readme: ---
  language: "en"
  #thumbnail: "url to a thumbnail used in social sharing"
  tags:
  - Android
  - tflite
  - blenderbot
  license: "apache-2.0"
  #datasets:
  #metrics:
  ---
  # Model Card
  
  `blenderbot-small-tflite` is a tflite version of `blenderbot-small-90M` I converted for my UTA CSE3310 class. See the repo at [https://github.com/kmosoti/DesparadosAEYE](https://github.com/kmosoti/DesparadosAEYE) and the conversion process [here](https://drive.google.com/file/d/1F93nMsDIm1TWhn70FcLtcaKQUynHq9wS/view?usp=sharing).
  
  You have to right pad your user and model input integers to make them [32,]-shaped. Then indicate te true length with the 3rd and 4th params.
  
  ```python
  display(interpreter.get_input_details())
  display(interpreter.get_output_details())
  ```
  
  ```json
  [{'dtype': numpy.int32,
    'index': 0,
    'name': 'input_tokens',
    'quantization': (0.0, 0),
    'quantization_parameters': {'quantized_dimension': 0,
     'scales': array([], dtype=float32),
     'zero_points': array([], dtype=int32)},
    'shape': array([32], dtype=int32),
    'shape_signature': array([32], dtype=int32),
    'sparsity_parameters': {}},
   {'dtype': numpy.int32,
    'index': 1,
    'name': 'decoder_input_tokens',
    'quantization': (0.0, 0),
    'quantization_parameters': {'quantized_dimension': 0,
     'scales': array([], dtype=float32),
     'zero_points': array([], dtype=int32)},
    'shape': array([32], dtype=int32),
    'shape_signature': array([32], dtype=int32),
    'sparsity_parameters': {}},
   {'dtype': numpy.int32,
    'index': 2,
    'name': 'input_len',
    'quantization': (0.0, 0),
    'quantization_parameters': {'quantized_dimension': 0,
     'scales': array([], dtype=float32),
     'zero_points': array([], dtype=int32)},
    'shape': array([], dtype=int32),
    'shape_signature': array([], dtype=int32),
    'sparsity_parameters': {}},
   {'dtype': numpy.int32,
    'index': 3,
    'name': 'decoder_input_len',
    'quantization': (0.0, 0),
    'quantization_parameters': {'quantized_dimension': 0,
     'scales': array([], dtype=float32),
     'zero_points': array([], dtype=int32)},
    'shape': array([], dtype=int32),
    'shape_signature': array([], dtype=int32),
    'sparsity_parameters': {}}]
  [{'dtype': numpy.int32,
    'index': 3113,
    'name': 'Identity',
    'quantization': (0.0, 0),
    'quantization_parameters': {'quantized_dimension': 0,
     'scales': array([], dtype=float32),
     'zero_points': array([], dtype=int32)},
    'shape': array([1], dtype=int32),
    'shape_signature': array([1], dtype=int32),
    'sparsity_parameters': {}}]
  ```