A. To generate text based only on the model's internal knowledge without external data

B. To generate text using extra information obtained from an external data source

C. To store text in an external database without using it for generation

D. To retrieve text from an external source and present it without any modifications

A. LCEL is a programming language used to write documentation for LangChain.

B. LCEL is a legacy method for creating chains in LangChain.

C. LCEL is a declarative and preferred way to compose chains together.

D. LCEL is an older Python library for building Large Language Models.

A. Encoder models and decoder models both convert sequences of words into vector representations without generating new text.

B. Encoder models take a sequence of words and predict the next word in the sequence, whereas decoder models convert a sequence of words into a numerical representation.

C. Encoder models convert a sequence of words into a vector representation, and decoder models take this vector representation to generate a sequence of words.

D. Encoder models are used only for numerical calculations, whereas decoder models are used to interpret the calculated numerical values back into text.

A. Because text generation does not require complex models

B. Because text is not categorical

C. Because text representation is categorical unlike images

D. Because diffusion models can only produce images

A. In-context Learning

B. Step-Back Prompting

C. Least-to-Most Prompting

D. Chain-of-Thought

A. Measuring coherence of generated text

B. Aligning code readability

C. Evaluating factual accuracy of outputs

D. Detecting bias or toxicity