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<h1 class="relative group"><a id="endofchapter-quiz" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#endofchapter-quiz"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
	<span>End-of-chapter quiz
	</span></h1>



<div class="flex space-x-1 absolute z-10 right-0 top-0"><a href="https://discuss.huggingface.co/t/chapter-6-questions" target="_blank"><img alt="Ask a Question" class="!m-0" src="https://img.shields.io/badge/Ask%20a%20question-ffcb4c.svg?logo=data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgLTEgMTA0IDEwNiI+PGRlZnM+PHN0eWxlPi5jbHMtMXtmaWxsOiMyMzFmMjA7fS5jbHMtMntmaWxsOiNmZmY5YWU7fS5jbHMtM3tmaWxsOiMwMGFlZWY7fS5jbHMtNHtmaWxsOiMwMGE5NGY7fS5jbHMtNXtmaWxsOiNmMTVkMjI7fS5jbHMtNntmaWxsOiNlMzFiMjM7fTwvc3R5bGU+PC9kZWZzPjx0aXRsZT5EaXNjb3Vyc2VfbG9nbzwvdGl0bGU+PGcgaWQ9IkxheWVyXzIiPjxnIGlkPSJMYXllcl8zIj48cGF0aCBjbGFzcz0iY2xzLTEiIGQ9Ik01MS44NywwQzIzLjcxLDAsMCwyMi44MywwLDUxYzAsLjkxLDAsNTIuODEsMCw1Mi44MWw1MS44Ni0uMDVjMjguMTYsMCw1MS0yMy43MSw1MS01MS44N1M4MCwwLDUxLjg3LDBaIi8+PHBhdGggY2xhc3M9ImNscy0yIiBkPSJNNTIuMzcsMTkuNzRBMzEuNjIsMzEuNjIsMCwwLDAsMjQuNTgsNjYuNDFsLTUuNzIsMTguNEwzOS40LDgwLjE3YTMxLjYxLDMxLjYxLDAsMSwwLDEzLTYwLjQzWiIvPjxwYXRoIGNsYXNzPSJjbHMtMyIgZD0iTTc3LjQ1LDMyLjEyYTMxLjYsMzEuNiwwLDAsMS0zOC4wNSw0OEwxOC44Niw4NC44MmwyMC45MS0yLjQ3QTMxLjYsMzEuNiwwLDAsMCw3Ny40NSwzMi4xMloiLz48cGF0aCBjbGFzcz0iY2xzLTQiIGQ9Ik03MS42MywyNi4yOUEzMS42LDMxLjYsMCwwLDEsMzguOCw3OEwxOC44Niw4NC44MiwzOS40LDgwLjE3QTMxLjYsMzEuNiwwLDAsMCw3MS42MywyNi4yOVoiLz48cGF0aCBjbGFzcz0iY2xzLTUiIGQ9Ik0yNi40Nyw2Ny4xMWEzMS42MSwzMS42MSwwLDAsMSw1MS0zNUEzMS42MSwzMS42MSwwLDAsMCwyNC41OCw2Ni40MWwtNS43MiwxOC40WiIvPjxwYXRoIGNsYXNzPSJjbHMtNiIgZD0iTTI0LjU4LDY2LjQxQTMxLjYxLDMxLjYxLDAsMCwxLDcxLjYzLDI2LjI5YTMxLjYxLDMxLjYxLDAsMCwwLTQ5LDM5LjYzbC0zLjc2LDE4LjlaIi8+PC9nPjwvZz48L3N2Zz4="></a>
	
	</div>
<p>Let’s test what you learned in this chapter!</p>
<h3 class="relative group"><a id="1.-when-should-you-train-a-new-tokenizer?" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#1.-when-should-you-train-a-new-tokenizer?"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
	<span>1. When should you train a new tokenizer?
	</span></h3>

<div><form><label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="0">
				<!-- HTML_TAG_START -->When your dataset is similar to that used by an existing pretrained model, and you want to pretrain a new model<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="1">
				<!-- HTML_TAG_START -->When your dataset is similar to that used by an existing pretrained model, and you want to fine-tune a new model using this pretrained model<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="2">
				<!-- HTML_TAG_START -->When your dataset is different from the one used by an existing pretrained model, and you want to pretrain a new model<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="3">
				<!-- HTML_TAG_START -->When your dataset is different from the one used by an existing pretrained model, but you want to fine-tune a new model using this pretrained model<!-- HTML_TAG_END --></label>
			
		<div class="flex flex-row items-center mt-3"><button class="btn px-4 mr-4" type="submit" disabled>Submit </button>

			</div></form></div>
<h3 class="relative group"><a id="2.-what-is-the-advantage-of-using-a-generator-of-lists-of-texts-compared-to-a-list-of-lists-of-texts-when-using-<code>train_new_from_iterator()</code>?" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#2.-what-is-the-advantage-of-using-a-generator-of-lists-of-texts-compared-to-a-list-of-lists-of-texts-when-using-<code>train_new_from_iterator()</code>?"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
	<span>2. What is the advantage of using a generator of lists of texts compared to a list of lists of texts when using <code>train_new_from_iterator()</code>?
	</span></h3>

