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

# MARTINI_enrich_BERTopic_shadowman2020

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("AIDA-UPM/MARTINI_enrich_BERTopic_shadowman2020")

topic_model.get_topic_info()
```

## Topic overview

* Number of topics: 8
* Number of training documents: 656

<details>
  <summary>Click here for an overview of all topics.</summary>
  
  | Topic ID | Topic Keywords | Topic Frequency | Label | 
|----------|----------------|-----------------|-------| 
| -1 | antifa - britain - veterans - boris - invasion | 27 | -1_antifa_britain_veterans_boris | 
| 0 | coronavirus - pandemic - pfizer - nhs - masks | 274 | 0_coronavirus_pandemic_pfizer_nhs | 
| 1 | protesters - palestine - barricades - dublin - stabbed | 103 | 1_protesters_palestine_barricades_dublin | 
| 2 | illegals - migrant - britain - dover - invaded | 71 | 2_illegals_migrant_britain_dover | 
| 3 | biden - votes - recount - michigan - republicans | 60 | 3_biden_votes_recount_michigan | 
| 4 | syria - airstrikes - mercenaries - karabakh - pentagon | 44 | 4_syria_airstrikes_mercenaries_karabakh | 
| 5 | london - veterans - poppies - cenotaph - doherty | 39 | 5_london_veterans_poppies_cenotaph | 
| 6 | telegram - patrioticcrusader - youtube - subscribed - banned | 38 | 6_telegram_patrioticcrusader_youtube_subscribed |
  
</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: False
* 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: 1.5.2
* Sentence-transformers: 3.3.1
* Transformers: 4.46.3
* Numba: 0.60.0
* Plotly: 5.24.1
* Python: 3.10.12