Title: 3 Bert Bidirectional Encoder Representations From Transformers
Course: LLM_Prompt_Engineering_For_Developers > Section: Module 27: 3 Bert Bidirectional Encoder Representations From Transformers

3. BERT (Bidirectional Encoder Representations from Transformers)

Overview

BERT, developed by Google, is another groundbreaking model released in 2018 that focuses on understanding the context of words in a sentence. Unlike GPT models that are autoregressive (predict the next word), BERT is bidirectional, considering the full context of the sentence before making predictions.

Features

- Contextual Awareness: Better at understanding the context of words based on surrounding words, making it effective for tasks that require nuanced comprehension.
- Fine-tuning: Can be fine-tuned on specific datasets for particular tasks, such as sentiment analysis, and named entity recognition.

Example

Prompt: "What is the capital of France?"

Output:

The capital of France is Paris.

Prompt: "Why is Paris considered a cultural hub?"

Output:

Paris is considered a cultural hub due to its rich history, diverse art scene, and influence on fashion and cuisine. The city is home to world-renowned museums like the Louvre, historic sites such as the Notre-Dame Cathedral, and has been a gathering place for artistic movements throughout history.

Conclusion