Noibu/Bertopic_Keybert_Champions

tags:

• —bertopic libraryname: bertopic pipelinetag: text-classification ---

BertopicKeybertChampions

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("Noibu/Bertopic_Keybert_Champions")

topic_model.get_topic_info()

Topic overview

• —Number of topics: 10
• —Number of training documents: 11678

<details> <summary>Click here for an overview of all topics.</summary>

</details>

Training hyperparameters

• —calculate_probabilities: True
• —language: None
• —low_memory: False
• —mintopicsize: 50
• —ngramrange: (1, 2)
• —nr_topics: 10
• —seedtopiclist: [['ship', 'address', 'location', 'destination', 'post', 'deliver', 'florida', 'texas', 'united states', 'europe', 'asia'], ['password', 'account', 'login', 'sign in', 'email', 'id', 'authentication', 'username'], ['select', 'choose', 'sort', 'next', 'more', 'back', 'scroll', 'previous', 'search', 'results', 'catalog', 'find', 'lookup', 'query', 'browse', 'explore', 'filter'], ['first', 'last', 'name', 'username', 'middlename', 'surname', 'given name', 'alias'], ['cart', 'basket', 'bag', 'add', 'remove', 'edit', 'cancel', 'update', 'delete', 'modify', 'change'], ['checkout', 'payment', 'pay', 'order', 'purchase', 'billing', 'transaction'], ['small', 'medium', 'large', 'extra large', 's', 'm', 'l', 'xl', 'xxl', 'slim fit', 'size', 'fit', 'quantity'], ['promo', 'code', 'apply', 'welcome', 'offer']]
• —topnwords: 10
• —verbose: False

Framework versions

• —Numpy: 1.23.5
• —HDBSCAN: 0.8.33
• —UMAP: 0.5.3
• —Pandas: 1.5.3
• —Scikit-Learn: 1.2.2
• —Sentence-transformers: 2.2.2
• —Transformers: 4.31.0
• —Numba: 0.56.4
• —Plotly: 5.15.0
• —Python: 3.10.12