<div><form><label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="0">
				<!-- HTML_TAG_START -->That's the only type the method <code>train_new_from_iterator()</code> accepts.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="1">
				<!-- HTML_TAG_START -->You will avoid loading the whole dataset into memory at once.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="2">
				<!-- HTML_TAG_START -->This will allow the 🤗 Tokenizers library to use multiprocessing.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="3">
				<!-- HTML_TAG_START -->The tokenizer you train will generate better texts.<!-- HTML_TAG_END --></label>
			
		<div class="flex flex-row items-center mt-3"><button class="btn px-4 mr-4" type="submit" disabled>Submit </button>

			</div></form></div>
<h3 class="relative group"><a id="3.-what-are-the-advantages-of-using-a-“fast”-tokenizer?" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#3.-what-are-the-advantages-of-using-a-“fast”-tokenizer?"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
	<span>3. What are the advantages of using a “fast” tokenizer?
	</span></h3>

<div><form><label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="0">
				<!-- HTML_TAG_START -->It can process inputs faster than a slow tokenizer when you batch lots of inputs together.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="1">
				<!-- HTML_TAG_START -->Fast tokenizers always tokenize faster than their slow counterparts.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="2">
				<!-- HTML_TAG_START -->It can apply padding and truncation.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="3">
				<!-- HTML_TAG_START -->It has some additional features allowing you to map tokens to the span of text that created them.<!-- HTML_TAG_END --></label>
			
		<div class="flex flex-row items-center mt-3"><button class="btn px-4 mr-4" type="submit" disabled>Submit </button>

			</div></form></div>
<h3 class="relative group"><a id="4.-how-does-the-<code>token-classification</code>-pipeline-handle-entities-that-span-over-several-tokens?" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#4.-how-does-the-<code>token-classification</code>-pipeline-handle-entities-that-span-over-several-tokens?"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
	<span>4. How does the <code>token-classification</code> pipeline handle entities that span over several tokens?
	</span></h3>

<div><form><label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="0">
				<!-- HTML_TAG_START -->The entities with the same label are merged into one entity.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="1">
				<!-- HTML_TAG_START -->There is a label for the beginning of an entity and a label for the continuation of an entity.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="2">
				<!-- HTML_TAG_START -->In a given word, as long as the first token has the label of the entity, the whole word is considered labeled with that entity.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="3">
				<!-- HTML_TAG_START -->When a token has the label of a given entity, any other following token with the same label is considered part of the same entity, unless it's labeled as the start of a new entity.<!-- HTML_TAG_END --></label>
			
		<div class="flex flex-row items-center mt-3"><button class="btn px-4 mr-4" type="submit" disabled>Submit </button>

			</div></form></div>
<h3 class="relative group"><a id="5.-how-does-the-<code>question-answering</code>-pipeline-handle-long-contexts?" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#5.-how-does-the-<code>question-answering</code>-pipeline-handle-long-contexts?"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
	<span>5. How does the <code>question-answering</code> pipeline handle long contexts?
	</span></h3>

<div><form><label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="0">
				<!-- HTML_TAG_START -->It doesn't really, as it truncates the long context at the maximum length accepted by the model.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="1">
				<!-- HTML_TAG_START -->It splits the context into several parts and averages the results obtained.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="2">
				<!-- HTML_TAG_START -->It splits the context into several parts (with overlap) and finds the maximum score for an answer in each part.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="3">
				<!-- HTML_TAG_START -->It splits the context into several parts (without overlap, for efficiency) and finds the maximum score for an answer in each part.<!-- HTML_TAG_END --></label>
			
		<div class="flex flex-row items-center mt-3"><button class="btn px-4 mr-4" type="submit" disabled>Submit </button>

			</div></form></div>
<h3 class="relative group"><a id="6.-what-is-normalization?" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#6.-what-is-normalization?"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
	<span>6. What is normalization?
	</span></h3>

<div><form><label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="0">
				<!-- HTML_TAG_START -->It's any cleanup the tokenizer performs on the texts in the initial stages.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="1">
				<!-- HTML_TAG_START -->It's a data augmentation technique that involves making the text more normal by removing rare words.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="2">
				<!-- HTML_TAG_START -->It's the final post-processing step where the tokenizer adds the special tokens.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="3">
				<!-- HTML_TAG_START -->It's when the embeddings are made with mean 0 and standard deviation 1, by subtracting the mean and dividing by the std.<!-- HTML_TAG_END --></label>
			
		<div class="flex flex-row items-center mt-3"><button class="btn px-4 mr-4" type="submit" disabled>Submit </button>

			</div></form></div>
<h3 class="relative group"><a id="7.-what-is-pre-tokenization-for-a-subword-tokenizer?" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#7.-what-is-pre-tokenization-for-a-subword-tokenizer?"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
	<span>7. What is pre-tokenization for a subword tokenizer?
	</span></h3>

