Build A Large Language Model From Scratch Pdf «OFFICIAL»
# Main function def main(): # Set hyperparameters vocab_size = 10000 embedding_dim = 128 hidden_dim = 256 output_dim = vocab_size batch_size = 32 epochs = 10
def __getitem__(self, idx): text = self.text_data[idx] input_seq = [] output_seq = [] for i in range(len(text) - 1): input_seq.append(self.vocab[text[i]]) output_seq.append(self.vocab[text[i + 1]]) return { 'input': torch.tensor(input_seq), 'output': torch.tensor(output_seq) } build a large language model from scratch pdf
if __name__ == '__main__': main()
# Train and evaluate model for epoch in range(epochs): loss = train(model, device, loader, optimizer, criterion) print(f'Epoch {epoch+1}, Loss: {loss:.4f}') eval_loss = evaluate(model, device, loader, criterion) print(f'Epoch {epoch+1}, Eval Loss: {eval_loss:.4f}') # Main function def main(): # Set hyperparameters
# Define a dataset class for our language model class LanguageModelDataset(Dataset): def __init__(self, text_data, vocab): self.text_data = text_data self.vocab = vocab criterion) print(f'Epoch {epoch+1}
# Create dataset and data loader dataset = LanguageModelDataset(text_data, vocab) loader = DataLoader(dataset, batch_size=batch_size, shuffle=True)
# Main function def main(): # Set hyperparameters vocab_size = 10000 embedding_dim = 128 hidden_dim = 256 output_dim = vocab_size batch_size = 32 epochs = 10
def __getitem__(self, idx): text = self.text_data[idx] input_seq = [] output_seq = [] for i in range(len(text) - 1): input_seq.append(self.vocab[text[i]]) output_seq.append(self.vocab[text[i + 1]]) return { 'input': torch.tensor(input_seq), 'output': torch.tensor(output_seq) }
if __name__ == '__main__': main()
# Train and evaluate model for epoch in range(epochs): loss = train(model, device, loader, optimizer, criterion) print(f'Epoch {epoch+1}, Loss: {loss:.4f}') eval_loss = evaluate(model, device, loader, criterion) print(f'Epoch {epoch+1}, Eval Loss: {eval_loss:.4f}')
# Define a dataset class for our language model class LanguageModelDataset(Dataset): def __init__(self, text_data, vocab): self.text_data = text_data self.vocab = vocab
# Create dataset and data loader dataset = LanguageModelDataset(text_data, vocab) loader = DataLoader(dataset, batch_size=batch_size, shuffle=True)
