BERTopic-gemini-summary

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("nataliecastro/BERTopic-gemini-summary")

topic_model.get_topic_info()

Topic overview

  • Number of topics: 37
  • Number of training documents: 3500
Click here for an overview of all topics.
Topic ID Topic Keywords Topic Frequency Label
-1 the - and - to - of - for 13 -1_the_and_to_of
0 the - to - of - that - budget 1043 0_the_to_of_that
1 the - to - and - of - that 625 1_the_to_and_of
2 thompson - the - school - and - of 432 2_thompson_the_school_and
3 westminster - swanson - the - of - dr 125 3_westminster_swanson_the_of
4 students - and - college - to - the 118 4_students_and_college_to
5 and - the - you - to - of 114 5_and_the_you_to
6 math - the - data - in - performance 95 6_math_the_data_in
7 anderson - the - boulder - and - of 80 7_anderson_the_boulder_and
8 board - the - that - policy - to 72 8_board_the_that_policy
9 the - and - program - to - of 59 9_the_and_program_to
10 bilingual - language - the - and - of 53 10_bilingual_language_the_and
11 the - and - salary - to - of 49 11_the_and_salary_to
12 the - board - of - and - greeley 45 12_the_board_of_and
13 sros - sro - of - to - and 42 13_sros_sro_of_to
14 technology - policy - use - to - privacy 40 14_technology_policy_use_to
15 and - schools - the - principal - school 39 15_and_schools_the_principal
16 that - we - the - and - to 37 16_that_we_the_and
17 audit - financial - the - statements - of 33 17_audit_financial_the_statements
18 athletic - coach - the - and - team 33 18_athletic_coach_the_and
19 security - safety - and - of - the 31 19_security_safety_and_of
20 technology - devices - to - the - of 31 20_technology_devices_to_the
21 transgender - lgbtq - and - of - gender 29 21_transgender_lgbtq_and_of
22 sustainability - energy - waste - air - and 26 22_sustainability_energy_waste_air
23 sel - and - students - the - mental 25 23_sel_and_students_the
24 dyslexia - screener - reading - the - with 24 24_dyslexia_screener_reading_the
25 bullying - and - to - the - of 20 25_bullying_and_to_the
26 greeley - the - scholarship - school - of 20 26_greeley_the_scholarship_school
27 calendar - the - days - break - for 20 27_calendar_the_days_break
28 start - school - time - day - to 18 28_start_school_time_day
29 color - of - diversity - and - the 17 29_color_of_diversity_and
30 and - speaker - the - to - that 17 30_and_speaker_the_to
31 volunteers - the - and - of - their 16 31_volunteers_the_and_of
32 enrollment - growth - in - housing - the 16 32_enrollment_growth_in_housing
33 ix - title - complaint - harassment - sexual 15 33_ix_title_complaint_harassment
34 marijuana - policy - medical - to - the 14 34_marijuana_policy_medical_to
35 pilch - dr - the - board - to 14 35_pilch_dr_the_board

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: True
  • zeroshot_min_similarity: 0.7
  • zeroshot_topic_list: None

Framework versions

  • Numpy: 1.24.3
  • HDBSCAN: 0.8.29
  • UMAP: 0.5.6
  • Pandas: 1.5.3
  • Scikit-Learn: 1.2.2
  • Sentence-transformers: 3.1.0
  • Transformers: 4.44.2
  • Numba: 0.57.0
  • Plotly: 5.9.0
  • Python: 3.10.12
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