Few Shot Prompting

Few-shot prompting is a powerful tool in the world of large language models (LLMs). It's like showing your AI a few "training wheels" to guide it towards the desired output, especially for complex tasks where zero-shot prompting (asking straight up) might not be enough. Imagine explaining a new recipe to a friend; showing them a few key steps and pictures would make it much easier for them to follow than just giving them the ingredients list, right?

Here's how few-shot prompting works:

Lets understand with an Example for Few-Shot Prompting:

Suppose we have a language model that we want to fine-tune for sentiment analysis on movie reviews. We only have a few labeled examples of positive and negative movie reviews to train the model.

Positive movie review examples:

Negative movie review examples:

Using the few-shot prompting technique, we can provide these labeled examples as prompts to the language model during fine-tuning. The model learns to associate certain language patterns with positive or negative sentiment based on these examples.

After fine-tuning, we can then provide new, unlabelled movie reviews to the model, and it will predict the sentiment of each review based on its learned knowledge from the few-shot examples.

For example, if we provide the following movie review:

"I was pleasantly surprised by how much I enjoyed this movie. The characters were relatable and the plot kept me engaged throughout."

The model, having been fine-tuned using few-shot prompting, might correctly predict this review as positive based on its learned associations between language patterns and sentiment.

Few-shot prompting is particularly useful when we have limited labeled data for a specific task but still want to leverage the power of pre-trained language models to perform that task effectively.

Benefits of Few-Shot Prompting:

Challenges of Few-Shot Prompting:

Overall, few-shot prompting is a valuable technique for harnessing the power of LLMs with greater control and accuracy. By providing a few guiding examples, you can unlock your AI's potential and achieve impressive results.