Welcome to the FAQ page for Infermatic.ai! Here, you can find answers to your questions about large language models and the AI industry. Whether you’re curious about how to use our tools or want to learn more about AI, this page is a great place to start.
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Related Questions
- What is the concept of subwords and how do they help large language models handle out-of-vocabulary words?
- How do word embeddings, such as Word2Vec or GloVe, enable large language models to represent words in a continuous vector space?
- Can you explain how the use of subwords or word embeddings allows large language models to generalize to words they have not seen before?
- How do subwords or word embeddings help large language models to capture nuances of word meanings and relationships?
- What are the benefits of using subwords or word embeddings in large language models, and how do they improve performance?
- Can you provide examples of how subwords or word embeddings are used in large language models to handle out-of-vocabulary words?
- How do the choice of subword vocabulary or word embedding model impact the performance of large language models on out-of-vocabulary words?
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