MARTINI_enrich_BERTopic_alertamagnetica

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("AIDA-UPM/MARTINI_enrich_BERTopic_alertamagnetica")

topic_model.get_topic_info()

Topic overview

• Number of topics: 5
• Number of training documents: 211

Click here for an overview of all topics.

Topic ID	Topic Keywords	Topic Frequency	Label
-1	vacunados - magnetico - nanoportador - 5g - iphone	20	-1_vacunados_magnetico_nanoportador_5g
0	magnetofeccion - bioelectromagnetico - ferritina - vacunas - nanoparticulas	105	0_magnetofeccion_bioelectromagnetico_ferritina_vacunas
1	vacunados - anticovid - dios - peligrosos - morir	43	1_vacunados_anticovid_dios_peligrosos
2	vacuna - microesferas - morgellons - imagen - tentaculos	22	2_vacuna_microesferas_morgellons_imagen
3	profecias - anticristo - septiembre - revolucion - sacerdotes	21	3_profecias_anticristo_septiembre_revolucion

Training hyperparameters

• calculate_probabilities: True
• 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: False
• zeroshot_min_similarity: 0.7
• zeroshot_topic_list: None

Framework versions

• Numpy: 1.26.4
• HDBSCAN: 0.8.40
• UMAP: 0.5.7
• Pandas: 2.2.3
• Scikit-Learn: 1.5.2
• Sentence-transformers: 3.3.1
• Transformers: 4.46.3
• Numba: 0.60.0
• Plotly: 5.24.1
• Python: 3.10.12