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Add BERTopic model
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---
tags:
- bertopic
library_name: bertopic
pipeline_tag: text-classification
---
# TopicModel_StoreReviews
This is a [BERTopic](https://github.com/MaartenGr/BERTopic) model.
BERTopic is a flexible and modular topic modeling framework that allows for the generation of easily interpretable topics from large datasets.
## Usage
To use this model, please install BERTopic:
```
pip install -U bertopic
```
You can use the model as follows:
```python
from bertopic import BERTopic
topic_model = BERTopic.load("shantanudave/TopicModel_StoreReviews")
topic_model.get_topic_info()
```
## Topic overview
* Number of topics: 10
* Number of training documents: 14747
<details>
<summary>Click here for an overview of all topics.</summary>
| Topic ID | Topic Keywords | Topic Frequency | Label |
|----------|----------------|-----------------|-------|
| 0 | clothing - clothes - fashion - clothe - clothing store | 2672 | Fashionable Clothing Selection |
| 1 | shopping - shop - price - cheap - store | 1864 | Diverse Shopping Experiences |
| 2 | tidy - clean - branch - range - renovation | 1807 | Clean Retail Space |
| 3 | quality - offer - use - stop - good | 1793 | Quality Offer Search |
| 4 | selection - choice - large - large selection - size | 1459 | Large Size Selection |
| 5 | advice - saleswoman - service - friendly - competent | 1447 | Friendly Saleswoman Service |
| 6 | staff - friendly staff - staff staff - staff friendly - friendly | 1177 | Friendly Staff Selection |
| 7 | wow - waw - oh - yeah - | 1108 | Expressive Words Discovery |
| 8 | voucher - money - return - exchange - cash | 933 | Customer Return Experience |
| 9 | super - friendly super - super friendly - pleasure - super service | 487 | super friendly service |
</details>
## Training hyperparameters
* calculate_probabilities: True
* language: None
* low_memory: False
* min_topic_size: 10
* n_gram_range: (1, 1)
* nr_topics: None
* seed_topic_list: None
* top_n_words: 10
* verbose: True
* zeroshot_min_similarity: 0.7
* zeroshot_topic_list: None
## Framework versions
* Numpy: 1.23.5
* HDBSCAN: 0.8.33
* UMAP: 0.5.5
* Pandas: 1.3.5
* Scikit-Learn: 1.4.1.post1
* Sentence-transformers: 2.6.1
* Transformers: 4.39.3
* Numba: 0.59.1
* Plotly: 5.21.0
* Python: 3.10.13