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Mô hình ngôn ngữ lớn cho mọi người LLM (Mô hình ngôn ngữ lớn) Phần 1 - Dùng thử Tinh chỉnh Llama 2

Bạn sẽ học từng bước từ các khái niệm cơ bản về LLM (Mô hình ngôn ngữ lớn) cho đến cách tinh chỉnh mô hình Llama 2, LLM hiệu suất cao, trên tập dữ liệu bạn chọn.

(4.7) 84 đánh giá

1,278 học viên

  • AISchool
이론 실습 모두
전이학습
딥러닝모델
LLM
Llama
Deep Learning(DL)
PyTorch
ChatGPT

Đánh giá từ những học viên đầu tiên

Dịch cái này sang tiếng Việt

  • Các khái niệm cơ bản về LLM (Mô hình ngôn ngữ lớn)

  • Cách tinh chỉnh mô hình Llama 2, LLM hiệu suất cao, trên tập dữ liệu tôi muốn

  • Cách tinh chỉnh GPT cho tập dữ liệu của riêng bạn bằng API OpenAI

  • Các kỹ thuật tinh chỉnh hiệu quả tham số (PEFT) khác nhau

  • Các kỹ thuật kỹ thuật nhanh chóng khác nhau để tối đa hóa hiệu suất của LLM

Thạc sĩ Luật về công nghệ AI tiên tiến, từ khái niệm đến điều chỉnh mô hình!

✨ LLM, bông hoa của công nghệ AI tiên tiến

Bằng cách tận dụng đúng Llama2 và API OpenAI, chúng ta có thể tạo ra một LLM mạnh hơn GPT-4, LLM mạnh nhất hiện nay, trong một phạm vi hẹp!

  • ✅ Bạn có thể học từng bước từ các khái niệm cơ bản của LLM (Mô hình ngôn ngữ lớn) mới nhất đến Llama 2 Fine-Tuning.
  • ✅ Tìm hiểu cách tinh chỉnh Llama 2 trên tập dữ liệu của riêng bạn, từng bước một!

Khóa học này dành cho ai?

Mô hình LLM mới nhất
Các khái niệm và nguyên tắc
Học tập kỹ lưỡng
Những người muốn 

Nguồn mở hiệu suất cao
LLM Llama 2
Trong tập dữ liệu của riêng tôi
Tinh chỉnh
Những người muốn

Giống như PEFT
Xu hướng LLM mới nhất
Những người muốn học

Sử dụng API OpenAI
Tinh chỉnh GPT
 Tìm hiểu cách
Những người muốn

Bài giảng của người chơi ✅

👋 Khóa học này yêu cầu bạn đã có kiến thức nền tảng về Python, học sâu và xử lý ngôn ngữ tự nhiên (NLP) . Vui lòng học các khóa học bên dưới hoặc có kiến thức tương đương trước khi tham gia khóa học này.

Bài giảng tiếp theo ✅

Hỏi & Đáp 💬

H. LLM (Mô hình ngôn ngữ lớn) là gì?

LLM là viết tắt của "Mô hình Ngôn ngữ Lớn", một mô hình ngôn ngữ AI được đào tạo trên các tập dữ liệu lớn. Các mô hình này được sử dụng rộng rãi trong các tác vụ xử lý ngôn ngữ tự nhiên (NLP) và có thể thực hiện nhiều tác vụ khác nhau, bao gồm tạo văn bản, phân loại, dịch thuật, trả lời câu hỏi và phân tích cảm xúc.

Thông thường, LLM có hàng triệu tham số , cho phép mô hình học được nhiều mẫu và cấu trúc ngôn ngữ khác nhau. Nhờ đó, LLM có thể tạo ra văn bản cực kỳ tinh vi và tự nhiên.

Ví dụ, các mô hình như loạt Generative Pre-trained Transformer (GPT) do OpenAI phát triển là một ví dụ điển hình của LLM. Các mô hình này được đào tạo trên các tập dữ liệu văn bản lớn, chẳng hạn như trang web, sách, báo và bài viết, và sau đó có thể được áp dụng cho nhiều tác vụ xử lý ngôn ngữ tự nhiên.

