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ahessamb
/
bertopic-test

Text Classification
BERTopic
Model card Files Community
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Add BERTopic model

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Files changed (4) hide show
  1. README.md +117 -0
  2. config.json +14 -0
  3. topic_embeddings.safetensors +3 -0
  4. topics.json +3985 -0
README.md ADDED
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1
+
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+ ---
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+ tags:
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+ - bertopic
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+ library_name: bertopic
6
+ pipeline_tag: text-classification
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+ ---
8
+
9
+ # bertopic-test
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+
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+ This is a [BERTopic](https://github.com/MaartenGr/BERTopic) model.
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+ BERTopic is a flexible and modular topic modeling framework that allows for the generation of easily interpretable topics from large datasets.
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+
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+ ## Usage
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+
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+ To use this model, please install BERTopic:
17
+
18
+ ```
19
+ pip install -U bertopic
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+ ```
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+
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+ You can use the model as follows:
23
+
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+ ```python
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+ from bertopic import BERTopic
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+ topic_model = BERTopic.load("ahessamb/bertopic-test")
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+
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+ topic_model.get_topic_info()
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+ ```
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+
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+ ## Topic overview
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+
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+ * Number of topics: 50
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+ * Number of training documents: 1570
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+
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+ <details>
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+ <summary>Click here for an overview of all topics.</summary>
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+
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+ | Topic ID | Topic Keywords | Topic Frequency | Label |
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+ |----------|----------------|-----------------|-------|
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+ | 0 | liquidations - forcefully - betting - liquidation - contracts | 8 | 0_liquidations_forcefully_betting_liquidation |
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+ | 1 | litecoin - wsm - presale - 77 - near | 94 | 1_litecoin_wsm_presale_77 |
43
+ | 2 | sec - court - terraform - dismiss - lawyers | 49 | 2_sec_court_terraform_dismiss |
44
+ | 3 | huobi - hkvac - bsl - web3 - code | 12 | 3_huobi_hkvac_bsl_web3 |
45
+ | 4 | lucie - shiba - susbarium - puppynet - portals | 3 | 4_lucie_shiba_susbarium_puppynet |
46
+ | 5 | 000006819 - shiba - accuracy - finbold - estimates | 27 | 5_000006819_shiba_accuracy_finbold |
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+ | 6 | tokens - sec - binance - securities - coinbase | 45 | 6_tokens_sec_binance_securities |
48
+ | 7 | mckinsey - ai - nanjing - productivity - diffusion | 43 | 7_mckinsey_ai_nanjing_productivity |
49
+ | 8 | resistance - swing - fib - zone - ltc | 32 | 8_resistance_swing_fib_zone |
50
+ | 9 | brinkman - tategpt - bitcoin - artists - wealth | 26 | 9_brinkman_tategpt_bitcoin_artists |
51
+ | 10 | stablecoin - stablecoins - decline - redemptions - tusd | 2 | 10_stablecoin_stablecoins_decline_redemptions |
52
+ | 11 | mutant - mayc - bayc - club - mcmullen | 64 | 11_mutant_mayc_bayc_club |
53
+ | 12 | xrp - ema - ripple - bullish - cryptocurrencies | 43 | 12_xrp_ema_ripple_bullish |
54
+ | 13 | tether - cbdcs - loans - federal - nafcu | 27 | 13_tether_cbdcs_loans_federal |
55
+ | 14 | rate - tradingview - bnb - breakout - coinmarketcap | 85 | 14_rate_tradingview_bnb_breakout |
56
+ | 15 | 26 - bulls - rsi - ceiling - 300 | 2 | 15_26_bulls_rsi_ceiling |
57
+ | 16 | lowest - jump - week - wallet - staggering | 3 | 16_lowest_jump_week_wallet |
