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---

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


# BERTopic

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("zsozsi12/BERTopic")



topic_model.get_topic_info()

```

## Topic overview

* Number of topics: 14
* Number of training documents: 1152

<details>
  <summary>Click here for an overview of all topics.</summary>

  | Topic ID | Topic Keywords | Topic Frequency | Label | 
|----------|----------------|-----------------|-------| 
| -1 | az - is - de - nem - nagyon | 12 | -1_az_is_de_nem | 
| 0 | az - nem - nekem - is - de | 394 | 0_az_nem_nekem_is | 
| 1 | netflix - az - hogy - egy - nem | 147 | 1_netflix_az_hogy_egy | 
| 2 | the - you - stranger - things - breaking | 115 | 2_the_you_stranger_things | 
| 3 | hogy - az - is - nem - egy | 105 | 3_hogy_az_is_nem | 
| 4 | film - az - de - nem - egy | 61 | 4_film_az_de_nem | 
| 5 | disney - spotify - youtube - netflix - hbo | 61 | 5_disney_spotify_youtube_netflix | 
| 6 | hogy - egy - nem - vagy - de | 60 | 6_hogy_egy_nem_vagy | 
| 7 | hogy - nem - netflix - is - az | 55 | 7_hogy_nem_netflix_is | 
| 8 | valaki - nem - mg - meg - sem | 41 | 8_valaki_nem_mg_meg | 
| 9 | teljesen - nem - teljes - az - ha | 36 | 9_teljesen_nem_teljes_az | 
| 10 | nagyon - szerintem - volt - sorozat - annyira | 28 | 10_nagyon_szerintem_volt_sorozat | 
| 11 | mint - olyan - normlis - knyv - forint | 25 | 11_mint_olyan_normlis_knyv | 
| 12 | tv - van - apple - nem - fhd | 12 | 12_tv_van_apple_nem |

</details>

## Training hyperparameters

* calculate_probabilities: False

* language: english

* low_memory: False
* min_topic_size: 10
* n_gram_range: (1, 1)
* nr_topics: None

* seed_topic_list: None

* top_n_words: 10

* verbose: False

* zeroshot_min_similarity: 0.7

* zeroshot_topic_list: None



## Framework versions



* Numpy: 1.26.4

* HDBSCAN: 0.8.40

* UMAP: 0.5.9.post2

* Pandas: 2.2.3

* Scikit-Learn: 1.7.1

* Sentence-transformers: 5.1.0

* Transformers: 4.56.1

* Numba: 0.61.2

* Plotly: 5.22.0

* Python: 3.12.2