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

# BERTopic_andattakstruk_1

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("GiganticLemon/BERTopic_andattakstruk_1")

topic_model.get_topic_info()
```

## Topic overview

* Number of topics: 10
* Number of training documents: 16559

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

  | Topic ID | Topic Keywords | Topic Frequency | Label | 
|----------|----------------|-----------------|-------| 
| -1 | the - and - to - of - in | 329 | -1_the_and_to_of | 
| 0 | her - and - to - the - she | 8589 | 0_her_and_to_the | 
| 1 | the - to - and - of - is | 1950 | 1_the_to_and_of | 
| 2 | the - of - to - and - in | 1740 | 2_the_of_to_and | 
| 3 | the - to - and - of - in | 1283 | 3_the_to_and_of | 
| 4 | the - and - to - of - he | 645 | 4_the_and_to_of | 
| 5 | the - of - to - and - in | 564 | 5_the_of_to_and | 
| 6 | the - to - and - of - his | 527 | 6_the_to_and_of | 
| 7 | the - and - to - of - in | 482 | 7_the_and_to_of | 
| 8 | the - and - to - of - is | 450 | 8_the_and_to_of |

</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: True
* zeroshot_min_similarity: 0.7
* zeroshot_topic_list: None

## Framework versions

* Numpy: 2.0.2
* HDBSCAN: 0.8.40
* UMAP: 0.5.7
* Pandas: 2.2.2
* Scikit-Learn: 1.6.1
* Sentence-transformers: 3.4.1
* Transformers: 4.51.3
* Numba: 0.60.0
* Plotly: 5.24.1
* Python: 3.11.12