Gpt, Transformer, Pytorch, Multi Head Attention, Decoder.
count_parameters(model): return sum(p.numel() for p in model.parameters() if p.requires_grad) print(f"The model has {count_parameters(model):,} trainable parameters") To see the output, we will convert the log probabilities into probabilities, and convert the output tensor to numpy array. # Convert