58
+ | 17 | xrp - ripple - mekras - sbi - institutions | 56 | 17_xrp_ripple_mekras_sbi |
59
+ | 18 | debt - mortgages - trillion - government - suspends | 3 | 18_debt_mortgages_trillion_government |
60
+ | 19 | longitude - chronometer - bitcoin - ships - graffiti | 2 | 19_longitude_chronometer_bitcoin_ships |
61
+ | 20 | volumes - piggy - aud - xrp - usdt | 15 | 20_volumes_piggy_aud_xrp |
62
+ | 21 | root - ledger - stakers - sidechains - compatibility | 4 | 21_root_ledger_stakers_sidechains |
63
+ | 22 | astra - letter - concerns - investors - bitwise | 4 | 22_astra_letter_concerns_investors |
64
+ | 23 | gold - governments - manipulated - stocks - mined | 10 | 23_gold_governments_manipulated_stocks |
65
+ | 24 | tether - sygnum - documents - bank - coindesk | 9 | 24_tether_sygnum_documents_bank |
66
+ | 25 | rewards - governance - lido - proposal - june | 45 | 25_rewards_governance_lido_proposal |
67
+ | 26 | listings - coin - fairerc20 - bittrex - withdrawals | 68 | 26_listings_coin_fairerc20_bittrex |
68
+ | 27 | peaq - ordibots - cosmos - fetch - machine | 81 | 27_peaq_ordibots_cosmos_fetch |
69
+ | 28 | uniswap - v4 - orders - hooks - differing | 23 | 28_uniswap_v4_orders_hooks |
70
+ | 29 | price - neo - matic - rise - altcoin | 92 | 29_price_neo_matic_rise |
71
+ | 30 | emptydoc - staff - policy - binance - workspaces | 2 | 30_emptydoc_staff_policy_binance |
72
+ | 31 | lunc - synthetix - terra - perps - staking | 33 | 31_lunc_synthetix_terra_perps |
73
+ | 32 | tweet - dogecoin - chart - meme - negative | 3 | 32_tweet_dogecoin_chart_meme |
74
+ | 33 | binance - securities - exchange - cz - regulators | 63 | 33_binance_securities_exchange_cz |
75
+ | 34 | bitmart - sale - xrp - discount - event | 4 | 34_bitmart_sale_xrp_discount |
76
+ | 35 | yuan - event - olympics - canadians - organizers | 49 | 35_yuan_event_olympics_canadians |
77
+ | 36 | gusd - fidelity - bitcoin - proposal - blackrock | 52 | 36_gusd_fidelity_bitcoin_proposal |
78
+ | 37 | bills - mcglone - markets - stablecoins - liquidity | 56 | 37_bills_mcglone_markets_stablecoins |
79
+ | 38 | asset - gain - drop - trading - hours | 2 | 38_asset_gain_drop_trading |
80
+ | 39 | epstein - hamsterwheel - vulnerability - bounty - certick | 28 | 39_epstein_hamsterwheel_vulnerability_bounty |
81
+ | 40 | pyth - transparency - data - terra - oracle | 19 | 40_pyth_transparency_data_terra |
82
+ | 41 | shiba - inu - weighted - collapse - recovery | 2 | 41_shiba_inu_weighted_collapse |
83
+ | 42 | neo - opensea - carey - security - impersonators | 24 | 42_neo_opensea_carey_security |
84
+ | 43 | balancer - zkevm - liquidity - defi - 8020 | 3 | 43_balancer_zkevm_liquidity_defi |
85
+ | 44 | reed - battle - platform - argument - trading | 22 | 44_reed_battle_platform_argument |
86
+ | 45 | ada - cardano - whale - sell - investors | 4 | 45_ada_cardano_whale_sell |
87
+ | 46 | uk - coinbase - hong - crypto - regulatory | 65 | 46_uk_coinbase_hong_crypto |
88
+ | 47 | ethereum - tvl - defi - arbitrum - airdrop | 54 | 47_ethereum_tvl_defi_arbitrum |
89
+ | 48 | swyftx - shibarium - token - shibaswap - shiba | 54 | 48_swyftx_shibarium_token_shibaswap |
90
+ | 49 | bitcoin - mining - gain - miners - difficulty | 54 | 49_bitcoin_mining_gain_miners |
91
+
92
+ </details>
93
+
94
+ ## Training hyperparameters
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+
96
+ * calculate_probabilities: False
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+ * language: None
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+ * low_memory: False
99
+ * min_topic_size: 10
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+ * n_gram_range: (1, 1)
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+ * nr_topics: None
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+ * seed_topic_list: None
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+ * top_n_words: 10
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+ * verbose: False
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+
106
+ ## Framework versions
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+
108
+ * Numpy: 1.22.4
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+ * HDBSCAN: 0.8.29
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+ * UMAP: 0.5.3
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+ * Pandas: 1.5.3
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+ * Scikit-Learn: 1.2.2
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+ * Sentence-transformers: 2.2.2
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+ * Transformers: 4.30.2
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+ * Numba: 0.56.4
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+ * Plotly: 5.13.1
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+ * Python: 3.10.12
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