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<h1 class="relative group"><a id="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="#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>การสร้าง tokenizer ทีละขั้นตอน
	</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,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"></a>
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<p>จากบทก่อนๆ คุณจะเห็นว่า การตัดคำ ประกอบไปด้วยหลายขั้นตอน :</p>
<ul><li>Normalization (หรือ การปรับข้อความให้เป็นมาตรฐาน หมายถึงการทำความสะอาดข้อความ เช่น ลบช่องว่างหรือเครื่องหมายเน้นเสียง รวมถึงการทำ Unicode normalization และอื่นๆ)</li>
<li>Pre-tokenization (ขั้นตอนก่อนตัดคำ หมายถึง การแยกข้อความออกเป็นคำๆ)</li>
<li>ส่ง input เข้าไปในโมเดล (แยกคำที่ได้จากขั้นตอน pre-tokenization ออกเป็นคำย่อยหลายๆคำ)</li>
<li>Post-processing (ขั้นตอนปรับแต่งผลลัพธ์ เช่น การใส่ token พิเศษของ tokenizer เข้าไปในผลลัพธ์, การสร้าง attention mask และ token type IDs)</li></ul>
<p>เพื่อเป็นการเตือนความจำ มาดูกระบวนการโดยรวมอีกครั้ง :</p>
<div class="flex justify-center"><img class="block dark:hidden" src="https://huggingface.co/datasets/huggingface-course/documentation-images/resolve/main/en/chapter6/tokenization_pipeline.svg" alt="The tokenization pipeline.">
<img class="hidden dark:block" src="https://huggingface.co/datasets/huggingface-course/documentation-images/resolve/main/en/chapter6/tokenization_pipeline-dark.svg" alt="The tokenization pipeline."></div>
<p>🤗 Tokenizers library เป็นเครื่องมือสำหรับช่วยดำเนินการขั้นตอนพวกนี้ โดยคุณสามารถผสมผสานเครื่องมือพวกนี้ตามความต้องการได้
ในบทนี้เราจะมาเรียนวิธีสร้าง tokenizer ขึ้นมาตั้งแต่ต้น แทนที่จะเทรนจากตัวที่ถูก implement แล้วด้วยข้อมูลใหม่เท่านั้น อย่างที่เราได้ลองทำกันใน<a href="/course/chapter6/2">บทที่ 2</a> เมื่อจบบทนี้ คุณจะสามารถสร้าง tokenizer แบบใดก็ได้ตามที่คุณต้องการ</p>
<iframe class="w-full xl:w-4/6 h-80" src="https://www.youtube-nocookie.com/embed/MR8tZm5ViWU" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
<p>library นี้ ประกอบด้วยส่วนหลักคือ <code>Tokenizer</code> class ที่มีส่วนประกอบย่อยสำคัญอื่นๆ แบ่งเป็นหลาย submodules</p>
<ul><li><code>normalizers</code> ประกอบไปด้วย <code>Normalizer</code> หลายประเภทที่คุณสามารถใช้ได้ (รายชื่อทั้งหมดดูได้<a href="https://huggingface.co/docs/tokenizers/python/latest/api/reference.html#module-tokenizers.normalizers" rel="nofollow">ที่นี่</a>).</li>
<li><code>pre_tokenizers</code> ประกอบไปด้วย <code>PreTokenizer</code> หลายประเภทที่คุณสามารถใช้ได้ (รายชื่อทั้งหมดดูได้<a href="https://huggingface.co/docs/tokenizers/python/latest/api/reference.html#module-tokenizers.pre_tokenizers" rel="nofollow">ที่นี่</a>).</li>
<li><code>models</code> ประกอบไปด้วย <code>Model</code> หลายประเภทที่คุณสามารถใช้ได้ เช่น <code>BPE</code>, <code>WordPiece</code>, และ <code>Unigram</code> (รายชื่อทั้งหมดดูได้<a href="https://huggingface.co/docs/tokenizers/python/latest/api/reference.html#module-tokenizers.models" rel="nofollow">ที่นี่</a>).</li>
<li><code>trainers</code> ประกอบไปด้วย <code>Trainer</code> หลายประเภทที่คุณสามารถใช้เพื่อเทรนโมเดลด้วย corpus ที่มีได้ (แต่ละโมเดลจะมีเทรนเนอร์อย่างละตัว; รายชื่อทั้งหมดดูได้<a href="https://huggingface.co/docs/tokenizers/python/latest/api/reference.html#module-tokenizers.trainers" rel="nofollow">ที่นี่</a>).</li>
<li><code>post_processors</code> ประกอบไปด้วย <code>PostProcessor</code> หลายประเภทที่คุณสามารถใช้ได้ (รายชื่อทั้งหมดดูได้<a href="https://huggingface.co/docs/tokenizers/python/latest/api/reference.html#module-tokenizers.processors" rel="nofollow">ที่นี่</a>)</li>
<li><code>decoders</code> ประกอบไปด้วย <code>Decoder</code> หลายประเภทที่ใช้เพื่อ decode ผลลัพธ์จากการ tokenization (รายชื่อทั้งหมดดูได้<a href="https://huggingface.co/docs/tokenizers/python/latest/components.html#decoders" rel="nofollow">ที่นี่</a>)</li></ul>
<p>คุณสามารถดูรายชื่อของส่วนประกอบสำคัญๆต่างๆได้<a href="https://huggingface.co/docs/tokenizers/python/latest/components.html" rel="nofollow">ที่นี่</a></p>
<h2 class="relative group"><a id="corpus" 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="#corpus"><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>การโหลด corpus
	</span></h2>

<p>ในการเทรน tokenizer ตัวใหม่ เราจะใช้ corpus เล็กๆ เพื่อที่การคำนวณจะได้รวดเร็ว
การเรียกใช้งาน corpus จะทำคล้ายๆกับวิธีที่เราใช้ใน<a href="/course/chapter6/2">ตอนต้นของบทนี้</a> แต่ครั้งนี้เราจะใช้ชุดข้อมูลชื่อ <a href="https://huggingface.co/datasets/wikitext" rel="nofollow">WikiText-2</a></p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
	<div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div>
	Copied</div></button></div>
	<pre><!-- HTML_TAG_START --><span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> load_dataset

dataset = load_dataset(<span class="hljs-string">&quot;wikitext&quot;</span>, name=<span class="hljs-string">&quot;wikitext-2-raw-v1&quot;</span>, split=<span class="hljs-string">&quot;train&quot;</span>)


