Build A Large Language Model From Scratch Pdf -

# Load data text_data = [...] vocab = {...}

# Main function def main(): # Set hyperparameters vocab_size = 10000 embedding_dim = 128 hidden_dim = 256 output_dim = vocab_size batch_size = 32 epochs = 10 build a large language model from scratch pdf

def __len__(self): return len(self.text_data) # Load data text_data = [

# Set device device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') criterion) print(f'Epoch {epoch+1}

# 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 simple language model class LanguageModel(nn.Module): def __init__(self, vocab_size, embedding_dim, hidden_dim, output_dim): super(LanguageModel, self).__init__() self.embedding = nn.Embedding(vocab_size, embedding_dim) self.rnn = nn.RNN(embedding_dim, hidden_dim, batch_first=True) self.fc = nn.Linear(hidden_dim, output_dim)

# 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