You can deploy this model and start earning money today!

nataliecastro/
BERTopic-gemini-summary

Name: BERTopic-gemini-summary
Availability: InStock

bertopic

text-classification

Views

No views yet

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:

python

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