<span class="hljs-keyword">def</span> <span class="hljs-title function_">get_training_corpus</span>():
    <span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> <span class="hljs-built_in">range</span>(<span class="hljs-number">0</span>, <span class="hljs-built_in">len</span>(dataset), <span class="hljs-number">1000</span>):
        <span class="hljs-keyword">yield</span> dataset[i : i + <span class="hljs-number">1000</span>][<span class="hljs-string">&quot;text&quot;</span>]<!-- HTML_TAG_END --></pre></div>
<p><code>get_training_corpus()</code> เป็น generator ที่จะ yield ข้อมูลในรูปแบบ batch โดยแต่ละ batch ประกอบไปด้วย 1,000 ข้อความ
🤗 Tokenizers สามารถเทรนได้จากไฟล์ข้อความโดยตรง ดังนั้นเราจะสร้างไฟล์ข้อความ ที่ประกอบไปด้วย ข้อความทั้งหมดจาก WikiText-2</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
	<div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div>
	Copied</div></button></div>
	<pre><!-- HTML_TAG_START --><span class="hljs-keyword">with</span> <span class="hljs-built_in">open</span>(<span class="hljs-string">&quot;wikitext-2.txt&quot;</span>, <span class="hljs-string">&quot;w&quot;</span>, encoding=<span class="hljs-string">&quot;utf-8&quot;</span>) <span class="hljs-keyword">as</span> f:
    <span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> <span class="hljs-built_in">range</span>(<span class="hljs-built_in">len</span>(dataset)):
        f.write(dataset[i][<span class="hljs-string">&quot;text&quot;</span>] + <span class="hljs-string">&quot;\n&quot;</span>)<!-- HTML_TAG_END --></pre></div>
<p>ต่อไปเราจะพาคุณสร้าง tokenizer แบบ BERT, GPT-2, and XLNet ของคุณเอง ทีละขั้นตอน
ซึ่งคุณก็จะได้ลองใช้งาน tokenization algorithm ต่างๆที่ได้เรียนมาแล้ว เช่น WordPiece, BPE, and Unigram มาเริ่มจาก BERT กัน</p>
<h2 class="relative group"><a id="wordpiece-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="#wordpiece-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>สร้าง WordPiece tokenizer ตั้งแต่เริ่มต้น
	</span></h2>

<p>ในการสร้าง tokenizer โดยใช้ 🤗 Tokenizers library เราจะเริ่มจากการสร้าง <code>Tokenizer</code> object จาก <code>model</code> และตั้งค่า attribute ต่างๆ ได้แก่ <code>normalizer</code>, <code>pre_tokenizer</code>, <code>post_processor</code>, และ <code>decoder</code> ด้วยค่าที่เราต้องการ</p>
<p>ในตัวอย่างนี้ เราจะสร้าง <code>Tokenizer</code> ด้วย WordPiece :</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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	<pre><!-- HTML_TAG_START --><span class="hljs-keyword">from</span> tokenizers <span class="hljs-keyword">import</span> (
    decoders,
    models,
    normalizers,
    pre_tokenizers,
    processors,
    trainers,
    Tokenizer,
)

tokenizer = Tokenizer(models.WordPiece(unk_token=<span class="hljs-string">&quot;[UNK]&quot;</span>))<!-- HTML_TAG_END --></pre></div>
<p>จากนั้นเราจะตั้งค่า <code>unk_token</code> เพื่อบอกโมเดลว่าให้มัน return ค่าอะไรหากมันเจอตัวอักษรที่มันไม่รู้จัก
ส่วน argument อื่นๆที่เราสามารถตั้งค่าได้ก็คือ <code>vocab</code> (แต่เนื่องจากเราจะเทรนโมเดล ทำให้ตอนนี้เรายังไม่ต้องตั้งค่านี้) และ <code>max_input_chars_per_word</code> ซึ่งหมายถึง ความยาวสูงสุดของแต่ละคำ (คำที่ยาวกว่าค่านี้จะถูกแบ่งเป็นหลายๆส่วน)</p>
<p>ขั้นตอนแรกคือ normalization เนื่องจาก BERT เป็นโมเดลที่ได้รับความนิยมมาก เราจึงมี <code>BertNormalizer</code> เฉพาะ ซึ่งมี option ต่างๆดังนี้: <code>lowercase</code>, <code>strip_accents</code>, <code>clean_text</code> (ลบ control characters และแทนที่ช่องว่างที่อยู่ต่อกันหลายๆอันด้วยช่องว่างเดียว), และ <code>handle_chinese_chars</code> (เพิ่มช่องว่างในตัวอักษรจีน)</p>
<p>เราจะมาเลียนแบบ <code>bert-base-uncased</code> tokenizer โดยตั้งค่า normalizer ดังนี้ :</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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	<pre><!-- HTML_TAG_START -->tokenizer.normalizer = normalizers.BertNormalizer(lowercase=<span class="hljs-literal">True</span>)<!-- HTML_TAG_END --></pre></div>
<p>แต่ปกติแล้ว สำหรับ tokenizer ใหม่ คุณอาจจะไม่สามารถใช้ normalizer ที่จาก 🤗 Tokenizers library ได้ ดังนั้นเราจะมาเรียนวิธีการสร้าง BERT normalizer เองกัน</p>
<p>library นี้ มี normalizer เพื่อ <code>Lowercase</code> และเพื่อ <code>StripAccents</code> ซึ่งคุณสามารถรวมทั้งสองตัวได้โดยใช้ <code>Sequence</code> :</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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	<pre><!-- HTML_TAG_START -->tokenizer.normalizer = normalizers.<span class="hljs-type">Sequence</span>(
    [normalizers.NFD(), normalizers.Lowercase(), normalizers.StripAccents()]
)<!-- HTML_TAG_END --></pre></div>
<p>เราจะใช้ <code>NFD</code> Unicode normalizer ด้วย เพื่อที่จะให้ <code>StripAccents</code> สามารถหาสัญลักษณ์ accents ได้ และจะได้ลบพวกมันออก</p>
<p>เพื่อเช็คผลลัพธ์ของ normalizer เราจะใช้ <code>normalize_str()</code> method จาก <code>normalizer</code> :</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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	<pre><!-- HTML_TAG_START --><span class="hljs-built_in">print</span>(tokenizer.normalizer.normalize_str(<span class="hljs-string">&quot;Héllò hôw are ü?&quot;</span>))<!-- HTML_TAG_END --></pre></div>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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	<pre><!-- HTML_TAG_START -->hello how are u?<!-- HTML_TAG_END --></pre></div>


<div class="course-tip  bg-gradient-to-br dark:bg-gradient-to-r before:border-green-500 dark:before:border-green-800 from-green-50 dark:from-gray-900 to-white dark:to-gray-950 border border-green-50 text-green-700 dark:text-gray-400"><p><strong>รายละเอียดเพิ่มเติม</strong> ถ้าคุณทดลองใช้งาน normalizer ทั้งสองเวอร์ชันกับข้อความที่มีตัวอักษร unicode <code>u&quot;\u0085&quot;</code> คุณจะได้ผลลัพธ์ที่แตกต่างกัน
อย่างไรก็ตาม เราไม่อยากทำให้เวอร์ชันที่สร้างจาก <code>normalizers.Sequence</code> ของเรานั้นซับซ้อนเกินไป เราจึงไม่ใช้ Regex ที่ <code>BertNormalizer</code> ใช้เวลาที่ <code>clean_text</code> ถูกตั้งค่าเป็น <code>True</code> ซึ่งเป็นค่าตั้งต้น
แต่คุณไม่ต้องกังวลไป เพราะมันยังมีวิธีที่จะทำให้ผลลัพธ์ออกมาเป็นเหมือนกันโดยที่ไม่ต้องใช้ <code>BertNormalizer</code> นั่นคือโดยการเพิ่ม <code>normalizers.Replace</code> สองครั้ง เข้าไปใน <code>normalizers.Sequence</code></p></div>
<p>ขั้นตอนต่อไปคือ การ pre-tokenization เราจะใช้ <code>BertPreTokenizer</code> ที่ถูกสร้างมาแล้ว :</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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	<pre><!-- HTML_TAG_START -->tokenizer.pre_tokenizer = pre_tokenizers.BertPreTokenizer()<!-- HTML_TAG_END --></pre></div>
<p>หรือจะใช้ตัวที่เราสร้างขึ้นมาเองก็ได้ :</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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	<pre><!-- HTML_TAG_START -->tokenizer.pre_tokenizer = pre_tokenizers.Whitespace()<!-- HTML_TAG_END --></pre></div>
<p>โปรดทราบว่า <code>Whitespace</code> pre-tokenizer จะตัดข้อความตรงที่มีช่องว่าง และ รวมถึงตัวสัญลักษณ์ที่ไม่ใช้ตัวอักษร ตัวเลข หรือ underscore หรือพูดอีกแบบก็คือ มันจะแบ่งข้อความตรงที่มีช่องว่างและเครื่องหมายวรรคตอน นั่นเอง</p>

