close-mar11

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("Thang203/close-mar11")

topic_model.get_topic_info()

Topic overview

• Number of topics: 20
• Number of training documents: 4147

Click here for an overview of all topics.

Topic ID	Topic Keywords	Topic Frequency	Label
-1	models - language - llms - language models - chatgpt	11	-1_models_language_llms_language models
0	code - models - language - llms - language models	1366	0_code_models_language_llms
1	medical - clinical - models - llms - language	840	1_medical_clinical_models_llms
2	language - models - human - model - llms	310	2_language_models_human_model
3	bias - llms - language - models - biases	196	3_bias_llms_language_models
4	attacks - adversarial - attack - llms - security	188	4_attacks_adversarial_attack_llms
5	visual - image - multimodal - models - video	184	5_visual_image_multimodal_models
6	text - detection - chatgpt - models - content	175	6_text_detection_chatgpt_models
7	reasoning - language - models - mathematical - logical	173	7_reasoning_language_models_mathematical
8	students - chatgpt - education - learning - programming	119	8_students_chatgpt_education_learning
9	training - models - model - transformer - transformers	109	9_training_models_model_transformer
10	ai - chatgpt - ethical - concerns - research	106	10_ai_chatgpt_ethical_concerns
11	ai - design - creative - generative - ideas	84	11_ai_design_creative_generative
12	financial - sentiment - stock - market - investment	68	12_financial_sentiment_stock_market
13	spatial - urban - models - traffic - large	52	13_spatial_urban_models_traffic
14	materials - chemistry - drug - discovery - molecule	41	14_materials_chemistry_drug_discovery
15	legal - analysis - law - llms - lawyers	35	15_legal_analysis_law_llms
16	recommendation - recommender - recommender systems - systems - recommendations	35	16_recommendation_recommender_recommender systems_systems
17	game - agents - games - llms - playing	30	17_game_agents_games_llms
18	astronomy - scientific - knowledge - galactica - data	25	18_astronomy_scientific_knowledge_galactica

Training hyperparameters

• calculate_probabilities: False
• language: None
• low_memory: False
• min_topic_size: 10
• n_gram_range: (1, 1)
• nr_topics: 20
• seed_topic_list: None
• top_n_words: 10
• verbose: True
• zeroshot_min_similarity: 0.7
• zeroshot_topic_list: None

Framework versions

• Numpy: 1.25.2
• HDBSCAN: 0.8.33
• UMAP: 0.5.5
• Pandas: 1.5.3
• Scikit-Learn: 1.2.2
• Sentence-transformers: 2.6.1
• Transformers: 4.38.2
• Numba: 0.58.1
• Plotly: 5.15.0
• Python: 3.10.12