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@@ -11,4 +11,64 @@ license: "apache-2.0"
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  ---
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  # Model Card
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- `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://colab.research.google.com/drive/1YRLxI92MdpUV0d-W5ToQfe3_J_9a4PF4?usp=sharing).
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # Model Card
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+ `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://colab.research.google.com/drive/1YRLxI92MdpUV0d-W5ToQfe3_J_9a4PF4?usp=sharing).
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+
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+ 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.
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+
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+ ```python
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+ display(interpreter.get_input_details())
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+ display(interpreter.get_output_details())
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+ ```
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+
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+ ```json
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+ [{'dtype': numpy.int32,
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+ 'index': 0,
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+ 'name': 'input_tokens',
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+ 'quantization': (0.0, 0),
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+ 'quantization_parameters': {'quantized_dimension': 0,
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+ 'scales': array([], dtype=float32),
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+ 'zero_points': array([], dtype=int32)},
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+ 'shape': array([32], dtype=int32),
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+ 'shape_signature': array([32], dtype=int32),
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+ 'sparsity_parameters': {}},
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+ {'dtype': numpy.int32,
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+ 'index': 1,
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+ 'name': 'decoder_input_tokens',
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+ 'quantization': (0.0, 0),
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+ 'quantization_parameters': {'quantized_dimension': 0,
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+ 'scales': array([], dtype=float32),
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+ 'zero_points': array([], dtype=int32)},
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+ 'shape': array([32], dtype=int32),
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+ 'shape_signature': array([32], dtype=int32),
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+ 'sparsity_parameters': {}},
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+ {'dtype': numpy.int32,
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+ 'index': 2,
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+ 'name': 'input_len',
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+ 'quantization': (0.0, 0),
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+ 'quantization_parameters': {'quantized_dimension': 0,
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+ 'scales': array([], dtype=float32),
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+ 'zero_points': array([], dtype=int32)},
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+ 'shape': array([], dtype=int32),
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+ 'shape_signature': array([], dtype=int32),
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+ 'sparsity_parameters': {}},
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+ {'dtype': numpy.int32,
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+ 'index': 3,
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+ 'name': 'decoder_input_len',
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+ 'quantization': (0.0, 0),
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+ 'quantization_parameters': {'quantized_dimension': 0,
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+ 'scales': array([], dtype=float32),
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+ 'zero_points': array([], dtype=int32)},
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+ 'shape': array([], dtype=int32),
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+ 'shape_signature': array([], dtype=int32),
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+ 'sparsity_parameters': {}}]
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+ [{'dtype': numpy.int32,
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+ 'index': 3112,
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+ 'name': 'Identity',
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+ 'quantization': (0.0, 0),
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+ 'quantization_parameters': {'quantized_dimension': 0,
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+ 'scales': array([], dtype=float32),
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+ 'zero_points': array([], dtype=int32)},
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+ 'shape': array([], dtype=int32),
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+ 'shape_signature': array([], dtype=int32),
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+ 'sparsity_parameters': {}}]
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+ ```