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	<pre><!-- HTML_TAG_START -->tokenizer.pre_tokenizer.pre_tokenize_str(<span class="hljs-string">&quot;Let&#x27;s test my pre-tokenizer.&quot;</span>)<!-- HTML_TAG_END --></pre></div>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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	<pre><!-- HTML_TAG_START -->[(<span class="hljs-string">&#x27;Let&#x27;</span>, (<span class="hljs-number">0</span>, <span class="hljs-number">3</span>)), (<span class="hljs-string">&quot;&#x27;&quot;</span>, (<span class="hljs-number">3</span>, <span class="hljs-number">4</span>)), (<span class="hljs-string">&#x27;s&#x27;</span>, (<span class="hljs-number">4</span>, <span class="hljs-number">5</span>)), (<span class="hljs-string">&#x27;test&#x27;</span>, (<span class="hljs-number">6</span>, <span class="hljs-number">10</span>)), (<span class="hljs-string">&#x27;my&#x27;</span>, (<span class="hljs-number">11</span>, <span class="hljs-number">13</span>)), (<span class="hljs-string">&#x27;pre&#x27;</span>, (<span class="hljs-number">14</span>, <span class="hljs-number">17</span>)),
 (<span class="hljs-string">&#x27;-&#x27;</span>, (<span class="hljs-number">17</span>, <span class="hljs-number">18</span>)), (<span class="hljs-string">&#x27;tokenizer&#x27;</span>, (<span class="hljs-number">18</span>, <span class="hljs-number">27</span>)), (<span class="hljs-string">&#x27;.&#x27;</span>, (<span class="hljs-number">27</span>, <span class="hljs-number">28</span>))]<!-- HTML_TAG_END --></pre></div>
<p>แต่ถ้าคุณต้องการจะแบ่งข้อความตามช่องว่างเท่านั้น ให้ใช้ <code>WhitespaceSplit</code> pre-tokenizer :</p>

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	<pre><!-- HTML_TAG_START -->pre_tokenizer = pre_tokenizers.WhitespaceSplit()
pre_tokenizer.pre_tokenize_str(<span class="hljs-string">&quot;Let&#x27;s test my pre-tokenizer.&quot;</span>)<!-- HTML_TAG_END --></pre></div>

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	<pre><!-- HTML_TAG_START -->[(<span class="hljs-string">&quot;Let&#x27;s&quot;</span>, (<span class="hljs-number">0</span>, <span class="hljs-number">5</span>)), (<span class="hljs-string">&#x27;test&#x27;</span>, (<span class="hljs-number">6</span>, <span class="hljs-number">10</span>)), (<span class="hljs-string">&#x27;my&#x27;</span>, (<span class="hljs-number">11</span>, <span class="hljs-number">13</span>)), (<span class="hljs-string">&#x27;pre-tokenizer.&#x27;</span>, (<span class="hljs-number">14</span>, <span class="hljs-number">28</span>))]<!-- HTML_TAG_END --></pre></div>
<p>เหมือนกับใน normalizer เราสามารถใช้ <code>Sequence</code> เพื่อรวมหลายๆ pre-tokenizers เข้าด้วยกัน :</p>

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	<pre><!-- HTML_TAG_START -->pre_tokenizer = pre_tokenizers.<span class="hljs-type">Sequence</span>(
    [pre_tokenizers.WhitespaceSplit(), pre_tokenizers.Punctuation()]
)
pre_tokenizer.pre_tokenize_str(<span class="hljs-string">&quot;Let&#x27;s test my pre-tokenizer.&quot;</span>)<!-- HTML_TAG_END --></pre></div>

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	<pre><!-- HTML_TAG_START -->[(<span class="hljs-string">&#x27;Let&#x27;</span>, (<span class="hljs-number">0</span>, <span class="hljs-number">3</span>)), (<span class="hljs-string">&quot;&#x27;&quot;</span>, (<span class="hljs-number">3</span>, <span class="hljs-number">4</span>)), (<span class="hljs-string">&#x27;s&#x27;</span>, (<span class="hljs-number">4</span>, <span class="hljs-number">5</span>)), (<span class="hljs-string">&#x27;test&#x27;</span>, (<span class="hljs-number">6</span>, <span class="hljs-number">10</span>)), (<span class="hljs-string">&#x27;my&#x27;</span>, (<span class="hljs-number">11</span>, <span class="hljs-number">13</span>)), (<span class="hljs-string">&#x27;pre&#x27;</span>, (<span class="hljs-number">14</span>, <span class="hljs-number">17</span>)),
 (<span class="hljs-string">&#x27;-&#x27;</span>, (<span class="hljs-number">17</span>, <span class="hljs-number">18</span>)), (<span class="hljs-string">&#x27;tokenizer&#x27;</span>, (<span class="hljs-number">18</span>, <span class="hljs-number">27</span>)), (<span class="hljs-string">&#x27;.&#x27;</span>, (<span class="hljs-number">27</span>, <span class="hljs-number">28</span>))]<!-- HTML_TAG_END --></pre></div>
<p>ขั้นตอนต่อไปใน tokenization pipeline คือการใส่ input เข้าไปในโมเดล
เราได้สร้างโมเดลขึ้นมาแล้ว แต่เรายังคงต้องเทรนมัน ซึ่งเราจะใช้ <code>WordPieceTrainer</code></p>
<p>สิ่งสำคัญที่คุณต้องจำคือ เวลาสร้าง (instantiate) trainer ใน 🤗 Tokenizers คุณจะต้องเพิ่ม token พิเศษต่างๆ เข้าไปในเทรนเนอร์เอง ไม่เช่นนั้น มันจะไม่เพิ่ม token พวกนี้เข้าไปใน vocabulary เพราะว่า token พิเศษไม่ได้อยู่ใน training corpus :</p>

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	<pre><!-- HTML_TAG_START -->special_tokens = [<span class="hljs-string">&quot;[UNK]&quot;</span>, <span class="hljs-string">&quot;[PAD]&quot;</span>, <span class="hljs-string">&quot;[CLS]&quot;</span>, <span class="hljs-string">&quot;[SEP]&quot;</span>, <span class="hljs-string">&quot;[MASK]&quot;</span>]
trainer = trainers.WordPieceTrainer(vocab_size=<span class="hljs-number">25000</span>, special_tokens=special_tokens)<!-- HTML_TAG_END --></pre></div>
<p>นอกจากเราจะสามารถตั้งค่า <code>vocab_size</code> และ <code>special_tokens</code> แล้ว เรายังสามารถตั้งค่า <code>min_frequency</code> (ความถี่ขั้นต่ำของคำที่ต้องมี เพื่อที่จะได้ถูกเพิ่มลงไปใน vocabulary) หรือ <code>continuing_subword_prefix</code> (ถ้าหากเราต้องการใช้สัญลักษณ์อื่น ที่ไม่ใช่<code>##</code>) ได้อีกด้วย</p>
<p>เราจะเทรนโมเดลโดยรันคำสั่งต่อไปนี้ :</p>

