? Description:
BERT (Bidirectional Encoder Representations from Transformers) is a powerful transformer-based machine learning model developed by Google AI for natural language understanding. Unlike previous models, BERT is deeply bidirectional, meaning it reads text both left-to-right and right-to-left to understand the full context of a word in a sentence.
This repository contains TensorFlow code and pre-trained checkpoints for the BERT model, as described in the paper:
? BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
(arXiv:1810.04805)
Key Features
? Bidirectional Contextual Understanding
Reads entire sequences in both directions for more accurate understanding.
? Pre-trained Models
Several BERT models are available (e.g., BERT-Base, BERT-Large) trained on BooksCorpus + English Wikipedia.
? Masked Language Modeling (MLM)
Trains by predicting randomly masked words within a sentence.
? Next Sentence Prediction (NSP)
Trains the model to understand relationships between sentence pairs.
? Fine-Tuning Ready
Easily fine-tuned on downstream tasks like:
Question Answering (SQuAD)
Sentiment Analysis
Named Entity Recognition (NER)
Natural Language Inference (NLI)
?️ TensorFlow Implementation
Includes training code, inference scripts, and model export utilities.
Android DevHub
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