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Tokenization
One major application of Large Language Models is in
translation, which facilitates communication across languages.
Large Language Models are capable of performing
analysis to determine the emotional tone of text.
Large Language Models can be used for various tasks, including
, summarization, and question answering.
Another application is
development, where these models can interact with users in a conversational manner.
What is one concern related to Large Language Models?
Large Language Models can generate human-like
after being trained on a diverse dataset.
Overfitting
Natural language processing
Fine-tuning
How do Large Language Models usually learn?
In the field of
, large language models can provide personalized tutoring and support to learners.
Transformer
The primary training method for Large Language Models is called
learning.
Large Language Models are primarily based on the
architecture.
What does 'GPT' stand for in the context of Large Language Models?
Large Language Models can be used for
generation, allowing for the creation of human-like content.
Semantic analysis
Inference
One challenge faced by Large Language Models is the
present in the training data.