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	<pre><!-- HTML_TAG_START -->tokenizer.train_from_iterator(get_training_corpus(), trainer=trainer)<!-- HTML_TAG_END --></pre></div>
<p>คุณสามารถใช้ไฟล์ข้อความเพื่อเทรนได้ด้วย (แต่ก่อนอื่น คุณจะต้องสร้างโมเดลขึ้นมาใหม่โดยใช้ <code>WordPiece</code> ที่ยังว่างเปล่าอยู่) :</p>

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	<pre><!-- HTML_TAG_START -->tokenizer.model = models.WordPiece(unk_token=<span class="hljs-string">&quot;[UNK]&quot;</span>)
tokenizer.train([<span class="hljs-string">&quot;wikitext-2.txt&quot;</span>], trainer=trainer)<!-- HTML_TAG_END --></pre></div>
<p>สำหรับทั้งสองกรณี คุณสามารถทดลองใช้ tokenizer กับข้อความได้ โดยเรียกใช้ <code>encode()</code> method :</p>

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	<pre><!-- HTML_TAG_START -->encoding = tokenizer.encode(<span class="hljs-string">&quot;Let&#x27;s test this tokenizer.&quot;</span>)
<span class="hljs-built_in">print</span>(encoding.tokens)<!-- HTML_TAG_END --></pre></div>

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	<pre><!-- HTML_TAG_START -->[<span class="hljs-string">&#x27;let&#x27;</span>, <span class="hljs-string">&quot;&#x27;&quot;</span>, <span class="hljs-string">&#x27;s&#x27;</span>, <span class="hljs-string">&#x27;test&#x27;</span>, <span class="hljs-string">&#x27;this&#x27;</span>, <span class="hljs-string">&#x27;tok&#x27;</span>, <span class="hljs-string">&#x27;##eni&#x27;</span>, <span class="hljs-string">&#x27;##zer&#x27;</span>, <span class="hljs-string">&#x27;.&#x27;</span>]<!-- HTML_TAG_END --></pre></div>
<p><code>encoding</code> ที่เราได้คือ <code>Encoding</code> ที่ประกอบไปด้วยข้อมูลจำเป็นต่างๆสำหรับ tokenizer ได้แก่ <code>ids</code>, <code>type_ids</code>, <code>tokens</code>, <code>offsets</code>, <code>attention_mask</code>, <code>special_tokens_mask</code>, และ <code>overflowing</code></p>
<p>ขั้นตอนสุดท้ายของ pipeline คือ post-processing
เราจะเพิ่ม <code>[CLS]</code> ไว้ที่ตอนต้นของผลลัพธ์จากการ tokenize และ <code>[SEP]</code> ไว้ที่ตอนท้าย หรือหลังสิ้นสุดประโยค ถ้า input ของเรามีสองประโยค</p>
<p>เราจะใช้ <code>TemplateProcessor</code> เพื่อช่วยเราทำ แต่ก่อนอื่นเราต้องหา ID ของ <code>[CLS]</code> และ <code>[SEP]</code> ก่อน :</p>

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	<pre><!-- HTML_TAG_START -->cls_token_id = tokenizer.token_to_id(<span class="hljs-string">&quot;[CLS]&quot;</span>)
sep_token_id = tokenizer.token_to_id(<span class="hljs-string">&quot;[SEP]&quot;</span>)
<span class="hljs-built_in">print</span>(cls_token_id, sep_token_id)<!-- HTML_TAG_END --></pre></div>

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	<pre><!-- HTML_TAG_START -->(<span class="hljs-number">2</span>, <span class="hljs-number">3</span>)<!-- HTML_TAG_END --></pre></div>
<p>เราจะมาสร้าง template ให้กับ <code>TemplateProcessor</code> โดยจะต้องกำหนดว่าเราต้องการให้มันประมวลผล input ที่เป็น ประโยคเดี่ยว และ input ที่มีสองประโยคอย่างไร
สำหรับทั้งสองกรณี เราจะต้องกำหนด token พิเศษ เพื่อแทนประโยคขึ้นมา สำหรับประโยคเดี่ยวหรือประโยคแรก เราจะใช้ <code>$A</code> ส่วนสำหรับประโยคที่สอง เราจะใช้ <code>$B</code>
สำหรับ token พิเศษพวกนี้และประโยค เราจะสร้าง token type ID ขึ้นมา โดยจะเขียน ID นี้หลังเครื่องหมาย colon</p>
<p>template ของ BERT มีรายละเอียดดังนี้ :</p>

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	<pre><!-- HTML_TAG_START -->tokenizer.post_processor = processors.TemplateProcessing(
    single=<span class="hljs-string">f&quot;[CLS]:0 $A:0 [SEP]:0&quot;</span>,
    pair=<span class="hljs-string">f&quot;[CLS]:0 $A:0 [SEP]:0 $B:1 [SEP]:1&quot;</span>,
    special_tokens=[(<span class="hljs-string">&quot;[CLS]&quot;</span>, cls_token_id), (<span class="hljs-string">&quot;[SEP]&quot;</span>, sep_token_id)],
)<!-- HTML_TAG_END --></pre></div>
<p>อย่าลืมว่า เราจะต้องให้ข้อมูลโมเดลเกี่ยวกับ ID ของ token พิเศษด้วย เพื่อที่โมเดลจะได้แปลงมันได้อย่างถูกต้อง</p>
<p>เราจะกลับมาดูตัวอย่างก่อนหน้ากัน :</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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	<pre><!-- HTML_TAG_START -->encoding = tokenizer.encode(<span class="hljs-string">&quot;Let&#x27;s test this tokenizer.&quot;</span>)
<span class="hljs-built_in">print</span>(encoding.tokens)<!-- HTML_TAG_END --></pre></div>

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	<pre><!-- HTML_TAG_START -->[<span class="hljs-string">&#x27;[CLS]&#x27;</span>, <span class="hljs-string">&#x27;let&#x27;</span>, <span class="hljs-string">&quot;&#x27;&quot;</span>, <span class="hljs-string">&#x27;s&#x27;</span>, <span class="hljs-string">&#x27;test&#x27;</span>, <span class="hljs-string">&#x27;this&#x27;</span>, <span class="hljs-string">&#x27;tok&#x27;</span>, <span class="hljs-string">&#x27;##eni&#x27;</span>, <span class="hljs-string">&#x27;##zer&#x27;</span>, <span class="hljs-string">&#x27;.&#x27;</span>, <span class="hljs-string">&#x27;[SEP]&#x27;</span>]<!-- HTML_TAG_END --></pre></div>
<p>ถ้าเราใส่ input ที่เป็นสองประโยค เราจะได้ :</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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	<pre><!-- HTML_TAG_START -->encoding = tokenizer.encode(<span class="hljs-string">&quot;Let&#x27;s test this tokenizer...&quot;</span>, <span class="hljs-string">&quot;on a pair of sentences.&quot;</span>)
<span class="hljs-built_in">print</span>(encoding.tokens)
<span class="hljs-built_in">print</span>(encoding.type_ids)<!-- HTML_TAG_END --></pre></div>

