Kikai gakushū enjinia no tame no Transformers : saisentan no shizen gengo shori raiburari ni yoru moderu kaihatsu /
機械学習エンジニアのためのTransformers : 最先端の自然言語処理ライブラリによるモデル開発 /
"Since their introduction in 2017, transformers have quickly become the dominant architecture for achieving state-of-the-art results on a variety of natural language processing tasks. If you're a data scientist or coder, this practical book -now revised in full color- shows you how to trai...
Clasificación: | Libro Electrónico |
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Autores principales: | , , |
Otros Autores: | |
Formato: | Electrónico eBook |
Idioma: | Japonés Inglés |
Publicado: |
Tōkyō-to Shinjuku-ku :
Orairī Japan,
2022.
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Edición: | Shohan. |
Temas: | |
Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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003 | OCoLC | ||
005 | 20231017213018.0 | ||
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066 | |c Hani |c $1 | ||
020 | |a 9784873119953 |q (electronic bk.) | ||
020 | |a 4873119952 |q (electronic bk.) | ||
029 | 1 | |a AU@ |b 000074572453 | |
035 | |a (OCoLC)1370619690 | ||
037 | |a 9784873119953 |b O'Reilly Media | ||
041 | 1 | |a jpn |h eng | |
050 | 4 | |a QA76.9.N38 | |
082 | 0 | 4 | |a 006.3/5 |2 23/eng/20230220 |
049 | |a UAMI | ||
100 | 1 | |a Tunstall, Lewis, |e author. | |
240 | 1 | 0 | |a Natural language processing with transformers. |l Japanese |
245 | 1 | 0 | |6 880-01 |a Kikai gakushū enjinia no tame no Transformers : |b saisentan no shizen gengo shori raiburari ni yoru moderu kaihatsu / |c Lewis Tunstall, Leandro von Werra, Thomas Wolf cho ; Nakayama Hiroki yaku = Natural language processing with transformers : building language applications with Hugging Face / Lewis Tunstall, Leandro von Werra and Thomas Wolf. |
246 | 3 | 1 | |a Natural language processing with transformers : |b building language applications with Hugging Face |
250 | |6 880-02 |a Shohan. | ||
264 | 1 | |6 880-03 |a Tōkyō-to Shinjuku-ku : |b Orairī Japan, |c 2022. | |
300 | |a 1 online resource (424 pages) : |b color illustrations.. | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
546 | |a In Japanese. | ||
504 | |a Includes bibiographical references. | ||
520 | |a "Since their introduction in 2017, transformers have quickly become the dominant architecture for achieving state-of-the-art results on a variety of natural language processing tasks. If you're a data scientist or coder, this practical book -now revised in full color- shows you how to train and scale these large models using Hugging Face Transformers, a Python-based deep learning library. Transformers have been used to write realistic news stories, improve Google Search queries, and even create chatbots that tell corny jokes. In this guide, authors Lewis Tunstall, Leandro von Werra, and Thomas Wolf, among the creators of Hugging Face Transformers, use a hands-on approach to teach you how transformers work and how to integrate them in your applications. You'll quickly learn a variety of tasks they can help you solve. Build, debug, and optimize transformer models for core NLP tasks, such as text classification, named entity recognition, and question answering Learn how transformers can be used for cross-lingual transfer learning Apply transformers in real-world scenarios where labeled data is scarce Make transformer models efficient for deployment using techniques such as distillation, pruning, and quantization Train transformers from scratch and learn how to scale to multiple GPUs and distributed environments." -- |c Provided by publisher. | ||
590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
650 | 0 | |a Natural language processing (Computer science) | |
650 | 0 | |a Python (Computer program language) | |
650 | 0 | |a Deep learning (Machine learning) | |
650 | 7 | |a Deep learning (Machine learning) |2 fast |0 (OCoLC)fst02032663 | |
650 | 7 | |a Natural language processing (Computer science) |2 fast |0 (OCoLC)fst01034365 | |
650 | 7 | |a Python (Computer program language) |2 fast |0 (OCoLC)fst01084736 | |
700 | 1 | |a Werra, Leandro von, |e author | |
700 | 1 | |a Wolf, Thomas |c (Of HuggingFace), |e author. | |
700 | 1 | |6 880-04 |a Nakayama, Hiroki, |e translator. | |
765 | 0 | 8 | |i Translation of: |a Tunstall, Lewis. |t Natural language processing with transformers. |b Revised edition. |d SEBASTOPOL : O'REILLY MEDIA, 2022 |z 1098136764 |w (OCoLC)1321899597 |
856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9784873119953/?ar |z Texto completo (Requiere registro previo con correo institucional) |
880 | 1 | 0 | |6 245-01/$1 |a 機械学習エンジニアのためのTransformers : |b 最先端の自然言語処理ライブラリによるモデル開発 / |c Lewis Tunstall, Leandro von Werra, Thomas Wolf著 ; 中山光樹訳 = Natural language processing with transformers : building language applications with Hugging Face / Lewis Tunstall, Leandro von Werra and Thomas Wolf. |
880 | |6 250-02/$1 |a 初版. | ||
880 | 1 | |6 264-03/$1 |a 東京都新宿区 : |b オライリー・ジャパン, |c 2022. | |
880 | |6 520-00/$1 |a "「Hugging Face Transformers」を使った自然言語処理の解説書。2017年の登場以来、Transformerと呼ばれるアーキテクチャを使った大規模なモデルが急速に普及しています。本書では、Hugging Faceの開発者らが、「Hugging Face Transformers」を使って、これらの大規模モデルを学習しスケールする方法をわかりやすく紹介します。テキスト分類、固有表現認識、テキスト生成、要約、質問応答といったタスクだけでなく、蒸留、量子化、枝刈り、ONNX Runtimeといったモデルの高速化技術、ラベル付きデータが少ないときに使えるゼロショット学習や少数事例学習、その他、多言語転移やドメイン適応といった類書では扱っていない技術についても解説しています。" -- |c Provided by publisher. | ||
880 | 1 | |6 700-04/$1 |a 中山光樹, |e translator. | |
994 | |a 92 |b IZTAP |