bertopic-test_1010
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("ahessamb/bertopic-test_1010")
topic_model.get_topic_info()
Topic overview
- Number of topics: 10
- Number of training documents: 1570
Click here for an overview of all topics.
| Topic ID | Topic Keywords | Topic Frequency | Label |
|---|---|---|---|
| 0 | ethereum - listings - market - eth - binance | 173 | 0_ethereum_listings_market_eth |
| 1 | xrp - ripple - crypto - mekras - sbi | 93 | 1_xrp_ripple_crypto_mekras |
| 2 | peaq - blockchain - nft - opensea - ordibots | 226 | 2_peaq_blockchain_nft_opensea |
| 3 | crypto - regulatory - securities - coinbase - lawsuit | 204 | 3_crypto_regulatory_securities_coinbase |
| 4 | binance - exchange - securities - sec - letter | 116 | 4_binance_exchange_securities_sec |
| 5 | mutant - mayc - bayc - club - mcmullen | 95 | 5_mutant_mayc_bayc_club |
| 6 | tether - yuan - games - bitcoin - cbdcs | 211 | 6_tether_yuan_games_bitcoin |
| 7 | crypto - bills - exponential - markets - liquidity | 140 | 7_crypto_bills_exponential_markets |
| 8 | ada - cardano - litecoin - resistance - market | 214 | 8_ada_cardano_litecoin_resistance |
| 9 | shib - doge - shiba - sentiment - market | 98 | 9_shib_doge_shiba_sentiment |
Training hyperparameters
- calculate_probabilities: False
- 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
Framework versions
- Numpy: 1.22.4
- HDBSCAN: 0.8.29
- UMAP: 0.5.3
- Pandas: 1.5.3
- Scikit-Learn: 1.2.2
- Sentence-transformers: 2.2.2
- Transformers: 4.30.2
- Numba: 0.56.4
- Plotly: 5.13.1
- Python: 3.10.12
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