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	<pre><!-- HTML_TAG_START -->[<span class="hljs-string">&#x27;[CLS]&#x27;</span>, <span class="hljs-string">&#x27;let&#x27;</span>, <span class="hljs-string">&quot;&#x27;&quot;</span>, <span class="hljs-string">&#x27;s&#x27;</span>, <span class="hljs-string">&#x27;test&#x27;</span>, <span class="hljs-string">&#x27;this&#x27;</span>, <span class="hljs-string">&#x27;tok&#x27;</span>, <span class="hljs-string">&#x27;##eni&#x27;</span>, <span class="hljs-string">&#x27;##zer&#x27;</span>, <span class="hljs-string">&#x27;...&#x27;</span>, <span class="hljs-string">&#x27;[SEP]&#x27;</span>, <span class="hljs-string">&#x27;on&#x27;</span>, <span class="hljs-string">&#x27;a&#x27;</span>, <span class="hljs-string">&#x27;pair&#x27;</span>, <span class="hljs-string">&#x27;of&#x27;</span>, <span class="hljs-string">&#x27;sentences&#x27;</span>, <span class="hljs-string">&#x27;.&#x27;</span>, <span class="hljs-string">&#x27;[SEP]&#x27;</span>]
[<span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>]<!-- HTML_TAG_END --></pre></div>
<p>ขั้นตอนสุดท้าย เราจะเพิ่ม decoder เข้าไปใน pipeline :</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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	<pre><!-- HTML_TAG_START -->tokenizer.decoder = decoders.WordPiece(prefix=<span class="hljs-string">&quot;##&quot;</span>)<!-- HTML_TAG_END --></pre></div>
<p>มาดูผลลัพธ์ของ <code>encoding</code> กัน :</p>

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	<pre><!-- HTML_TAG_START -->tokenizer.decode(encoding.ids)<!-- HTML_TAG_END --></pre></div>

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	<pre><!-- HTML_TAG_START --><span class="hljs-string">&quot;let&#x27;s test this tokenizer... on a pair of sentences.&quot;</span><!-- HTML_TAG_END --></pre></div>
<p>เยี่ยมมาก! ตอนนี้เราสามารถบันทึก tokenizer นี้เป็นไฟล์ JSON ได้แล้ว ดังนี้ :</p>

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	<pre><!-- HTML_TAG_START -->tokenizer.save(<span class="hljs-string">&quot;tokenizer.json&quot;</span>)<!-- HTML_TAG_END --></pre></div>
<p>คุณสามารถโหลดไฟล์นี้ให้เป็น <code>Tokenizer</code> object ได้โดยใช้ <code>from_file()</code> method :</p>

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	<pre><!-- HTML_TAG_START -->new_tokenizer = Tokenizer.from_file(<span class="hljs-string">&quot;tokenizer.json&quot;</span>)<!-- HTML_TAG_END --></pre></div>
<p>การจะนำ tokenizer นี้มาใช้ใน 🤗 Transformers เราจะต้อง wrap มันให้เป็น <code>PreTrainedTokenizerFast</code> ก่อน
โดยเราใช้ class ปกติ (ถ้า tokenizer ของเรามีโครงสร้างสอดคล้องกันโมเดลหลักเราที่จะใช้งาน) หรือ class ที่ถูกสร้างขึ้นมาแล้ว เช่น <code>BertTokenizerFast</code>
ในกรณีที่คุณสร้าง tokenizer ขึ้นมาเองอย่างที่เราได้สอนไว้ข้างต้น คุณจะต้องใช้ตัวเลือกแรก</p>
<p>การจะ wrap tokenizer ของเราให้เป็น <code>PreTrainedTokenizerFast</code> เราจะต้องส่งผ่าน tokenizer ของเราเข้าไปเป็น <code>tokenizer_object</code> หรือ ส่งผ่านไฟล์ของ tokenizer เป็น <code>tokenizer_file</code>
สิ่งสำคัญอีกอย่างคือ คุณจะต้องส่งผ่านข้อมูลเกี่ยวกับ token พิเศษ ต่างๆให้โมเดลเอง เพราะว่า class นี้จะไม่สามารถ infer จาก <code>tokenizer</code> object ได้เอง ว่า token ตัวไหนเป็น mask token เช่น <code>[CLS]</code> :</p>

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	<pre><!-- HTML_TAG_START --><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> PreTrainedTokenizerFast

wrapped_tokenizer = PreTrainedTokenizerFast(
    tokenizer_object=tokenizer,
    <span class="hljs-comment"># tokenizer_file=&quot;tokenizer.json&quot;, # You can load from the tokenizer file, alternatively</span>
    unk_token=<span class="hljs-string">&quot;[UNK]&quot;</span>,
    pad_token=<span class="hljs-string">&quot;[PAD]&quot;</span>,
    cls_token=<span class="hljs-string">&quot;[CLS]&quot;</span>,
    sep_token=<span class="hljs-string">&quot;[SEP]&quot;</span>,
    mask_token=<span class="hljs-string">&quot;[MASK]&quot;</span>,
)<!-- HTML_TAG_END --></pre></div>
<p>ถ้าคุณใช้ class ที่เฉพาะเจาะจง เช่น <code>BertTokenizerFast</code> คุณเพียงแค่ต้องเพิ่มข้อมูลเกี่ยวกับ token พิเศษที่ต่างจากตัวที่โมเดลใช้อยู่แล้ว ในตัวอย่างของเรา เราไม่ได้ใช้ token พิเศษอื่น จึงไม่ต้องเพิ่มอะไร :</p>

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	<pre><!-- HTML_TAG_START --><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> BertTokenizerFast

wrapped_tokenizer = BertTokenizerFast(tokenizer_object=tokenizer)<!-- HTML_TAG_END --></pre></div>
<p>ตอนนี้เราก็สามารถใช้ tokenizer ที่เราได้สร้างขึ้นมาเอง เหมือนกับ tokenizer ตัวอื่นๆจาก 🤗 Transformers ได้แล้ว นอกจากนั้นคุณยังสามารถเซฟมันได้ โดยใช้ <code>save_pretrained()</code> หรืออัพโหลดมันไปที่ Hub โดยใช้ <code>push_to_hub()</code></p>
<p>หลังจากที่เราได้ดูกันแล้วว่าจะสร้าง WordPiece tokenizer อย่างไร เราจะมาดูกันว่า จะทำแบบเดียวกันกับ BPE tokenizer ได้อย่างไร เราจะอธิบายคร่าวๆเท่านั้น เพราะคุณได้เรียนรายละเอียดมาแล้ว และจะพูดถึงแค่ข้อแตกต่างเท่านั้น</p>
<h2 class="relative group"><a id="bpe-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="#bpe-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>การสร้าง BPE tokenizer ตั้งแต่เริ่มต้น
	</span></h2>

<p>เราจะมาสร้าง GPT-2 tokenizer กัน เช่นเดียวกับตัวอย่างของ BERT tokenizer เราจะเริ่มด้วยกัน initialize <code>Tokenizer</code> ด้วยโมเดล BPE :</p>

