<feed xmlns="http://www.w3.org/2005/Atom"><title>ckumemohythy&#39;s Ownd</title><link href="https://ckumemohythy.themedia.jp"></link><id>https://ckumemohythy.themedia.jp</id><author><name>ckumemohythy</name></author><updated>2026-05-07T06:48:10+00:00</updated><entry><title><![CDATA[Read [pdf]> Chainsaw Man, Vol. 14 by Tatsuki Fujimoto]]></title><link rel="alternate" href="https://ckumemohythy.themedia.jp/posts/58801854/"></link><id>https://ckumemohythy.themedia.jp/posts/58801854</id><summary><![CDATA[Chainsaw Man, Vol. 14 by Tatsuki Fujimoto






                





    Chainsaw Man, Vol. 14
    Tatsuki Fujimoto
    Page: 192
    Format: pdf, ePub, mobi, fb2
        ISBN: 9781974743582
            Publisher: VIZ Media LLC
    

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]]></summary><author><name>ckumemohythy</name></author><published>2026-05-07T06:48:10+00:00</published><updated>2026-05-07T06:48:12+00:00</updated><content type="html"><![CDATA[
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			<h2>Chainsaw Man, Vol. 14 by Tatsuki Fujimoto</h2>
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</p><ul>
    <li>Chainsaw Man, Vol. 14</li>
    <li>Tatsuki Fujimoto</li>
    <li>Page: 192</li>
    <li>Format: pdf, ePub, mobi, fb2</li>
        <li>ISBN: 9781974743582</li>
            <li>Publisher: VIZ Media LLC</li>
    </ul>
<p></p>
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	]]></content></entry><entry><title><![CDATA[[Pdf/ePub] Hands-On Large Language Models:]]></title><link rel="alternate" href="https://ckumemohythy.themedia.jp/posts/58801849/"></link><id>https://ckumemohythy.themedia.jp/posts/58801849</id><summary><![CDATA[Hands-On Large Language Models: Language Understanding and Generation by Jay Alammar, Maarten Grootendorst






                





    Hands-On Large Language Models: Language Understanding and Generation
    Jay Alammar, Maarten Grootendorst
    Page: 425
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        ISBN: 9781098150969
            Publisher: O'Reilly Media, Incorporated
    

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Overview
AI has acquired startling new language capabilities in just the past few years. Driven by rapid advances in deep learning, language AI systems are able to write and understand text better than ever before. This trend is enabling new features, products, and entire industries. Through this book's visually educational nature, readers will learn practical tools and concepts they need to use these capabilities today. You'll understand how to use pretrained large language models for use cases like copywriting and summarization; create semantic search systems that go beyond keyword matching; and use existing libraries and pretrained models for text classification, search, and clusterings. This book also helps you: Understand the architecture of Transformer language models that excel at text generation and representation Build advanced LLM pipelines to cluster text documents and explore the topics they cover Build semantic search engines that go beyond keyword search, using methods like dense retrieval and rerankers Explore how generative models can be used, from prompt engineering all the way to retrieval-augmented generation Gain a deeper understanding of how to train LLMs and optimize them for specific applications using generative model fine-tuning, contrastive fine-tuning, and in-context learning





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]]></summary><author><name>ckumemohythy</name></author><published>2026-05-07T06:46:41+00:00</published><updated>2026-05-07T06:46:44+00:00</updated><content type="html"><![CDATA[
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			<h2>Hands-On Large Language Models: Language Understanding and Generation by Jay Alammar, Maarten Grootendorst</h2>
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<p>

</p><ul>
    <li>Hands-On Large Language Models: Language Understanding and Generation</li>
    <li>Jay Alammar, Maarten Grootendorst</li>
    <li>Page: 425</li>
    <li>Format: pdf, ePub, mobi, fb2</li>
        <li>ISBN: 9781098150969</li>
            <li>Publisher: O'Reilly Media, Incorporated</li>
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<h4>Overview</h4>
<p>AI has acquired startling new language capabilities in just the past few years. Driven by rapid advances in deep learning, language AI systems are able to write and understand text better than ever before. This trend is enabling new features, products, and entire industries. Through this book's visually educational nature, readers will learn practical tools and concepts they need to use these capabilities today. You'll understand how to use pretrained large language models for use cases like copywriting and summarization; create semantic search systems that go beyond keyword matching; and use existing libraries and pretrained models for text classification, search, and clusterings. This book also helps you: Understand the architecture of Transformer language models that excel at text generation and representation Build advanced LLM pipelines to cluster text documents and explore the topics they cover Build semantic search engines that go beyond keyword search, using methods like dense retrieval and rerankers Explore how generative models can be used, from prompt engineering all the way to retrieval-augmented generation Gain a deeper understanding of how to train LLMs and optimize them for specific applications using generative model fine-tuning, contrastive fine-tuning, and in-context learning</p>




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