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

# 1m_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("Jellywibble/1m_topic_model")

topic_model.get_topic_info()
```

## Topic overview

* Number of topics: 15
* Number of training documents: 1000000

<details>
  <summary>Click here for an overview of all topics.</summary>
  
  | Topic ID | Topic Keywords | Topic Frequency | Label | 
|----------|----------------|-----------------|-------| 
| 0 | cock - cum - inside - pleasure - body | 208793 | 0_cock_cum_inside_pleasure | 
| 1 | eyes - dont - just - im - youre | 154818 | 1_eyes_dont_just_im | 
| 2 | kiss - lips - body - eyes - hands | 117610 | 2_kiss_lips_body_eyes | 
| 3 | just - im - eyes - like - dont | 115264 | 3_just_im_eyes_like | 
| 4 | eyes - youre - just - im - dont | 113788 | 4_eyes_youre_just_im | 
| 5 | eyes - sleep - just - softly - heart | 91136 | 5_eyes_sleep_just_softly | 
| 6 | sorry - eyes - ghost - body - youre | 56038 | 6_sorry_eyes_ghost_body | 
| 7 | eyes - body - satoru - cock - toji | 38594 | 7_eyes_body_satoru_cock | 
| 8 | kai - jungkook - eyes - kais - body | 30259 | 8_kai_jungkook_eyes_kais | 
| 9 | hoshi - food - eyes - eat - just | 29696 | 9_hoshi_food_eyes_eat | 
| 10 | leo - felix - leos - choso - eyes | 21878 | 10_leo_felix_leos_choso | 
| 11 | que - la - se - en - su | 10551 | 11_que_la_se_en | 
| 12 | eyes - youre - just - body - voice | 6977 | 12_eyes_youre_just_body | 
| 13 | xavier - xaviers - eyes - hand - lips | 2338 | 13_xavier_xaviers_eyes_hand | 
| 14 | bakugo - bakugou - bakugos - bakugous - deku | 2260 | 14_bakugo_bakugou_bakugos_bakugous |
  
</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: 1.23.1
* HDBSCAN: 0.8.33
* UMAP: 0.5.5
* Pandas: 1.3.5
* Scikit-Learn: 1.3.2
* Sentence-transformers: 2.3.1
* Transformers: 4.38.1
* Numba: 0.58.1
* Plotly: 5.19.0
* Python: 3.8.10