LLM hiện đang được sử dụng trong nhiều ứng dụng thương mại và được công nhận về giá trị trong nhiều lĩnh vực, bao gồm chatbot, công cụ tìm kiếm, dịch vụ dịch máy và đề xuất nội dung. Tuy nhiên, các mô hình này vẫn có thể có những hạn chế trong các nhiệm vụ đòi hỏi trình độ chuyên môn cao và dễ gặp phải các vấn đề như tạo ra thông tin sai lệch, thiên vị và thiếu hiểu biết.

H. Người chơi có cần kiến thức không?

Khóa học này, [Mô hình Ngôn ngữ Lớn cho Mọi Người (LLM) Phần 1 - Tinh chỉnh Llama 2], bao gồm giải thích chi tiết và cách sử dụng mô hình LLM mới nhất. Do đó, khóa học này giả định bạn đã có hiểu biết cơ bản về học sâu và xử lý ngôn ngữ tự nhiên. Nếu bạn chưa có kiến thức này, chúng tôi khuyên bạn nên tham gia khóa học trước, [Giới thiệu về Học sâu và Xử lý Ngôn ngữ Tự nhiên: NLP với TensorFlow - Từ RNN đến BERT] .

📢 Vui lòng kiểm tra trước khi tham gia lớp học

  • Do môi trường ghi âm , chất lượng âm thanh của một số video có thể không đồng đều. (Vui lòng tham khảo bài giảng [Xem trước] trước khi tham gia khóa học.)

Khuyến nghị cho
những người này

Khóa học này dành cho ai?

  • Những người muốn tìm hiểu khái niệm và cách sử dụng mô hình ngôn ngữ lớn (LLM)

  • Bất kỳ ai muốn tinh chỉnh LLM mới nhất trên tập dữ liệu của riêng họ

  • Những người muốn có được một công việc trong lĩnh vực liên quan đến nghiên cứu deep learning

  • Những người muốn tiến hành nghiên cứu liên quan đến trí tuệ nhân tạo/deep learning

  • Những người chuẩn bị học cao học về trí tuệ nhân tạo (AI)

Cần biết trước khi bắt đầu?

  • Kinh nghiệm sử dụng Python

  • Bài giảng tiên quyết [Giới thiệu về Xử lý ngôn ngữ tự nhiên trong học tập sâu thông qua các ví dụ NLP với TensorFlow - Từ RNN đến BERT] Kinh nghiệm khóa học

Xin chào
Đây là

9,096

Học viên

671

Đánh giá

351

Trả lời

4.6

Xếp hạng

29

Các khóa học

Chương trình giảng dạy

Tất cả

127 bài giảng ∙ (30giờ 15phút)

Tài liệu khóa học:

Tài liệu bài giảng
Ngày đăng: 
Cập nhật lần cuối: 

Đánh giá

Tất cả

84 đánh giá

4.7

84 đánh giá

  • qkstjrdl965038님의 프로필 이미지
    qkstjrdl965038

    Đánh giá 6

    ∙

    Đánh giá trung bình 4.7

    3

    20% đã tham gia

    The lecture is good, but it seems like the materials were made using GPT. It would have been better if the materials were a little more refined.

    • 3040sw5011님의 프로필 이미지
      3040sw5011

      Đánh giá 1

      ∙

      Đánh giá trung bình 4.0

      4

      91% đã tham gia

      The content itself is fine, but the microphone quality is not good, and the author writes with a mouse and reads the explanations as if he is reading a book spread out in front of him. It would be a good idea to invest in some equipment.

      • new27kr

        I agree. I'm listening to the lecture, and the microphone keeps coming on and off. I wish you had invested in a microphone.

    • enopus님의 프로필 이미지
      enopus

      Đánh giá 11

      ∙

      Đánh giá trung bình 4.8

      4

      33% đã tham gia

      The content is really good, but I feel like the lecture preparation was lacking. Just like the lectures I took before, the readability of the notation using the mouse is so poor, which is disappointing. Additionally, some lectures had unstable volume due to microphone issues, and these parts could have been easily fixed by checking after recording, but when I see the videos uploaded as they are, I feel like they were not properly prepared. From the perspective of someone who is paying to listen, the lecture content is really good, but I wish they had paid a little more attention to the external aspects when recording.

