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TheItCrOw/
bertopic-german-mails-small

Name: bertopic-german-mails-small
Availability: InStock

bertopic

text-classification

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bertopic-german-mails-small

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("TheItCrOw/bertopic-german-mails-small")

topic_model.get_topic_info()

Topic overview

Number of topics: 7
Number of training documents: 627

Click here for an overview of all topics.

Topic ID	Topic Keywords	Topic Frequency	Label
-1	specificationsheet - der xsl - specs - xsl - parsen	40	Fehlermeldung "Fehler beim Parsen der XSL Daten" in der Gewinnkalkulation
0	mac - die installation - wenden sie sich - wenden sie - wenden	223	Interbase SPARQL Server - Installation fehlerhaft
1	auf den - sie bitte - die bestellnummer - anzeigen - stelle	137	Warehouses Prozessverwaltung und -übertragung
2	fuer - moechte - ueber - freundlichen gruessen - mit freundlichen gruessen	75	Softwareprobleme und Support
3	aktivierungscode - fehlerhaften - 27 - ticket - einer anderen	65	Softwarefehler bei Sales First Class
4	intel - core - ethernet - ghz - solarmobile	44	Hardwareprobleme bei der Installation von Sales First Class
5	build exception - build - project build exception - disc project build - project build	43	Brennvorgänge mit Build-Exception-Fehlern

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: True
zeroshot_min_similarity: 0.7
zeroshot_topic_list: None

Framework versions

Numpy: 2.2.6
HDBSCAN: 0.8.40
UMAP: 0.5.9.post2
Pandas: 2.3.2
Scikit-Learn: 1.7.1
Sentence-transformers: 5.1.0
Transformers: 4.55.4
Numba: 0.61.2
Plotly: 6.3.0
Python: 3.12.0