AttributeError: 'CountVectorizer' object has no attribute 'get_feature_names'

Nobody has claimed this yet.

Trying to run this code on Google Colab and seeing this error now. Simply just trying to use the demo provided in this repo, but now it's throwing the following error:

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AttributeError Traceback (most recent call last)
[](https://localhost:8080/#) in
3 # Fit the Concept model to the images and vocabulary
4 concept_model = ConceptModel()
----> 5 concepts = concept_model.fit_transform(img_names, docs=selected_nouns)
6
7 # Get the predicted probabilities for each concept cluster for each image

1 frames
[/usr/local/lib/python3.9/dist-packages/concept/_model.py](https://localhost:8080/#) in _extract_textual_representation(self, docs)
400 # Extract vocabulary from the documents
401 self.vectorizer_model.fit(docs)
--> 402 words = self.vectorizer_model.get_feature_names()
403
404 # Embed the documents and extract similarity between concept clusters and words

AttributeError: 'CountVectorizer' object has no attribute 'get_feature_names'

Start with the _extract_textual_representation method shown at line 402 of concept/_model.py, where the demo fails while fitting CountVectorizer. Check the current scikit-learn CountVectorizer API and run the repository's demo in Google Colab; done means the demo completes without this AttributeError.

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