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shaistaDev7/
topic_modeling_on_UDC

Name: topic_modeling_on_UDC
Rating: 2.5 (6 reviews)

bertopic

text-classification

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urdu_topic_modeling

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("shaistaDev7/urdu_topic_modeling")

topic_model.get_topic_info()

Topic overview

Number of topics: 5
Number of training documents: 1008

Click here for an overview of all topics.

Topic ID	Topic Keywords	Topic Frequency	Label
0	کینسر - استعمال - جسم - علاج - افراد	315	0_کینسر_استعمال_جسم_علاج
1	ٹیم - کرکٹ - محمد - میڈل - انگلینڈ	240	1_ٹیم_کرکٹ_محمد_میڈل
2	روپے - ارب - فیصد - ٹیکس - حکومت	238	2_روپے_ارب_فیصد_ٹیکس
3	فلم - خان - ووڈ - بالی - اداکارہ	205	3_فلم_خان_ووڈ_بالی
4	ظفر - میشا - شفیع - علی - جنسی	10	4_ظفر_میشا_شفیع_علی

Training hyperparameters

calculate_probabilities: True
language: urdu
low_memory: True
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: 1.23.5
HDBSCAN: 0.8.33
UMAP: 0.5.5
Pandas: 1.5.3
Scikit-Learn: 1.2.2
Sentence-transformers: 2.2.2
Transformers: 4.35.2
Numba: 0.58.1
Plotly: 5.15.0
Python: 3.10.12

shaistaDev7/topic_modeling_on_UDC