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---
tags:
- bertopic
library_name: bertopic
pipeline_tag: text-classification
---
# cnn_dailymail_123_3000_1500_test
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("KingKazma/cnn_dailymail_123_3000_1500_test")
topic_model.get_topic_info()
```
## Topic overview
* Number of topics: 12
* Number of training documents: 1500
<details>
<summary>Click here for an overview of all topics.</summary>
| Topic ID | Topic Keywords | Topic Frequency | Label |
|----------|----------------|-----------------|-------|
| -1 | league - season - klopp - game - club | 13 | -1_league_season_klopp_game |
| 0 | said - one - year - also - people | 73 | 0_said_one_year_also |
| 1 | liverpool - player - club - sterling - league | 1088 | 1_liverpool_player_club_sterling |
| 2 | league - goal - madrid - barcelona - champions | 91 | 2_league_goal_madrid_barcelona |
| 3 | manchester - united - city - van - gaal | 51 | 3_manchester_united_city_van |
| 4 | world - first - woods - hamilton - win | 38 | 4_world_first_woods_hamilton |
| 5 | england - cricket - test - captain - pietersen | 35 | 5_england_cricket_test_captain |
| 6 | celtic - game - inverness - rangers - player | 31 | 6_celtic_game_inverness_rangers |
| 7 | mayweather - fight - pacquiao - vegas - las | 28 | 7_mayweather_fight_pacquiao_vegas |
| 8 | mccoy - national - lady - ride - race | 23 | 8_mccoy_national_lady_ride |
| 9 | clermont - saracens - cup - england - northampton | 16 | 9_clermont_saracens_cup_england |
| 10 | chelsea - mourinho - stoke - league - game | 13 | 10_chelsea_mourinho_stoke_league |
</details>
## Training hyperparameters
* calculate_probabilities: True
* 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
## Framework versions
* Numpy: 1.22.4
* HDBSCAN: 0.8.33
* UMAP: 0.5.3
* Pandas: 1.5.3
* Scikit-Learn: 1.2.2
* Sentence-transformers: 2.2.2
* Transformers: 4.31.0
* Numba: 0.56.4
* Plotly: 5.13.1
* Python: 3.10.6
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