In this LLM course, learn the LLM fundamentals, fine-tuning, and evaluation, and explore its architecture and evolution. Discover GPT-2, compare models, and uncover use cases.

llm.tar.gz

gpt-2-demo

dataset-demo-1

jupy

gpt2-demo-2

dataset-demo-1-copy

gpt2-demo-2-copy

Matplotlib

MPLIB2

In this course, you will acquire a working knowledge of the capabilities and types of LLMs, along with their importance and limitations in various applications. You will gain valuable hands-on experience by fine-tuning LLMs to specific datasets and evaluating their performance. 

You will start with an introduction to large language models, looking at components, capabilities, and their types. Next, you will be introduced to GPT-2 as an example of a large language model. Then, you will learn how to fine-tune a selected LLM to a specific dataset, starting from model selection, data preparation, model training, and performance evaluation. You will also compare the performance of two different LLMs. 

By the end of this course, you will have gained practical experience in fine-tuning LLMs to specific datasets, building a comprehensive skill set for effectively leveraging these generative AI models in diverse language-related applications.

Essentials of Large Language Models: A Beginner’s Journey

def is_palindrome(s):
    # Remove spaces and convert to lowercase for consistency
    s = s.replace(" ", "").lower()
    
    # Check if the string is equal to its reverse
    return s == s[::-1]

# Hardcoded words
word1 = "racecar"
word2 = "hello"

# Check if each word is a palindrome
if is_palindrome(word1):
    print(f"'{word1}' is a palindrome!")
else:
    print(f"'{word1}' is not a palindrome.")

if is_palindrome(word2):
    print(f"'{word2}' is a palindrome!")
else:
    print(f"'{word2}' is not a palindrome.")


Python 3.10.4

<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Audio Player Bar</title>
    <link rel="stylesheet" href="styles.css">
</head>
<body>
    
    <audio id="audioPlayer" controls>
        <source src="/udata/kv8k1Y7L8Zr/generated_audio.mp3" type="audio/mp3">
        Your browser does not support the audio element.
    </audio>

    <script src="script.js"></script>
</body>
</html>

/* Basic styling to center the audio player */
body {
    display: flex;
    justify-content: center;
    align-items: center;
    height: 100vh;
    margin: 0;
    font-family: Arial, sans-serif;
    background-color: #f4f4f4;
}

/* Hide everything except the progress bar */
audio {
    width: 80%; /* Adjust width of the progress bar */
    -webkit-appearance: none;
    appearance: none;
    background-color: transparent;
    border: none;
}

/* Hide all default controls except the progress bar */
audio::-webkit-media-controls-panel {
    display: none !important;
}

audio::-webkit-media-controls-play-button,
audio::-webkit-media-controls-volume-slider,
audio::-webkit-media-controls-mute-button,
audio::-webkit-media-controls-current-time-display,
audio::-webkit-media-controls-duration-display,
audio::-webkit-media-controls-seek-backward-button,
audio::-webkit-media-controls-seek-forward-button {
    display: none !important;
}


codemirror

<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <title>Simulated LLM Demo</title>
  <link rel="stylesheet" href="styles.css">
</head>
<body>
  <div class="container">
    <h1>Simulated LLM Demo</h1>
    <div class="chatbox" id="chatbox"></div>
    <div class="input-area">
 <input type="text" id="user-input" placeholder="Ask me anything... like what is a LLM or how do LLMs work or tell me a joke " />
      <button id="send-button">Send</button>
    </div>
  </div>
  <script src="script.js"></script>
</body>
</html>


// Predefined responses to mimic an LLM
const responses = [
  { pattern: /hello/i, response: "Hi there! How can I assist you today?" },
  { 
    pattern: /what is (a|an|the)? (large language model|LLM)/i, 
    response: "A Large Language Model (LLM) is an advanced AI system trained on vast amounts of text to generate human-like responses." 
  },
  { 
    pattern: /how (do|does) large language models work/i, 
    response: "LLMs use neural networks to analyze input text and generate relevant and context-aware outputs." 
  },
  { pattern: /tell me a joke/i, response: "Why did the AI get promoted? It had a lot of neural network connections!" },
  { pattern: /.*/, response: "I'm not sure about that, but I can try to help with something else!" } // Default response
];

// DOM Elements
const chatbox = document.getElementById("chatbox");
const userInput = document.getElementById("user-input");
const sendButton = document.getElementById("send-button");

// Function to generate a response
function generateResponse(input) {
  for (const { pattern, response } of responses) {
    if (pattern.test(input)) {
      return response;
    }
  }
  return "Sorry, I didn't understand that.";
}

// Function to add a message to the chatbox
function addMessage(sender, message) {
  const messageElement = document.createElement("div");
  messageElement.className = sender; // Use class for styling
  messageElement.innerText = message;
  chatbox.appendChild(messageElement);
  chatbox.scrollTop = chatbox.scrollHeight; // Auto-scroll to the bottom
}

// Event Listener for the Send Button
sendButton.addEventListener("click", () => {
  const inputText = userInput.value.trim();
  if (inputText) {
    addMessage("user", `You: ${inputText}`);
    const response = generateResponse(inputText);
    addMessage("bot", `LLM: ${response}`);
    userInput.value = ""; // Clear input field
  }
});

// Allow pressing Enter to send messages
userInput.addEventListener("keypress", (event) => {
  if (event.key === "Enter") {
    sendButton.click();
  }
});


body {
  font-family: Arial, sans-serif;
  background-color: #f0f4f8;
  margin: 0;
  display: flex;
  justify-content: center;
  align-items: center;
  height: 100vh;
}

.container {
  width: 600px;
  background: white;
  padding: 20px;
  border-radius: 10px;
  box-shadow: 0 4px 8px rgba(0, 0, 0, 0.2);
}

h1 {
  text-align: center;
  margin-bottom: 20px;
  color: #333;
}

.chatbox {
  background: #f9f9f9;
  border: 1px solid #ddd;
  border-radius: 5px;
  height: 300px;
  overflow-y: auto;
  padding: 10px;
  margin-bottom: 15px;
}

.input-area {
  display: flex;
  gap: 10px;
}

#user-input {
  flex: 1;
  padding: 10px;
  font-size: 14px;
  border: 1px solid #ddd;
  border-radius: 5px;
}

#send-button {
  background: #28a745;
  color: white;
  border: none;
  padding: 10px 15px;
  font-size: 14px;
  border-radius: 5px;
  cursor: pointer;
}

#send-button:hover {
  background: #218838;
}

.user {
  text-align: right;
  color: #007bff;
  margin-bottom: 5px;
}

.bot {
  text-align: left;
  color: #555;
  margin-bottom: 5px;
}


Get an overview of what this course is about and its target audience.

Course Overview

Getting Started with LLMs

Fine-Tuning LLMs

Wrap Up

Exploring OpenAI API

Introduction to the Course