@amn41 Hi, My question is linked to how to use tensor flow ranking with preloaded word vectors from spaCy. pipeline: - name: "tokenizer_whitespace" - name: "intent_entity_featurizer_regex" - name: "ner_crf" - name: "ner_synonyms" - name: "intent_featurizer_spacy" - name: "intent_classifier_tensorflow_embedding" intent_tokenization_flag: true intent_split_symbol: "+" - name: "ner_duckling_http" url: "http://0.0.0.0:8000" locale: "NL_Nothing" Will this pipeline works, I understand that tensor flow requires text features and hence instead of using the count vector featurizer , I replaced it with spacY’s that pre-loads the vectors. Does this makes sense?

Pre-load vectors for Tensorflow ranking classifier pipeline

parthsharma1996 (Parth Sharma) September 1, 2018, 9:28am 5

I was looking this exact thing. Has someone figured out a standard way of doing this that works? It would be extremely helpful to us since our data set is quite small

Pre-Trained vectors for tensorflow pipeline

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Pre-load vectors for Tensorflow ranking classifier pipeline

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