the data with their stacks.
“We believe that in the future, the vast majority of organizations will develop customized models that are personalized to their industry, business, or use case,” OpenAI writes in a blog post. “With a variety of techniques available to build a custom model, organizations of all sizes can develop personalized models to realize more meaningful, specific impact from their AI implementations.”, OpenAI says.
Explaining their custom model trained model, OpenAI says that for industries where we need to train a model from scratch, this can imbue new knowledge there. To justify their statement the company has taken the example of Harvey, which is an AI tool for attorneys. The company says that after modifying the trained model process, “Harvey’s resulting model achieved an 83% increase in factual responses and attorneys preferred the customized model’s outputs 97% of the time over GPT-4.”
OpenAI has now unveiled the fine-tuning features for developers who are working with GPT 3.5. It will help the developers to create more advanced solutions.
