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\n\n \n\n\n\n\n## 推荐语\n\n\n
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\n\n本书的编者长期从事大模型技术的相关研究，曾组织研发了文澜、玉兰等一系列大模型，具有深厚的科研与实践积累。本书内容深入结合了编者在研发大模型过程中的第一手经验，全面覆盖了大模型技术的多方面知识，可以作为深入学习大模型技术的参考书籍，强烈推荐阅读!
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\n\n本书的编写团队于2023年3月发布了学术界首篇大语言模型综述文章“A Survey of Large Language Models”，受到了广泛关注。在这篇经典综述文章基础上，编写团队对编写内容进行了精心组织与撰写，并且融入了其长期从事大模型技术的科研经验。本书具有重要的参考与学习价值，是一部值得推荐的大模型佳作。
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\n\n## 课程资源\n为了帮助课程教学及传播大模型知识，《大语言模型》编写团队特别提供了相应的PDF课件：\n\n\n| 课程 | 目录 |\n|:----:|:----:|\n| 第一课 初识大模型（对应本书第一、二章） | [语言模型发展历程](https://github.com/LLMBook-zh/LLMBook-zh.github.io/blob/main/slides/%E7%AC%AC%E4%B8%80%E8%AF%BE%20%E5%88%9D%E8%AF%86%E5%A4%A7%E6%A8%A1%E5%9E%8B/1.1%20%E8%AF%AD%E8%A8%80%E6%A8%A1%E5%9E%8B%E5%8F%91%E5%B1%95%E5%8E%86%E7%A8%8B.pdf)、[大模型技术基础](https://github.com/LLMBook-zh/LLMBook-zh.github.io/blob/main/slides/%E7%AC%AC%E4%B8%80%E8%AF%BE%20%E5%88%9D%E8%AF%86%E5%A4%A7%E6%A8%A1%E5%9E%8B/1.2%20%E5%A4%A7%E6%A8%A1%E5%9E%8B%E6%8A%80%E6%9C%AF%E5%9F%BA%E7%A1%80.pdf)、[GPT和DeepSeek模型介绍](https://github.com/LLMBook-zh/LLMBook-zh.github.io/blob/main/slides/%E7%AC%AC%E4%B8%80%E8%AF%BE%20%E5%88%9D%E8%AF%86%E5%A4%A7%E6%A8%A1%E5%9E%8B/1.3%20GPT%2BDeepSeek%E6%A8%A1%E5%9E%8B%E4%BB%8B%E7%BB%8D.pdf) |\n| 第二课 模型架构（对应本书第五章） | [Transformer模型介绍](https://github.com/LLMBook-zh/LLMBook-zh.github.io/blob/main/slides/%E7%AC%AC%E4%BA%8C%E8%AF%BE%20%E6%A8%A1%E5%9E%8B%E6%9E%B6%E6%9E%84/2.1%20Transformer%E6%A8%A1%E5%9E%8B.pdf)、[模型详细配置](https://github.com/LLMBook-zh/LLMBook-zh.github.io/blob/main/slides/%E7%AC%AC%E4%BA%8C%E8%AF%BE%20%E6%A8%A1%E5%9E%8B%E6%9E%B6%E6%9E%84/2.2%20%E6%A8%A1%E5%9E%8B%E8%AF%A6%E7%BB%86%E9%85%8D%E7%BD%AE.pdf)、[长上下文模型和新型架构](https://github.com/LLMBook-zh/LLMBook-zh.github.io/blob/main/slides/%E7%AC%AC%E4%BA%8C%E8%AF%BE%20%E6%A8%A1%E5%9E%8B%E6%9E%B6%E6%9E%84/2.3%20%E9%95%BF%E4%B8%8A%E4%B8%8B%E6%96%87%E6%A8%A1%E5%9E%8B%E5%92%8C%E6%96%B0%E5%9E%8B%E6%9E%B6%E6%9E%84.pdf) |\n| 第三课 预训练（对应本书第四、六章） | [预训练之数据工程](https://github.com/LLMBook-zh/LLMBook-zh.github.io/blob/main/slides/%E7%AC%AC%E4%B8%89%E8%AF%BE%20%E9%A2%84%E8%AE%AD%E7%BB%83/3.1%20%E9%A2%84%E8%AE%AD%E7%BB%83%E4%B9%8B%E6%95%B0%E6%8D%AE%E5%B7%A5%E7%A8%8B.pdf)、[预训练之具体流程](https://github.com/LLMBook-zh/LLMBook-zh.github.io/blob/main/slides/%E7%AC%AC%E4%B8%89%E8%AF%BE%20%E9%A2%84%E8%AE%AD%E7%BB%83/3.2%E9%A2%84%E8%AE%AD%E7%BB%83%E4%B9%8B%E5%85%B7%E4%BD%93%E6%B5%81%E7%A8%8B.pdf)、[训练优化](https://github.com/LLMBook-zh/LLMBook-zh.github.io/blob/main/slides/%E7%AC%AC%E4%B8%89%E8%AF%BE%20%E9%A2%84%E8%AE%AD%E7%BB%83/3.3%E9%A2%84%E8%AE%AD%E7%BB%83%E4%B9%8B%E8%AE%AD%E7%BB%83%E4%BC%98%E5%8C%96%E4%B8%8E%E6%95%88%E7%8E%87.pdf)、[模型参数量与训练效率估","github_created_at":"2024-04-15T02:50:32+00:00","created_at":"2026-07-07T17:35:10.09627+00:00","updated_at":"2026-08-17T18:00:48.738182+00:00","categories":[{"slug":"developer-tools","name":"Developer Tools","url":"https://www.graphcanon.com/categories/developer-tools","markdown_url":"https://www.graphcanon.com/categories/developer-tools.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/developer-tools"},{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"artificial-intelligence","name":"artificial-intelligence"},{"slug":"deep-learning","name":"deep-learning"},{"slug":"deep-neural-networks","name":"deep-neural-networks"},{"slug":"fine-tuning","name":"fine-tuning"},{"slug":"language-model","name":"language-model"},{"slug":"large-language-models","name":"large language models"},{"slug":"natural-language-processing","name":"natural-language-processing"},{"slug":"nlp","name":"nlp"}],"trust":{"provenance":{"is_fork":false,"github_id":786642156,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-17T18:00:46.332Z","maintenance":{"label":"Slowing","score":36,"methodology":"github_public_v1","releases_90d":0,"days_since_push":349,"last_release_at":null,"stars_delta_30d":13,"open_issues_delta_30d":0},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:04:58.362Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-17T18:00:47.612Z"},"languages":{"value":["python"],"source":"github.language","observed_at":"2026-08-17T18:00:47.612Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["When looking for detailed explanations of LLM technologies written in Chinese","For readers with a basic understanding of deep learning but needing deeper insights into specific LLMs"],"when_not_to_use":["If your primary language is not Chinese and you seek immediate practical application","For advanced researchers preferring the latest, cutting-edge research without detailed foundational explanations"],"source":"enrich:decision_facts","observed_at":"2026-07-12T18:03:14.358Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"LLMBook-zh.github.io is a comprehensive guide on Large Language Models (LLMs) written in Chinese, ideal for Chinese-speaking beginners seeking to understand LLMs deeply."}]}}大模型作为一种快速兴起的人工智能技术，已经深刻地影响了未来的科技发展趋势。为了更好地推进大模型技术在我国的学习与普及，亟须有专业的中文技术图书进行系统介绍。本书是一部精心编写的大模型技术图书，涵盖了预训练、微调、对齐、提示工程等众多基础内容，能够为相关从业人员提供权威的、系统的学习参考，强烈推荐阅读。
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