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karinegabsschon/
BERTopic_Environmental

Name: BERTopic_Environmental
Availability: InStock

bertopic

text-classification

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BERTopic_Environmental

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("karinegabsschon/BERTopic_Environmental")

topic_model.get_topic_info()

Topic overview

Number of topics: 26
Number of training documents: 905

Click here for an overview of all topics.

Topic ID	Topic Keywords	Topic Frequency	Label
-1	electric - car - cars - charging - vehicles	11	-1_electric_car_cars_charging
0	battery - batteries - lithium - catl - technology	213	0_battery_batteries_lithium_catl
1	byd - charging - dolphin - chinese - new	61	1_byd_charging_dolphin_chinese
2	charging - ev - chargers - ev charging - electric	58	2_charging_ev_chargers_ev charging
3	zero - government - uk - mandate - electric	57	3_zero_government_uk_mandate
4	electric - charging - points - france - car	49	4_electric_charging_points_france
5	battery - lithium - recycling - batteries - supply	48	5_battery_lithium_recycling_batteries
6	cars - combustion - study - electric - car	36	6_cars_combustion_study_electric
7	percent - cars - market - sales - vehicles	33	7_percent_cars_market_sales
8	fires - safety - battery - electric - cars	29	8_fires_safety_battery_electric
9	charging - electric - sweden - vehicles - circle	29	9_charging_electric_sweden_vehicles
10	tax - drivers - petrol - ev - rates	25	10_tax_drivers_petrol_ev
11	kia - car - model - electric - range	25	11_kia_car_model_electric
12	cent - car - petrol - evs - drivers	23	12_cent_car_petrol_evs
13	charging - stations - charging stations - charging points - points	23	13_charging_stations_charging stations_charging points
14	india - ev - green - mobility - electric	23	14_india_ev_green_mobility
15	indonesia - battery - lg - ev - ev battery	20	15_indonesia_battery_lg_ev
16	department - flames - police - car - tesla	20	16_department_flames_police_car
17	transport - ireland - council - ev - climate	19	17_transport_ireland_council_ev
18	toyota - electric - new - europe - hyundai	19	18_toyota_electric_new_europe
19	sales - new - electric - cent - car	17	19_sales_new_electric_cent
20	european - commission - eu - von - der	15	20_european_commission_eu_von
21	power - blackout - spain - homes - electricity	14	21_power_blackout_spain_homes
22	nissan - leaf - micra - new - generation	13	22_nissan_leaf_micra_new
23	ship - coast - vessel - coast guard - guard	13	23_ship_coast_vessel_coast guard
24	id - volkswagen - vw - every1 - id every1	12	24_id_volkswagen_vw_every1

Training hyperparameters

calculate_probabilities: False
language: None
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: 2.0.2
HDBSCAN: 0.8.40
UMAP: 0.5.8
Pandas: 2.2.2
Scikit-Learn: 1.6.1
Sentence-transformers: 4.1.0
Transformers: 4.53.0
Numba: 0.60.0
Plotly: 5.24.1
Python: 3.11.13