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	<pre><!-- HTML_TAG_START -->tokenizer = Tokenizer(models.BPE())<!-- HTML_TAG_END --></pre></div>
<p>เราสามารถสร้างโมเดลนี้ด้วย vocabulary ที่มีอยู่ได้ โดยส่งผ่าน <code>vocab</code> และ <code>merges</code> แต่เราจะเทรนตั้งแต่ต้น แปลว่าเราไม่จำเป็นต้องทำขั้นตอนนี้
เราไม่จำเป็นต้องกำหนด <code>unk_token</code> เพราะ GPT-2 ใช้ byte-level BPE</p>
<p>นอกจากนั้น GPT-2 ยังไม่ใช้ normalizer อีกด้วย เราจึงจะข้ามขั้นตอนนี้ไปทำ pre-tokenization เลย :</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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	<pre><!-- HTML_TAG_START -->tokenizer.pre_tokenizer = pre_tokenizers.ByteLevel(add_prefix_space=<span class="hljs-literal">False</span>)<!-- HTML_TAG_END --></pre></div>
<p><code>add_prefix_space=False</code> หมายถึงเราจะไม่เพิ่มช่องว่างตรงต้นประโยค (ค่า default จะมีการเพิ่มช่องว่างนี้)</p>
<p>มาดูผลลัพธ์ตัวอย่างของการ pre-tokenization กัน :</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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	<pre><!-- HTML_TAG_START -->tokenizer.pre_tokenizer.pre_tokenize_str(<span class="hljs-string">&quot;Let&#x27;s test pre-tokenization!&quot;</span>)<!-- HTML_TAG_END --></pre></div>

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	<pre><!-- HTML_TAG_START -->[(<span class="hljs-string">&#x27;Let&#x27;</span>, (<span class="hljs-number">0</span>, <span class="hljs-number">3</span>)), (<span class="hljs-string">&quot;&#x27;s&quot;</span>, (<span class="hljs-number">3</span>, <span class="hljs-number">5</span>)), (<span class="hljs-string">&#x27;Ġtest&#x27;</span>, (<span class="hljs-number">5</span>, <span class="hljs-number">10</span>)), (<span class="hljs-string">&#x27;Ġpre&#x27;</span>, (<span class="hljs-number">10</span>, <span class="hljs-number">14</span>)), (<span class="hljs-string">&#x27;-&#x27;</span>, (<span class="hljs-number">14</span>, <span class="hljs-number">15</span>)),
 (<span class="hljs-string">&#x27;tokenization&#x27;</span>, (<span class="hljs-number">15</span>, <span class="hljs-number">27</span>)), (<span class="hljs-string">&#x27;!&#x27;</span>, (<span class="hljs-number">27</span>, <span class="hljs-number">28</span>))]<!-- HTML_TAG_END --></pre></div>
<p>ขั้นตอนต่อไปคือการเทรนโมเดล  สำหรับ GPT-2 มันจะมี token พิเศษตัวเดียวคือ end-of-text token (อยู่ตรงท้ายของข้อความ) :</p>

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	<pre><!-- HTML_TAG_START -->trainer = trainers.BpeTrainer(vocab_size=<span class="hljs-number">25000</span>, special_tokens=[<span class="hljs-string">&quot;&lt;|endoftext|&gt;&quot;</span>])
tokenizer.train_from_iterator(get_training_corpus(), trainer=trainer)<!-- HTML_TAG_END --></pre></div>
<p>เช่นเดียวกันกับ <code>WordPieceTrainer</code> คุณสามารถกำหนด <code>vocab_size</code>, <code>special_tokens</code>, <code>min_frequency</code> ได้ ถ้าหากคุณใช้ end-of-word suffix (เช่น <code>&lt;/w&gt;</code>) คุณก็สามารถตั้งค่ามันได้ด้วย <code>end_of_word_suffix</code></p>
<p>คุณสามารถเทรนด้วยไฟล์ข้อความได้ด้วย :</p>

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	<pre><!-- HTML_TAG_START -->tokenizer.model = models.BPE()
tokenizer.train([<span class="hljs-string">&quot;wikitext-2.txt&quot;</span>], trainer=trainer)<!-- HTML_TAG_END --></pre></div>
<p>มาดูผลลัพธ์ของการ tokenize ข้อความตัวอย่างกัน :</p>

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	<pre><!-- HTML_TAG_START -->encoding = tokenizer.encode(<span class="hljs-string">&quot;Let&#x27;s test this tokenizer.&quot;</span>)
<span class="hljs-built_in">print</span>(encoding.tokens)<!-- HTML_TAG_END --></pre></div>

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	<pre><!-- HTML_TAG_START -->[<span class="hljs-string">&#x27;L&#x27;</span>, <span class="hljs-string">&#x27;et&#x27;</span>, <span class="hljs-string">&quot;&#x27;&quot;</span>, <span class="hljs-string">&#x27;s&#x27;</span>, <span class="hljs-string">&#x27;Ġtest&#x27;</span>, <span class="hljs-string">&#x27;Ġthis&#x27;</span>, <span class="hljs-string">&#x27;Ġto&#x27;</span>, <span class="hljs-string">&#x27;ken&#x27;</span>, <span class="hljs-string">&#x27;izer&#x27;</span>, <span class="hljs-string">&#x27;.&#x27;</span>]<!-- HTML_TAG_END --></pre></div>
<p>เราจะทำการ post-processing แบบ byte-level ให้กับ GPT-2 tokenizer ดังนี้ :</p>

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	<pre><!-- HTML_TAG_START -->tokenizer.post_processor = processors.ByteLevel(trim_offsets=<span class="hljs-literal">False</span>)<!-- HTML_TAG_END --></pre></div>
<p><code>trim_offsets = False</code> แปลว่าเราจะไม่เปลี่ยนแปลงค่า offset ของ token ที่ขึ้นต้นด้วย <code>Ġ</code> ซึ่งแปลว่าตำแหน่งเริ่มต้นของ offset จะหมายถึง ช่องว่าง และไม่ใช่ตัวอักษรแรกของ token นั้น</p>
<p>มาดูผลลัพธ์ของข้อความที่เราเพิ่งจะ encode กันไป ในตัวอย่างนี้ token ในตำแหน่งที่ 4 คือ <code>&#39;Ġtest&#39;</code> :</p>

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	<pre><!-- HTML_TAG_START -->sentence = <span class="hljs-string">&quot;Let&#x27;s test this tokenizer.&quot;</span>
encoding = tokenizer.encode(sentence)
start, end = encoding.offsets[<span class="hljs-number">4</span>]
sentence[start:end]<!-- HTML_TAG_END --></pre></div>

