End-of-chapter quiz - Hugging Face NLP Course

3\. Fine-tuning a pretrained model

4\. Sharing models and tokenizers

5\. The 🤗 Datasets library

6\. The 🤗 Tokenizers library

9\. Building and sharing demos new

[Pytorch](?fw=pt) [TensorFlow](?fw=tf)

## [](#end-of-chapter-quiz)End-of-chapter quiz

[![Ask a Question](https://img.shields.io/badge/Ask%20a%20question-ffcb4c.svg?logo=data:image/svg+xml;base64,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)](https://discuss.huggingface.co/t/chapter-7-questions)

Let’s test what you learned in this chapter!

### [](#1.-which-of-the-following-tasks-can-be-framed-as-a-token-classification-problem?)1\. Which of the following tasks can be framed as a token classification problem?

### [](#2.-what-part-of-the-preprocessing-for-token-classification-differs-from-the-other-preprocessing-pipelines?)2\. What part of the preprocessing for token classification differs from the other preprocessing pipelines?

### [](#3.-what-problem-arises-when-we-tokenize-the-words-in-a-token-classification-problem-and-want-to-label-the-tokens?)3\. What problem arises when we tokenize the words in a token classification problem and want to label the tokens?

### [](#4.-what-does-“domain-adaptation”-mean?)4\. What does “domain adaptation” mean?

### [](#5.-what-are-the-labels-in-a-masked-language-modeling-problem?)5\. What are the labels in a masked language modeling problem?

### [](#6.-which-of-these-tasks-can-be-seen-as-a-sequence-to-sequence-problem?)6\. Which of these tasks can be seen as a sequence-to-sequence problem?

### [](#7.-what-is-the-proper-way-to-preprocess-the-data-for-a-sequence-to-sequence-problem?)7\. What is the proper way to preprocess the data for a sequence-to-sequence problem?

### [](#8.-why-is-there-a-specific-subclass-of-<code>trainer</code>-for-sequence-to-sequence-problems?)8\. Why is there a specific subclass of `Trainer` for sequence-to-sequence problems?

### [](#10.-when-should-you-pretrain-a-new-model?)10\. When should you pretrain a new model?

### [](#11.-why-is-it-easy-to-pretrain-a-language-model-on-lots-and-lots-of-texts?)11\. Why is it easy to pretrain a language model on lots and lots of texts?

### [](#12.-what-are-the-main-challenges-when-preprocessing-data-for-a-question-answering-task?)12\. What are the main challenges when preprocessing data for a question answering task?

### [](#13.-how-is-post-processing-usually-done-in-question-answering?)13\. How is post-processing usually done in question answering?