BERTopic
This is a 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:
from bertopic import BERTopic
topic_model = BERTopic.load("Jerado/BERTopic")
topic_model.get_topic_info()
Topic overview
- Number of topics: 17
- Number of training documents: 1000
Click here for an overview of all topics.
Topic ID | Topic Keywords | Topic Frequency | Label |
---|---|---|---|
-1 | theism - much - way - think - just | 15 | -1_theism_much_way_think |
0 | nhl - playoffs - rangers - hockey - league | 304 | 0_nhl_playoffs_rangers_hockey |
1 | performance - ram - drivers - monitor - speed | 92 | 1_performance_ram_drivers_monitor |
2 | x11r5 - hyperhelp - windows - pc - application | 82 | 2_x11r5_hyperhelp_windows_pc |
3 | dos - windows - harddisk - disk - software | 82 | 3_dos_windows_harddisk_disk |
4 | amp - amps - amplifier - ampere - current | 75 | 4_amp_amps_amplifier_ampere |
5 | scripture - christians - sin - bible - commandment | 44 | 5_scripture_christians_sin_bible |
6 | patients - biological - medicine - studies - doctors | 41 | 6_patients_biological_medicine_studies |
7 | nasa - solar - space - shuttle - orbiting | 39 | 7_nasa_solar_space_shuttle |
8 | armenians - armenian - armenia - turks - genocide | 38 | 8_armenians_armenian_armenia_turks |
9 | guns - gun - amendment - constitution - laws | 36 | 9_guns_gun_amendment_constitution |
10 | - - - - | 33 | 10____ |
11 | motorcycle - bikes - cobralinks - bike - riding | 32 | 11_motorcycle_bikes_cobralinks_bike |
12 | encryption - security - encrypted - privacy - secure | 24 | 12_encryption_security_encrypted_privacy |
13 | contacted - address - mail - contact - email | 23 | 13_contacted_address_mail_contact |
14 | paganism - faith - christianity - christians - atheists | 21 | 14_paganism_faith_christianity_christians |
15 | action - fbi - batf - war - president | 19 | 15_action_fbi_batf_war |
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: [['drug', 'cancer', 'drugs', 'doctor'], ['windows', 'drive', 'dos', 'file'], ['space', 'launch', 'orbit', 'lunar']]
- top_n_words: 10
- verbose: False
- zeroshot_min_similarity: 0.7
- zeroshot_topic_list: None
Framework versions
- Numpy: 1.23.5
- HDBSCAN: 0.8.33
- UMAP: 0.5.6
- Pandas: 2.0.3
- Scikit-Learn: 1.2.2
- Sentence-transformers: 2.7.0
- Transformers: 4.40.1
- Numba: 0.58.1
- Plotly: 5.15.0
- Python: 3.10.12
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