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	<pre><!-- HTML_TAG_START --><span class="hljs-string">&#x27; test&#x27;</span><!-- HTML_TAG_END --></pre></div>
<p>สุดท้ายเราจะเพิ่มส่วนที่เป็น byte-level decoder :</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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	<pre><!-- HTML_TAG_START -->tokenizer.decoder = decoders.ByteLevel()<!-- HTML_TAG_END --></pre></div>
<p>เช็คดูอีกทีว่าผลลัพธ์ถูกต้องหรือไม่ :</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
	<div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div>
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	<pre><!-- HTML_TAG_START -->tokenizer.decode(encoding.ids)<!-- HTML_TAG_END --></pre></div>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
	<div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div>
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	<pre><!-- HTML_TAG_START --><span class="hljs-string">&quot;Let&#x27;s test this tokenizer.&quot;</span><!-- HTML_TAG_END --></pre></div>
<p>เยี่ยมมาก! ตอนนี้คุณสามารถเซฟโมเดลได้ ส่วนขั้นต่อไปคือ เราจะ wrap tokenizer ของเราให้เป็น <code>PreTrainedTokenizerFast</code> หรือ <code>GPT2TokenizerFast</code> เพื่อจะได้เรียกใช้มันได้ใน 🤗 Transformers</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
	<div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div>
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	<pre><!-- HTML_TAG_START --><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> PreTrainedTokenizerFast

wrapped_tokenizer = PreTrainedTokenizerFast(
    tokenizer_object=tokenizer,
    bos_token=<span class="hljs-string">&quot;&lt;|endoftext|&gt;&quot;</span>,
    eos_token=<span class="hljs-string">&quot;&lt;|endoftext|&gt;&quot;</span>,
)<!-- HTML_TAG_END --></pre></div>
<p>หรือ :</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
	<div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div>
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	<pre><!-- HTML_TAG_START --><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> GPT2TokenizerFast

wrapped_tokenizer = GPT2TokenizerFast(tokenizer_object=tokenizer)<!-- HTML_TAG_END --></pre></div>
<p>ต่อไปเราจะสอนวิธีสร้าง Unigram tokenizer บ้าง</p>
<h2 class="relative group"><a id="unigram-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="#unigram-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>การสร้าง Unigram tokenizer ตั้งแต่เริ่มต้น
	</span></h2>

<p>เราจะสร้าง XLNet tokenizer โดยเริ่มจาก initialize <code>Tokenizer</code> ด้วย Unigram model !</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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	<pre><!-- HTML_TAG_START -->tokenizer = Tokenizer(models.Unigram())<!-- HTML_TAG_END --></pre></div>
<p>คุณสามารถ initialize มันโดยส่งผ่าน vocabulary ที่มีอยู่เข้าไปด้วย</p>
<p>ในขั้นตอน normalization โมเดล XLNet จะมีการแทนที่ตัวอักษรต่างๆ :</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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	<pre><!-- HTML_TAG_START --><span class="hljs-keyword">from</span> tokenizers <span class="hljs-keyword">import</span> Regex

tokenizer.normalizer = normalizers.<span class="hljs-type">Sequence</span>(
    [
        normalizers.Replace(<span class="hljs-string">&quot;``&quot;</span>, <span class="hljs-string">&#x27;&quot;&#x27;</span>),
        normalizers.Replace(<span class="hljs-string">&quot;&#x27;&#x27;&quot;</span>, <span class="hljs-string">&#x27;&quot;&#x27;</span>),
        normalizers.NFKD(),
        normalizers.StripAccents(),
        normalizers.Replace(Regex(<span class="hljs-string">&quot; {2,}&quot;</span>), <span class="hljs-string">&quot; &quot;</span>),
    ]
)<!-- HTML_TAG_END --></pre></div>
<p>โค้ดข้างบนนี้จะแทนที่ <code>“</code> และ <code>”</code> ด้วย <code>”</code>
และถ้ามีช่องว่างที่อยู่ต่อๆกัน มันจะถูกแปลงให้เป็นช่องว่างเดียว และสุดท้ายมันจะลบสัญลักษณ์ accent ออกด้วย</p>
<p>pre-tokenizer ที่ใช้ใน SentencePiece tokenizer คือ <code>Metaspace</code>  :</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
	<div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div>
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	<pre><!-- HTML_TAG_START -->tokenizer.pre_tokenizer = pre_tokenizers.Metaspace()<!-- HTML_TAG_END --></pre></div>
<p>มาดูผลลัพธ์ของการ pre-tokenization กับข้อความตัวอย่างกัน  :</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
	<div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div>
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	<pre><!-- HTML_TAG_START -->tokenizer.pre_tokenizer.pre_tokenize_str(<span class="hljs-string">&quot;Let&#x27;s test the pre-tokenizer!&quot;</span>)<!-- HTML_TAG_END --></pre></div>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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	<pre><!-- HTML_TAG_START -->[(<span class="hljs-string">&quot;▁Let&#x27;s&quot;</span>, (<span class="hljs-number">0</span>, <span class="hljs-number">5</span>)), (<span class="hljs-string">&#x27;▁test&#x27;</span>, (<span class="hljs-number">5</span>, <span class="hljs-number">10</span>)), (<span class="hljs-string">&#x27;▁the&#x27;</span>, (<span class="hljs-number">10</span>, <span class="hljs-number">14</span>)), (<span class="hljs-string">&#x27;▁pre-tokenizer!&#x27;</span>, (<span class="hljs-number">14</span>, <span class="hljs-number">29</span>))]<!-- HTML_TAG_END --></pre></div>
<p>ขั้นต่อไปคือการเทรน  XLNet มีการใช้ token พิเศษอยู่จำนวนหนึ่ง :</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
	<div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div>
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	<pre><!-- HTML_TAG_START -->special_tokens = [<span class="hljs-string">&quot;&lt;cls&gt;&quot;</span>, <span class="hljs-string">&quot;&lt;sep&gt;&quot;</span>, <span class="hljs-string">&quot;&lt;unk&gt;&quot;</span>, <span class="hljs-string">&quot;&lt;pad&gt;&quot;</span>, <span class="hljs-string">&quot;&lt;mask&gt;&quot;</span>, <span class="hljs-string">&quot;&lt;s&gt;&quot;</span>, <span class="hljs-string">&quot;&lt;/s&gt;&quot;</span>]
trainer = trainers.UnigramTrainer(
    vocab_size=<span class="hljs-number">25000</span>, special_tokens=special_tokens, unk_token=<span class="hljs-string">&quot;&lt;unk&gt;&quot;</span>
)
tokenizer.train_from_iterator(get_training_corpus(), trainer=trainer)<!-- HTML_TAG_END --></pre></div>
<p>สิ่งสำคัญเวลาใช้ <code>UnigramTrainer</code> คือ อย่าลืมกำหนด argument <code>unk_token</code>
นอกจากนั้นคุณยังสามารถตั้งค่า argument อื่นๆที่ต้องใช้กับ Unigram algorithm ได้ด้วย เช่น <code>shrinking_factor</code> (ค่าเริ่มต้นคือ  0.75) หรือ <code>max_piece_length</code> (ค่าเริ่มต้นคือ 16)</p>
<p>เราสามารถเทรนจากไฟล์ข้อความได้ด้วย  :</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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	<pre><!-- HTML_TAG_START -->tokenizer.model = models.Unigram()
tokenizer.train([<span class="hljs-string">&quot;wikitext-2.txt&quot;</span>], trainer=trainer)<!-- HTML_TAG_END --></pre></div>
<p>ลอง tokenize ตัวอย่างง่ายๆดู  :</p>

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	<pre><!-- HTML_TAG_START -->encoding = tokenizer.encode(<span class="hljs-string">&quot;Let&#x27;s test this tokenizer.&quot;</span>)
<span class="hljs-built_in">print</span>(encoding.tokens)<!-- HTML_TAG_END --></pre></div>