      • jejeoppa3364님의 프로필 이미지
        jejeoppa3364

        Đánh giá 1

        ∙

        Đánh giá trung bình 4.0

        4

        30% đã tham gia

        I listened to all of the lectures according to the curriculum, and it seems like a lecture that contains the core well. However, not only this lecture, but all of the lectures in the curriculum, I don't understand the writing style on the board.. Writing with the mouse, drawing lines, etc., it seems like a really bad way to not concentrate, and it's worse than not doing anything at all... I think you'd be better off not taking notes. I think many other people have said this, but I think investing in this level of equipment will make the lecture quality much better.

        • senicyhan6139님의 프로필 이미지
          senicyhan6139

          Đánh giá 1

          ∙

          Đánh giá trung bình 5.0

          5

          100% đã tham gia

          It helped me with my LLM studies! It's great that you update it every time a new model comes out so I can catch up.

          1.850.420 ₫

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          YoungJea Oh

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          (For Product Managers) Fundamentals of LLM and Understanding LLM-Based Service Planning

          arigaram

          Describes the need for LLM, its technical background, and basic concepts.

          입문

          입문

          NLP, gpt, AI

          (For Product Managers) Fundamentals of LLM and Understanding LLM-Based Service Planning강의 썸네일

          (For Product Managers) Fundamentals of LLM and Understanding LLM-Based Service Planning

          arigaram

          Large-Scale Language Models for Everyone LLM Part 3 - Building AI Applications with Google Gemini API, OpenAI API, and Gemma강의 썸네일

          Large-Scale Language Models for Everyone LLM Part 3 - Building AI Applications with Google Gemini API, OpenAI API, and Gemma

          AISchool

          This course will teach you the concept of the Google Gemini model and how to use the Gemini API, and create various AI applications using Streamlit.

          중급이상

          중급이상

          openAI API, ChatGPT, gemini

          Large-Scale Language Models for Everyone LLM Part 3 - Building AI Applications with Google Gemini API, OpenAI API, and Gemma강의 썸네일

          Large-Scale Language Models for Everyone LLM Part 3 - Building AI Applications with Google Gemini API, OpenAI API, and Gemma

          AISchool

          <Building LLMs from Scratch> GitHub + Bonus Content Commentary강의 썸네일

          <Building LLMs from Scratch> GitHub + Bonus Content Commentary

          haesunpark

          This is a course covering the GitHub notebooks and bonus content from <Build a Large Language Model from Scratch> (Gilbut, 2025). GitHub: https://github.com/rickiepark/llm-from-scratch/ <Build a Large Language Model from Scratch> is the Korean translation of the bestseller <Build a Large Language Model (from Scratch)> (Manning, 2024) by Sebastian Raschka. This book provides a way to learn and utilize the operating principles of large language models by building a complete model starting from scratch with OpenAI's GPT-2 model.

          초급

          초급

          PyTorch, gpt-2, transformer

          <Building LLMs from Scratch> GitHub + Bonus Content Commentary강의 썸네일

          <Building LLMs from Scratch> GitHub + Bonus Content Commentary

          haesunpark

          First Time Creating Custom LLMs – LoRA & QLoRA Fine-tuning Introduction강의 썸네일

          First Time Creating Custom LLMs – LoRA & QLoRA Fine-tuning Introduction

          HappyAI

          "LoRA-based lightweight fine-tuning: Your first step to creating a customized LLM!" This course is an introductory hands-on lecture designed so that even those encountering LLMs for the first time can easily follow along. We minimize complex theory and guide you step-by-step through the entire process: loading models → applying data → training → comparing results. In a short time, you'll directly experience the flow of cutting-edge lightweight fine-tuning techniques like LoRA and QLoRA, gaining an intuitive understanding of "how LLM fine-tuning works." Even without extensive resources, experience the satisfaction of creating an LLM specialized for your domain!

          입문

          입문

          Deep Learning(DL), NLP, AI

          First Time Creating Custom LLMs – LoRA & QLoRA Fine-tuning Introduction강의 썸네일

          First Time Creating Custom LLMs – LoRA & QLoRA Fine-tuning Introduction

          HappyAI

          LLM Basics to Latest RAG·LangChain: Master LLM Fundamentals in Just 5 Hours!강의 썸네일

          LLM Basics to Latest RAG·LangChain: Master LLM Fundamentals in Just 5 Hours!

