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ahessamb
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bertopic-test_3030

Text Classification
BERTopic
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Files changed (4) hide show
  1. README.md +97 -0
  2. config.json +14 -0
  3. topic_embeddings.safetensors +3 -0
  4. topics.json +3025 -0
README.md ADDED
@@ -0,0 +1,97 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+
2
+ ---
3
+ tags:
4
+ - bertopic
5
+ library_name: bertopic
6
+ pipeline_tag: text-classification
7
+ ---
8
+
9
+ # bertopic-test_3030
10
+
11
+ This is a [BERTopic](https://github.com/MaartenGr/BERTopic) model.
12
+ BERTopic is a flexible and modular topic modeling framework that allows for the generation of easily interpretable topics from large datasets.
13
+
14
+ ## Usage
15
+
16
+ To use this model, please install BERTopic:
17
+
18
+ ```
19
+ pip install -U bertopic
20
+ ```
21
+
22
+ You can use the model as follows:
23
+
24
+ ```python
25
+ from bertopic import BERTopic
26
+ topic_model = BERTopic.load("ahessamb/bertopic-test_3030")
27
+
28
+ topic_model.get_topic_info()
29
+ ```
30
+
31
+ ## Topic overview
32
+
33
+ * Number of topics: 30
34
+ * Number of training documents: 1570
35
+
36
+ <details>
37
+ <summary>Click here for an overview of all topics.</summary>
38
+
39
+ | Topic ID | Topic Keywords | Topic Frequency | Label |
40
+ |----------|----------------|-----------------|-------|
41
+ | 0 | apecoin - neckline - shoulders - fluctuating - chart | 2 | 0_apecoin_neckline_shoulders_fluctuating |
42
+ | 1 | astra - letter - investors - coindesk - bankruptcy | 84 | 1_astra_letter_investors_coindesk |
43
+ | 2 | 26 - bulls - rsi - ceiling - low | 30 | 2_26_bulls_rsi_ceiling |
44
+ | 3 | mutant - mayc - bayc - club - nfts | 112 | 3_mutant_mayc_bayc_club |
45
+ | 4 | shib - doge - shiba - sentiment - dogecoin | 115 | 4_shib_doge_shiba_sentiment |
46
+ | 5 | xrp - btc - lawsuit - sleuth - bullish | 47 | 5_xrp_btc_lawsuit_sleuth |
47
+ | 6 | binance - securities - crypto - coinbase - regulatory | 147 | 6_binance_securities_crypto_coinbase |
48
+ | 7 | ordibots - ordinals - collection - gbrc721 - text | 33 | 7_ordibots_ordinals_collection_gbrc721 |
49
+ | 8 | kitao - sbi - xrp - ripple - holdings | 95 | 8_kitao_sbi_xrp_ripple |
50
+ | 9 | listings - exponential - coin - ethereum - defi | 163 | 9_listings_exponential_coin_ethereum |
51
+ | 10 | yuan - event - games - rewards - olympics | 68 | 10_yuan_event_games_rewards |
52
+ | 11 | emptydoc - richmond - fashion - shiba - community | 15 | 11_emptydoc_richmond_fashion_shiba |
53
+ | 12 | sygnum - crypto - piggy - btr - huobi | 59 | 12_sygnum_crypto_piggy_btr |
54
+ | 13 | dln - debridge - chains - liquidity - slippage | 3 | 13_dln_debridge_chains_liquidity |
55
+ | 14 | longitude - chronometer - bitcoin - ships - rogers | 5 | 14_longitude_chronometer_bitcoin_ships |
56
+ | 15 | arbitrum - airdrop - recipients - scalability - ethereum | 14 | 15_arbitrum_airdrop_recipients_scalability |
57
+ | 16 | ethereum - fidelity - blackrock - cryptocurrency - fee | 111 | 16_ethereum_fidelity_blackrock_cryptocurrency |
58
+ | 17 | swyftx - shibarium - token - shiba - shibaswap | 17 | 17_swyftx_shibarium_token_shiba |
59
+ | 18 | zachxbt - squid - huang - donation - accused | 21 | 18_zachxbt_squid_huang_donation |
60
+ | 19 | reading - trend - leaning - ltc - breakdown | 2 | 19_reading_trend_leaning_ltc |
61
+ | 20 | tether - reserve - gusd - cbdcs - bills | 45 | 20_tether_reserve_gusd_cbdcs |
62
+ | 21 | lace - brave - mobile - wallet - iog | 2 | 21_lace_brave_mobile_wallet |
63
+ | 22 | binance - day - coinbase - exchange - bitcoin | 82 | 22_binance_day_coinbase_exchange |
64
+ | 23 | v3 - bnb - repurchase - peng - pancakeswap | 2 | 23_v3_bnb_repurchase_peng |
65
+ | 24 | xrp - banks - ripple - institutions - p2p | 6 | 24_xrp_banks_ripple_institutions |
66
+ | 25 | ada - level - litecoin - cardano - resistance | 186 | 25_ada_level_litecoin_cardano |
67
+ | 26 | xrp - hoskinson - cardano - securities - analisa | 26 | 26_xrp_hoskinson_cardano_securities |
68
+ | 27 | peaq - lunc - fetch - cosmos - terra | 73 | 27_peaq_lunc_fetch_cosmos |
69
+ | 28 | kostin - russia - sanctions - currency - yuan | 2 | 28_kostin_russia_sanctions_currency |
70
+ | 29 | upgrade - terra - lunc - chrome - jumps | 3 | 29_upgrade_terra_lunc_chrome |
71
+
72
+ </details>
73
+
74
+ ## Training hyperparameters
75
+
76
+ * calculate_probabilities: False
77
+ * language: None
78
+ * low_memory: False
79
+ * min_topic_size: 10
80
+ * n_gram_range: (1, 1)
81
+ * nr_topics: None
82
+ * seed_topic_list: None
83
+ * top_n_words: 10
84
+ * verbose: False
85
+
86
+ ## Framework versions
87
+
88
+ * Numpy: 1.22.4
89
+ * HDBSCAN: 0.8.29
90
+ * UMAP: 0.5.3
91
+ * Pandas: 1.5.3
92
+ * Scikit-Learn: 1.2.2
93
+ * Sentence-transformers: 2.2.2
94
+ * Transformers: 4.30.2
95
+ * Numba: 0.56.4
96
+ * Plotly: 5.13.1
97
+ * Python: 3.10.12
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+ 1,
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+ ],
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+ "nr_topics": null,
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+ "seed_topic_list": null,
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+ "top_n_words": 10,
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+ "verbose": false
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+ }
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