92. BERT: The Model That Reads in Both Directions
BERT is a transformer model that reads text in both directions, allowing it to understand context better than models like GPT. It uses a unique training method involving masked language modeling and next sentence prediction to enhance its understanding of language. BERT has become the preferred choice for various natural language processing tasks due to its bidirectional context awareness.
- ▪BERT reads all tokens simultaneously, while GPT reads left to right.
- ▪BERT was pretrained on a massive corpus using two tasks: masked language modeling and next sentence prediction.
- ▪BERT is particularly effective for classification tasks, whereas GPT excels in text generation.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 1358056) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Akhilesh Posted on May 20 92. BERT: The Model That Reads in Both Directions #ai #productivity #programming #beginners GPT generates text by predicting the next word. It reads left to right. BERT does something different. It masks random words in a sentence and tries to predict what they are. To do that well, it has to understand every word in relation to every other word simultaneously. Left and right context both matter.
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