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