Random Code GPT from Scratch Book

 Looking at the code from Sebastian Raschka on LLMs, here is a small snippet.  Training a model from scratch and basic test.  The key is understanding the basics.

Here is the text to train,

"I HAD always thought Jack Gisburn rather a cheap genius--though a good fellow enough--so it was no great surprise to me to hear that, in the height of his glory, he had dropped his painting, married a rich widow, and established himself in a villa on the Riviera. (Though I rather thought it would have been Rome or Florence.)"





See:

https://pytorch.org/
https://github.com/openai/tiktoken

import matplotlib.pyplot as plt
import os
import torch
import urllib.request
import tiktoken
 
class GPTDatasetV1(Dataset):
    def __init__(self, txt, tokenizer, max_length, stride):
        self.input_ids = []
        self.target_ids = []
        # Tokenize the entire text
        token_ids = tokenizer.encode(txt, allowed_special={"<|endoftext|>"})
        # Use a sliding window to chunk the book into overlapping sequences of max_length
        for i in range(0, len(token_ids) - max_length, stride):
            input_chunk = token_ids[i:i + max_length]
            target_chunk = token_ids[i + 1: i + max_length + 1]
            self.input_ids.append(torch.tensor(input_chunk))
            self.target_ids.append(torch.tensor(target_chunk))
    def __len__(self):
        return len(self.input_ids)
    def __getitem__(self, idx):
        return self.input_ids[idx], self.target_ids[idx]

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