          HappyAI

          This is a course to master the core technologies of LLM basic theory, LangChain, and RAG. You can easily learn the latest AI technologies used in practice, from LLM basics!

          초급

          초급

          Chatbot, LLM, LangChain

          LLM Basics to Latest RAG·LangChain: Master LLM Fundamentals in Just 5 Hours!강의 썸네일

          LLM Basics to Latest RAG·LangChain: Master LLM Fundamentals in Just 5 Hours!

          HappyAI

          Create Your Own Web Service in Just One Day - VibeCoding Workshop강의 썸네일

          Create Your Own Web Service in Just One Day - VibeCoding Workshop

          selfishclub

          Now is truly an era where anyone can create their own service in just one day. While the previous Vibe Coding workshop focused on directly experiencing what Vibe Coding is all about and aimed for everyone to complete and deploy the front-end (visible pages) of the service they wanted to create, this workshop goes beyond simply creating a visible service. It places significant emphasis on a development approach that involves concretely imagining actual users and focusing on 'who will use this service and why.' Through the workshop, participants will naturally learn how to clearly define their target users and the problems to solve while creating their own services. It's perfectly fine if you're new to Vibe Coding! Even if you don't know coding or development, it's more than enough! Rather than simply following along, experience creating a truly usable service yourself in this workshop!

          입문

          입문

          replit, ChatGPT, Vibe Coding

          Create Your Own Web Service in Just One Day - VibeCoding Workshop강의 썸네일

          Create Your Own Web Service in Just One Day - VibeCoding Workshop

          selfishclub

          Looking at the birth and development process of artificial intelligence reveals the principles of AI.강의 썸네일

          Looking at the birth and development process of artificial intelligence reveals the principles of AI.

          aidercollege

          AI is not a technology that suddenly appeared. To properly see AI's present and future, you must understand 70 years of challenges and failures. 👉 "The moment you understand AI history, you can see both its principles and future together." Start right now!

          입문

          입문

          Machine Learning(ML), Deep Learning(DL), Reinforcement Learning(RL)

          Looking at the birth and development process of artificial intelligence reveals the principles of AI.강의 썸네일

          Looking at the birth and development process of artificial intelligence reveals the principles of AI.

          aidercollege

          How does artificial intelligence think and learn? Complete mastery of machine learning강의 썸네일

          How does artificial intelligence think and learn? Complete mastery of machine learning

          momo7777322031

          Conquer everything about world-changing AI in just 4 lectures! Lecture 1. The True Identity of Artificial Intelligence AI is not magic. It's a digital brain created by analyzing human 'intelligence' like a mathematical formula! We thoroughly dissect the core structure of seemingly smart artificial intelligence. Lecture 2. Algorithm, AI's Creative (?) Thinking Method How does a pondering AI find answers? Experience firsthand the strategies of AI that plays Go, finds routes, and predicts your search results. Lecture 3. AI Hardware, The Engine That Turns Imagination Into Reality! The chip inside your smartphone is the heart of AI. We dissect everything from CPU, GPU, TPU, to even those unknown names. Lecture 4. The Great Clash of Machine Learning and Deep Learning! What on earth does it mean for AI to 'learn'? From classic rule-based AI to the currently hot ChatGPT! We trace the evolution of learning.

          입문

          입문

          Machine Learning(ML), Deep Learning(DL), AI

          How does artificial intelligence think and learn? Complete mastery of machine learning강의 썸네일

          How does artificial intelligence think and learn? Complete mastery of machine learning

          momo7777322031

          Anyone Can Easily Learn Generative AI (Basics)강의 썸네일

          Anyone Can Easily Learn Generative AI (Basics)

          aitutorlab

          If you have a vague curiosity about generative AI but don't know where to start, this course is the perfect answer. It's structured to explain the core principles of AI technology clearly and concisely, allowing anyone to quickly grasp the essence. We'll go beyond simply knowing 'what it is' to deeply explore why it works that way and how to utilize it effectively. This course will serve as the most reliable starting point to help you confidently and proactively leverage technology in the rapidly changing AI era.

          입문

          입문

          ChatGPT, gemini, AI

          Anyone Can Easily Learn Generative AI (Basics)강의 썸네일

          Anyone Can Easily Learn Generative AI (Basics)

          aitutorlab