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license: mit
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---
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---
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license: mit
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language:
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- en
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library_name: bertopic
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tags:
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- topic-modeling
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- nlp
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- amazon-reviews
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- clustering
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# Amazon Fine Food Reviews - BERTopic Model
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## Model Description
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This is a **Topic Modeling** model built using the [BERTopic](https://maartengr.github.io/BERTopic/) library. It was trained on the **Amazon Fine Food Reviews** dataset to automatically extract and cluster the main topics and aspects discussed by customers in their reviews.
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This model is part of an academic Web Mining project developed at EMSI Marrakech.
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### Intended Uses & Limitations
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- **Intended Use:** Automatically extracting topics from English food product reviews (e.g., Taste & Flavor, Packaging, Delivery, Specific foods like Coffee or Tea).
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- **Language:** English
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- **Limitation:** The model is optimized for food-related e-commerce reviews and may not perform well on general text or other domains.
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### How to use
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You can load this model directly in Python using the BERTopic library:
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```python
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from bertopic import BERTopic
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# Load the model from Hugging Face
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topic_model = BERTopic.load("aablaess/amazon-bertopic")
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# Predict topics for new reviews
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docs = ["The coffee tastes great but the packaging was damaged.", "My dog absolutely loves this food!"]
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topics, probs = topic_model.transform(docs)
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