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Questions and Answers
What is the primary function of the decoder in a transformer model?
What is the primary function of the decoder in a transformer model?
- To predict a future token given the past tokens
- To output a matrix representation of the input
- To iteratively generate an output from the input representation (correct)
- To learn representations of the entire sequence
What type of language model is used for predicting the next word in a sentence?
What type of language model is used for predicting the next word in a sentence?
- Auto-encoding model
- Transformer model
- Encoder-decoder model
- Auto-regressive model (correct)
What is the primary goal of an auto-encoding model?
What is the primary goal of an auto-encoding model?
- To generate text based on a prompt
- To comprehend the meaning of a sentence
- To learn representations of the entire sequence (correct)
- To predict a future token given the past tokens
What is the name of the family of models used for Natural Language Generation (NLG)?
What is the name of the family of models used for Natural Language Generation (NLG)?
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What is the primary goal of an auto-regressive model?
What is the primary goal of an auto-regressive model?
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Study Notes
Transformer Architecture
- A transformer consists of an encoder and a decoder
- The encoder takes in input and outputs a matrix representation of that input
- The decoder takes in that representation and iteratively generates an output
Language Modeling
- A language model is trained to predict a missing word in a sequence of words
- There are two types of language models: auto-regressive and auto-encoding
Auto-Regressive Models
- Goal: predict a future token (word) given either the past tokens or the future tokens but not both
- Applications:
- Predicting next word in a sentence (auto-complete)
- Natural Language Generation (NLG)
- GPT Family
Auto-Encoding Models
- Goal: learn representations of the entire sequence by predicting tokens given both the past and future tokens
- Applications:
- Comprehensive understanding and encoding of entire sequences of tokens
- Natural Language Understanding (NLU)
- BERT
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