bertopic_model_v1

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("ivanleomk/bertopic_model_v1")

topic_model.get_topic_info()

Topic overview

• Number of topics: 25
• Number of training documents: 1358

Click here for an overview of all topics.

Topic ID	Topic Keywords	Topic Frequency	Label
-1	events - invites - national - volunteer - week	12	-1_events_invites_national_volunteer
0	gworks - software - hub - the - and	34	0_gworks_software_hub_the
1	upflow - upflows - can - how - and	226	1_upflow_upflows_can_how
2	banking - compliance - are - what - unit	188	2_banking_compliance_are_what
3	canal - canals - for - what - shop	142	3_canal_canals_for_what
4	pricing - roi - details - upflows - of	135	4_pricing_roi_details_upflows
5	sama - task - delivery - annotation - quality	77	5_sama_task_delivery_annotation
6	collection - cash - processes - ar - collections	68	6_collection_cash_processes_ar
7	case - studies - we - have - do	46	7_case_studies_we_have
8	naro - naros - platform - answers - docebo	40	8_naro_naros_platform_answers
9	invoices - invoice - invoicing - upflow - handling	40	9_invoices_invoice_invoicing_upflow
10	recipient - renewal - the - sender - agreement	39	10_recipient_renewal_the_sender
11	payment - upflows - gateway - features - upflow	39	11_payment_upflows_gateway_features
12	builder - tool - audience - presentation - the	37	12_builder_tool_audience_presentation
13	where - found - be - deck - promised	34	13_where_found_be_deck
14	stripe - express - hubspot - billing - payment	30	14_stripe_express_hubspot_billing
15	retention - unit - ottimate - increase - customer	28	15_retention_unit_ottimate_increase
16	netsuite - with - upflow - integration - synchronization	24	16_netsuite_with_upflow_integration
17	email - inbox - ar - success - up	23	17_email_inbox_ar_success
18	chargebee - with - upflow - synchronized - integration	20	18_chargebee_with_upflow_synchronized
19	budget - allocation - iq - plate - ppl	17	19_budget_allocation_iq_plate
20	receivable - accounts - jjjworks - upflow - resources	16	20_receivable_accounts_jjjworks_upflow
21	card - cards - status - program - the	15	21_card_cards_status_program
22	project - projects - growth - roadmap - create	14	22_project_projects_growth_roadmap
23	nps - docebo - employee - scores - improving	14	23_nps_docebo_employee_scores

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: None
• top_n_words: 10
• verbose: False
• zeroshot_min_similarity: 0.7
• zeroshot_topic_list: None

Framework versions

• Numpy: 1.26.4
• HDBSCAN: 0.8.37
• UMAP: 0.5.6
• Pandas: 2.2.2
• Scikit-Learn: 1.5.0
• Sentence-transformers: 3.0.1
• Transformers: 4.41.2
• Numba: 0.60.0
• Plotly: 5.22.0
• Python: 3.12.3