Model: distilbert-base-uncased-finetuned-sst-2-english, ONNX export, 267 MB
ONNX Runtime 1.31.0

Inputs of the ONNX graph:
  input_ids TensorInfo(javaType=INT64,onnxType=ONNX_TENSOR_ELEMENT_DATA_TYPE_INT64,shape=[-1, -1],dimNames=[batch_size,sequence_length])
  attention_mask TensorInfo(javaType=INT64,onnxType=ONNX_TENSOR_ELEMENT_DATA_TYPE_INT64,shape=[-1, -1],dimNames=[batch_size,sequence_length])
Outputs:
  logits TensorInfo(javaType=FLOAT,onnxType=ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT,shape=[-1, 2],dimNames=[batch_size,""])

Tokenizing "I loved this film.":
  tokens:         [[CLS], i, loved, this, film, ., [SEP]]
  input_ids:      [101, 1045, 3866, 2023, 2143, 1012, 102]
  attention_mask: [1, 1, 1, 1, 1, 1, 1]

Two texts in one batch are padded to the same length:
  [[CLS], i, loved, this, film, ., [SEP]]
    mask [1, 1, 1, 1, 1, 1, 1]
  [[CLS], bad, ., [SEP], [PAD], [PAD], [PAD]]
    mask [1, 1, 1, 1, 0, 0, 0]