---
tags:
- bertopic
library_name: bertopic
pipeline_tag: text-classification
---

# topic_model

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("KritiShahi/topic_model")

topic_model.get_topic_info()
```

## Topic overview

* Number of topics: 9
* Number of training documents: 597

<details>
  <summary>Click here for an overview of all topics.</summary>
  
  | Topic ID | Topic Keywords | Topic Frequency | Label | 
|----------|----------------|-----------------|-------| 
| -1 | echo - tap - speaker - alexa - amazon | 21 | Amazon Echo and Bluetooth Speakers | 
| 0 | gift - love - great - bought - product | 227 | Gift ideas for loved ones | 
| 1 | sound - great - speaker - music - good | 75 | Portable speakers | 
| 2 | im - ive - bud - apple - well | 67 | Headphone Reviews | 
| 3 | earbuds - magnet - design - ear - headphone | 60 | Earbuds and Noise Cancellation | 
| 4 | remote - fire - work - phone - protector | 44 | Remote troubleshooting and solutions | 
| 5 | headphone - work - like - earpods - around | 43 | Headphone Reviews | 
| 6 | alexa - speaker - great - tap - button | 31 | Portable Alexa Speakers | 
| 7 | bluetooth - connect - speaker - wifi - via | 29 | Portable Bluetooth Speakers |
  
</details>

## Training hyperparameters

* calculate_probabilities: False
* 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: 1.26.4
* HDBSCAN: 0.8.40
* UMAP: 0.5.7
* Pandas: 2.2.3
* Scikit-Learn: 1.6.1
* Sentence-transformers: 3.3.1
* Transformers: 4.48.0
* Numba: 0.60.0
* Plotly: 5.24.1
* Python: 3.9.1