Loaded Model wont .fit or fit and transform

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Hello Maarten, I loved getting to learn BERTopic for a recent project, I got my model to work properly, and using this code

embedding_model = "sentence-transformers/all-MiniLM-L6-v2"
stored_models_path = "./Stored_Models/"
model.save(stored_models_path, serialization="pytorch", save_ctfidf=True, save_embedding_model=embedding_model)

I saved it however when I run

topics, probability = loaded_model.fit(doc2)
or just loaded_model.fit(doc2)

I get this erorr

ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (2,) + inhomogeneous part.

Do you know what I could be doing wrong? when I run the loaded_model cell I get a value of

so I think it saved properly. (I have also tried the pickling method with no luck)

Reproduce the failure using the shown model.save call, a reload into loaded_model, and loaded_model.fit(doc2). Start at the BERTopic save/load and fit entry points; done means a saved and reloaded model can fit doc2 without the reported array-shape error, with the expected return values.

Written by the indexing model from the issue text.