blob: 79b63a4099abca10edf468e2c953906e3c51a092 [file] [log] [blame]
{
"name": "Sentiment Analyzer (AverageWordVecModelSpec)",
"description": "Detect if the input text's sentiment is positive or negative. The model was trained on the IMDB Movie Reviews dataset so it is more accurate when input text is a movie review.",
"version": "v1",
"subgraph_metadata": [
{
"input_tensor_metadata": [
{
"name": "input_text",
"description": "Embedding vectors representing the input text to be classified. The input need to be converted from raw text to embedding vectors using the attached dictionary file.",
"content": {
"content_properties_type": "FeatureProperties",
"content_properties": {
}
},
"process_units": [
{
"options_type": "RegexTokenizerOptions",
"options": {
"delim_regex_pattern": "[^\\w\\']+",
"vocab_file": [
{
"name": "vocab.txt",
"description": "Vocabulary file to convert natural language words to embedding vectors.",
"type": "VOCABULARY"
}
]
}
}
]
}
],
"output_tensor_metadata": [
{
"name": "probability",
"description": "Probabilities of the labels respectively.",
"content": {
"content_properties_type": "FeatureProperties",
"content_properties": {
}
},
"stats": {
"max": [
1.0
],
"min": [
0.0
]
},
"associated_files": [
{
"name": "labels.txt",
"description": "Labels for the categories that the model can classify.",
"type": "TENSOR_AXIS_LABELS"
}
]
}
]
}
],
"author": "TensorFlow",
"license": "Apache License. Version 2.0 http://www.apache.org/licenses/LICENSE-2.0.",
"min_parser_version": "1.2.1"
}