<div><form><label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="0">
				<!-- HTML_TAG_START -->It's the step before the tokenization, where data augmentation (like random masking) is applied.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="1">
				<!-- HTML_TAG_START -->It's the step before the tokenization, where the desired cleanup operations are applied to the text.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="2">
				<!-- HTML_TAG_START -->It's the step before the tokenizer model is applied, to split the input into words.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="3">
				<!-- HTML_TAG_START -->It's the step before the tokenizer model is applied, to split the input into tokens.<!-- HTML_TAG_END --></label>
			
		<div class="flex flex-row items-center mt-3"><button class="btn px-4 mr-4" type="submit" disabled>Submit </button>

			</div></form></div>
<h3 class="relative group"><a id="8.-select-the-sentences-that-apply-to-the-bpe-model-of-tokenization." class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#8.-select-the-sentences-that-apply-to-the-bpe-model-of-tokenization."><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
	<span>8. Select the sentences that apply to the BPE model of tokenization.
	</span></h3>

<div><form><label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="0">
				<!-- HTML_TAG_START -->BPE is a subword tokenization algorithm that starts with a small vocabulary and learns merge rules.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="1">
				<!-- HTML_TAG_START -->BPE is a subword tokenization algorithm that starts with a big vocabulary and progressively removes tokens from it.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="2">
				<!-- HTML_TAG_START -->BPE tokenizers learn merge rules by merging the pair of tokens that is the most frequent.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="3">
				<!-- HTML_TAG_START -->A BPE tokenizer learns a merge rule by merging the pair of tokens that maximizes a score that privileges frequent pairs with less frequent individual parts.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="4">
				<!-- HTML_TAG_START -->BPE tokenizes words into subwords by splitting them into characters and then applying the merge rules.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="5">
				<!-- HTML_TAG_START -->BPE tokenizes words into subwords by finding the longest subword starting from the beginning that is in the vocabulary, then repeating the process for the rest of the text.<!-- HTML_TAG_END --></label>
			
		<div class="flex flex-row items-center mt-3"><button class="btn px-4 mr-4" type="submit" disabled>Submit </button>

			</div></form></div>
<h3 class="relative group"><a id="9.-select-the-sentences-that-apply-to-the-wordpiece-model-of-tokenization." class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#9.-select-the-sentences-that-apply-to-the-wordpiece-model-of-tokenization."><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
	<span>9. Select the sentences that apply to the WordPiece model of tokenization.
	</span></h3>

<div><form><label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="0">
				<!-- HTML_TAG_START -->WordPiece is a subword tokenization algorithm that starts with a small vocabulary and learns merge rules.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="1">
				<!-- HTML_TAG_START -->WordPiece is a subword tokenization algorithm that starts with a big vocabulary and progressively removes tokens from it.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="2">
				<!-- HTML_TAG_START -->WordPiece tokenizers learn merge rules by merging the pair of tokens that is the most frequent.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="3">
				<!-- HTML_TAG_START -->A WordPiece tokenizer learns a merge rule by merging the pair of tokens that maximizes a score that privileges frequent pairs with less frequent individual parts.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="4">
				<!-- HTML_TAG_START -->WordPiece tokenizes words into subwords by finding the most likely segmentation into tokens, according to the model.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="5">
				<!-- HTML_TAG_START -->WordPiece tokenizes words into subwords by finding the longest subword starting from the beginning that is in the vocabulary, then repeating the process for the rest of the text.<!-- HTML_TAG_END --></label>
			
		<div class="flex flex-row items-center mt-3"><button class="btn px-4 mr-4" type="submit" disabled>Submit </button>

			</div></form></div>
<h3 class="relative group"><a id="10.-select-the-sentences-that-apply-to-the-unigram-model-of-tokenization." class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#10.-select-the-sentences-that-apply-to-the-unigram-model-of-tokenization."><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
	<span>10. Select the sentences that apply to the Unigram model of tokenization.
	</span></h3>

<div><form><label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="0">
				<!-- HTML_TAG_START -->Unigram is a subword tokenization algorithm that starts with a small vocabulary and learns merge rules.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="1">
				<!-- HTML_TAG_START -->Unigram is a subword tokenization algorithm that starts with a big vocabulary and progressively removes tokens from it.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="2">
				<!-- HTML_TAG_START -->Unigram adapts its vocabulary by minimizing a loss computed over the whole corpus.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="3">
				<!-- HTML_TAG_START -->Unigram adapts its vocabulary by keeping the most frequent subwords.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="4">
				<!-- HTML_TAG_START -->Unigram tokenizes words into subwords by finding the most likely segmentation into tokens, according to the model.<!-- HTML_TAG_END --></label>
			<label class="block"><input autocomplete="off" class="form-input -mt-1.5 mr-2" name="choice" type="checkbox" value="5">
				<!-- HTML_TAG_START -->Unigram tokenizes words into subwords by splitting them into characters, then applying the merge rules.<!-- HTML_TAG_END --></label>
			
		<div class="flex flex-row items-center mt-3"><button class="btn px-4 mr-4" type="submit" disabled>Submit </button>

			</div></form></div>


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