| { |
| "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" |
| } |