How are documents usually evaluated in the simplest form of keyword-based search?

** Based on the presence and frequency of the user-provided keywords

When is fine-tuning an appropriate method for customizing a Large Language Model (LLM)?

When the LLM does not perform well on a task and the data for prompt engineering is too large

n which scenario is soft prompting appropriate compared to other training styles?

** When there is a need to add learnable parameters to a Large Language Model (LLM) without task-specific training

How does the temperature setting in a decoding algorithm influence the probability distribution over the vocabulary?

** Increasing the temperature flattens the distribution, allowing for more varied word choices.

Which statement is true about Fine-tuning and Parameter-Efficient Fine-Tuning (PEFT)?

** Fine-tuning requires training the entire model on new data, often leading to substantial computational costs, whereas PEFT involves updating only a small subset of parameters, minimizing computational requirements and data needs.

What does accuracy measure in the context of fine-tuning results for a generative model?

** How many predictions the model made correctly out of all the predictions in an evaluation

In the context of generating text with a Large Language Model (LLM), what does the process of greedy decoding entail?

* Choosing the word with the highest probability at each step of decoding

In the simplified workflow for managing and querying vector data, what is the role of indexing?

** To map vectors to a data structure for faster searching, enabling efficient retrieval

When does a chain typically interact with memory in a run within the LangChain framework?

** After user input but before chain execution, and again after core logic but before output

What does a cosine distance of 0 indicate about the relationship between two embeddings?

** They are similar in direction

Which is a characteristic of T-Few fine-tuning for Large Language Models (LLMs)? It does not update any weights but restructures the model architecture.

** It selectively updates only a fraction of the model's weights.

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Oracle

Certification Review

Term	Definition
How are documents usually evaluated in the simplest form of keyword-based search?	** Based on the presence and frequency of the user-provided keywords
When is fine-tuning an appropriate method for customizing a Large Language Model (LLM)?	When the LLM does not perform well on a task and the data for prompt engineering is too large
n which scenario is soft prompting appropriate compared to other training styles?	** When there is a need to add learnable parameters to a Large Language Model (LLM) without task-specific training
How does the temperature setting in a decoding algorithm influence the probability distribution over the vocabulary?	** Increasing the temperature flattens the distribution, allowing for more varied word choices.
Which statement is true about Fine-tuning and Parameter-Efficient Fine-Tuning (PEFT)?	** Fine-tuning requires training the entire model on new data, often leading to substantial computational costs, whereas PEFT involves updating only a small subset of parameters, minimizing computational requirements and data needs.
What does accuracy measure in the context of fine-tuning results for a generative model?	** How many predictions the model made correctly out of all the predictions in an evaluation
In the context of generating text with a Large Language Model (LLM), what does the process of greedy decoding entail?	* Choosing the word with the highest probability at each step of decoding
In the simplified workflow for managing and querying vector data, what is the role of indexing?	** To map vectors to a data structure for faster searching, enabling efficient retrieval
When does a chain typically interact with memory in a run within the LangChain framework?	** After user input but before chain execution, and again after core logic but before output
What do prompt templates use for templating in language model applications?	** Python's str.format syntax
What does a cosine distance of 0 indicate about the relationship between two embeddings?	** They are similar in direction
Which is a characteristic of T-Few fine-tuning for Large Language Models (LLMs)? It does not update any weights but restructures the model architecture.	** It selectively updates only a fraction of the model's weights.

Created by: Zeritzuuu

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