By default, the tokenizer creates an attention_mask for you based on your specific tokenizer's defaults.

attention_mask = torch.tensor([[1, 1, 1, 1, 1, 1], [1, 0, 0, 0, 0, 0]])
output = model(input_ids, attention_mask=attention_mask)
print(output.logits)
tensor([[ 0.0082, -0.2307],
        [-0.1008, -0.4061]], grad_fn=)

🤗 Transformers doesn't automatically create an attention_mask to mask a padding token if it is provided because: