GPT-3 (Generative Pre-trained Transformer 3) and InstructGPT are both language models based on the Transformer architecture, but they have some key differences in their architecture and training methods. Let’s quickly understand the difference between GPT-3 and InstructGPT.
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InstructGPT vs GPT-3
Architecture: GPT-3 is based on a standard Transformer architecture with an encoder and decoder, while InstructGPT uses a modified Transformer architecture with an additional instruction encoder. The instruction encoder takes natural language instructions as input and generates an instruction embedding attached to the input text before the model processes it.
Training data: GPT-3 is trained on a massive corpus of text data, while InstructGPT is trained on a combination of text and structured data. InstructGPT is designed to understand and generate text in response to natural language instructions that contain structured data, such as tables or graphs.
Training method: GPT-3 is trained using a standard unsupervised learning method, where the model is trained to predict the next word in a sequence of text.
InstructGPT is trained using a combination of supervised and unsupervised learning methods. The model is first pre-trained on a large corpus of text data using unsupervised learning and then fine-tuned on a smaller set of labeled data containing natural language instructions and structured data.
Application: GPT-3 is a general-purpose language model that can be used for various natural language tasks, such as language translation, summarization, and question-answering.
InstructGPT is designed specifically for tasks that require understanding and generating text in response to natural language instructions that contain structured data.
Results Comparison Of Real Toxicity, Truthfulness, Hallucinations, and Appropriateness Of InstructGPT And GPT-3
Examples Of GPT-3 vs InstructGPT
Benefits of InstructGPT Over GPT3 Models
- Compared to GPT-3 models, InstructGPT has a lower likelihood of generating false information or harmful content.
- In addition, InstructGPT is better at understanding the intent of questions.
- The incorporation of human feedback in the training loop allows InstructGPT to achieve higher accuracy and performance, despite only utilizing 1.3 billion parameters.
- While InstructGPT may still make occasional errors, research indicates that fine-tuning with human feedback holds great promise for aligning language models with human intent.
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