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	<pre><!-- HTML_TAG_START -->[<span class="hljs-string">&#x27;▁Let&#x27;</span>, <span class="hljs-string">&quot;&#x27;&quot;</span>, <span class="hljs-string">&#x27;s&#x27;</span>, <span class="hljs-string">&#x27;▁test&#x27;</span>, <span class="hljs-string">&#x27;▁this&#x27;</span>, <span class="hljs-string">&#x27;▁to&#x27;</span>, <span class="hljs-string">&#x27;ken&#x27;</span>, <span class="hljs-string">&#x27;izer&#x27;</span>, <span class="hljs-string">&#x27;.&#x27;</span>]<!-- HTML_TAG_END --></pre></div>
<p>XLNet จะเพิ่ม token พิเศษ <code>&lt;cls&gt;</code> ใส่ในตอนท้ายของประโยค และตั้งค่า type ID มันเป็น 2 เพื่อให้มันแตกต่างจาก token อื่น
การทำแบบนี้ถือว่าเป็นการ padding ทางด้ายซ้าย</p>
<p>เพื่อจัดการกับ token พิเศษ เราจะต้องสร้าง template ขึ้นมา ก่อนอื่นเราต้องดูว่า ID ของ <code>&lt;cls&gt;</code> และ <code>&lt;sep&gt;</code> คืออะไร :</p>

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	<pre><!-- HTML_TAG_START -->cls_token_id = tokenizer.token_to_id(<span class="hljs-string">&quot;&lt;cls&gt;&quot;</span>)
sep_token_id = tokenizer.token_to_id(<span class="hljs-string">&quot;&lt;sep&gt;&quot;</span>)
<span class="hljs-built_in">print</span>(cls_token_id, sep_token_id)<!-- HTML_TAG_END --></pre></div>

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	<pre><!-- HTML_TAG_START --><span class="hljs-number">0</span> <span class="hljs-number">1</span><!-- HTML_TAG_END --></pre></div>
<p>นี่คือตัวอย่างการสร้าง template :</p>

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	<pre><!-- HTML_TAG_START -->tokenizer.post_processor = processors.TemplateProcessing(
    single=<span class="hljs-string">&quot;$A:0 &lt;sep&gt;:0 &lt;cls&gt;:2&quot;</span>,
    pair=<span class="hljs-string">&quot;$A:0 &lt;sep&gt;:0 $B:1 &lt;sep&gt;:1 &lt;cls&gt;:2&quot;</span>,
    special_tokens=[(<span class="hljs-string">&quot;&lt;sep&gt;&quot;</span>, sep_token_id), (<span class="hljs-string">&quot;&lt;cls&gt;&quot;</span>, cls_token_id)],
)<!-- HTML_TAG_END --></pre></div>
<p>เราจะทดลองใช้งานมันโดยการ encode ประโยค input สองประโยค :</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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	<pre><!-- HTML_TAG_START -->encoding = tokenizer.encode(<span class="hljs-string">&quot;Let&#x27;s test this tokenizer...&quot;</span>, <span class="hljs-string">&quot;on a pair of sentences!&quot;</span>)
<span class="hljs-built_in">print</span>(encoding.tokens)
<span class="hljs-built_in">print</span>(encoding.type_ids)<!-- HTML_TAG_END --></pre></div>

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	<pre><!-- HTML_TAG_START -->[<span class="hljs-string">&#x27;▁Let&#x27;</span>, <span class="hljs-string">&quot;&#x27;&quot;</span>, <span class="hljs-string">&#x27;s&#x27;</span>, <span class="hljs-string">&#x27;▁test&#x27;</span>, <span class="hljs-string">&#x27;▁this&#x27;</span>, <span class="hljs-string">&#x27;▁to&#x27;</span>, <span class="hljs-string">&#x27;ken&#x27;</span>, <span class="hljs-string">&#x27;izer&#x27;</span>, <span class="hljs-string">&#x27;.&#x27;</span>, <span class="hljs-string">&#x27;.&#x27;</span>, <span class="hljs-string">&#x27;.&#x27;</span>, <span class="hljs-string">&#x27;&lt;sep&gt;&#x27;</span>, <span class="hljs-string">&#x27;▁&#x27;</span>, <span class="hljs-string">&#x27;on&#x27;</span>, <span class="hljs-string">&#x27;▁&#x27;</span>, <span class="hljs-string">&#x27;a&#x27;</span>, <span class="hljs-string">&#x27;▁pair&#x27;</span>,
  <span class="hljs-string">&#x27;▁of&#x27;</span>, <span class="hljs-string">&#x27;▁sentence&#x27;</span>, <span class="hljs-string">&#x27;s&#x27;</span>, <span class="hljs-string">&#x27;!&#x27;</span>, <span class="hljs-string">&#x27;&lt;sep&gt;&#x27;</span>, <span class="hljs-string">&#x27;&lt;cls&gt;&#x27;</span>]
[<span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">0</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">2</span>]<!-- HTML_TAG_END --></pre></div>
<p>จากนั้นตั้งค่า decoder เป็น <code>Metaspace</code> :</p>

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	<pre><!-- HTML_TAG_START -->tokenizer.decoder = decoders.Metaspace()<!-- HTML_TAG_END --></pre></div>
<p>ตอนนี้เราก็เสร็จแล้ว คุณสามารถเซฟ tokenizer และ wrap มันให้เป็น <code>PreTrainedTokenizerFast</code> หรือ <code>XLNetTokenizerFast</code> ก็ได้ ถ้าคุณต้องการใช้มันใน 🤗 Transformers</p>
<p>สิ่งสำคัญอีกอย่างเวลาใช้ <code>PreTrainedTokenizerFast</code> ก็คือเราจะต้องบอก 🤗 Transformers library ว่าเราได้ทำการ padding ทางซ้าย :</p>

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	<pre><!-- HTML_TAG_START --><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> PreTrainedTokenizerFast

wrapped_tokenizer = PreTrainedTokenizerFast(
    tokenizer_object=tokenizer,
    bos_token=<span class="hljs-string">&quot;&lt;s&gt;&quot;</span>,
    eos_token=<span class="hljs-string">&quot;&lt;/s&gt;&quot;</span>,
    unk_token=<span class="hljs-string">&quot;&lt;unk&gt;&quot;</span>,
    pad_token=<span class="hljs-string">&quot;&lt;pad&gt;&quot;</span>,
    cls_token=<span class="hljs-string">&quot;&lt;cls&gt;&quot;</span>,
    sep_token=<span class="hljs-string">&quot;&lt;sep&gt;&quot;</span>,
    mask_token=<span class="hljs-string">&quot;&lt;mask&gt;&quot;</span>,
    padding_side=<span class="hljs-string">&quot;left&quot;</span>,
)<!-- HTML_TAG_END --></pre></div>
<p>อีกวิธีก็คือ :</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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	<pre><!-- HTML_TAG_START --><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> XLNetTokenizerFast

wrapped_tokenizer = XLNetTokenizerFast(tokenizer_object=tokenizer)<!-- HTML_TAG_END --></pre></div>
<p>ตอนนี้ คุณก็ได้เรียนรู้ขั้นตอนในการสร้าง tokenizer ขึ้นมาเองแล้ว โดยการใช้เครื่องมือจาก 🤗 Tokenizers library และได้เรียนวิธีการนำ tokenizer ของคุณไปใช้ใน 🤗 Transformers อีกด้วย</p>


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