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WGNEWS_APR20

Text Classification
BERTopic
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Add BERTopic model

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  1. README.md +126 -0
  2. config.json +16 -0
  3. ctfidf.safetensors +3 -0
  4. ctfidf_config.json +0 -0
  5. topic_embeddings.safetensors +3 -0
  6. topics.json +0 -0
README.md ADDED
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+
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+ ---
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+ tags:
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+ - bertopic
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+ library_name: bertopic
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+ pipeline_tag: text-classification
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+ ---
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+
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+ # WGNEWS_APR20
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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:
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+
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+ ```
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+ pip install -U bertopic
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+ ```
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+
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+ You can use the model as follows:
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+
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+ ```python
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+ from bertopic import BERTopic
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+ topic_model = BERTopic.load("tyrealqian/WGNEWS_APR20")
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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: 57
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+ * Number of training documents: 6094
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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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+ | -1 | media - athletes - ceremony - opening - opening ceremony | 20 | -1_media_athletes_ceremony_opening |
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+ | 0 | covid - cases - pandemic - omicron - covid cases | 2071 | 0_covid_cases_pandemic_omicron |
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+ | 1 | teamcanada - curling - canada - hockey - canadas | 438 | 1_teamcanada_curling_canada_hockey |
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+ | 2 | kamila - valieva - kamila valieva - russian figure - skater kamila | 268 | 2_kamila_valieva_kamila valieva_russian figure |
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+ | 3 | winter sports - sports - ice snow - globalink - passion | 199 | 3_winter sports_sports_ice snow_globalink |
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+ | 4 | spokesperson - globalink - ambassador - turkish - said globalink | 197 | 4_spokesperson_globalink_ambassador_turkish |
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+ | 5 | dwen - mascot - bing dwen - dwen dwen - bing | 182 | 5_dwen_mascot_bing dwen_dwen dwen |
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+ | 6 | speed - short track - speed skating - track speed - track | 173 | 6_speed_short track_speed skating_track speed |
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+ | 7 | gu - eileen - womens freeski - eileen gu - gu ailing | 145 | 7_gu_eileen_womens freeski_eileen gu |
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+ | 8 | torch - flame - torch relay - relay - olympic flame | 139 | 8_torch_flame_torch relay_relay |
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+ | 9 | australia - diplomatic boycott - diplomatic - boycott - join diplomatic | 127 | 9_australia_diplomatic boycott_diplomatic_boycott |
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+ | 10 | traditional - chinese new - new year - papercutting - culture | 107 | 10_traditional_chinese new_new year_papercutting |
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+ | 11 | carbon - green - pollution - air quality - climate | 105 | 11_carbon_green_pollution_air quality |
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+ | 12 | biden - diplomatic boycott - diplomatic - white house - joe | 79 | 12_biden_diplomatic boycott_diplomatic_white house |
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+ | 13 | oval - skating oval - national speed - venue - ice | 73 | 13_oval_skating oval_national speed_venue |
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+ | 14 | mikaela - shiffrin - mikaela shiffrin - slalom - race | 71 | 14_mikaela_shiffrin_mikaela shiffrin_slalom |
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+ | 15 | socalled - boycott beijing - boycott - politicians - opposes | 69 | 15_socalled_boycott beijing_boycott_politicians |
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+ | 16 | robot - robots - food - serving - served | 68 | 16_robot_robots_food_serving |
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+ | 17 | putin - vladimir - vladimir putin - russian president - president vladimir | 66 | 17_putin_vladimir_vladimir putin_russian president |
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+ | 18 | kiara reddingius - kiara - reddingius - australian - australias | 65 | 18_kiara reddingius_kiara_reddingius_australian |
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+ | 19 | xi jinping - jinping - president xi - xi - chinese president | 65 | 19_xi jinping_jinping_president xi_xi |
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+ | 20 | human rights - rights - human - chinas human - rights watch | 61 | 20_human rights_rights_human_chinas human |
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+ | 21 | yanqing - paralympic - villages - winter paralympic - completed | 60 | 21_yanqing_paralympic_villages_winter paralympic |
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+ | 22 | nest - birds nest - birds - rehearsal - fireworks | 59 | 22_nest_birds nest_birds_rehearsal |
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+ | 23 | sadowskisynnott - new zealands - zealands - womens slopestyle - jakara | 59 | 23_sadowskisynnott_new zealands_zealands_womens slopestyle |
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+ | 24 | shaun - shaun white - white - halfpipe - hirano | 58 | 24_shaun_shaun white_white_halfpipe |
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+ | 25 | su - yiming - su yiming - mens snowboard - snowboarder su | 57 | 25_su_yiming_su yiming_mens snowboard |
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+ | 26 | heres watch - opening ceremony - opening - cbc - watch opening | 51 | 26_heres watch_opening ceremony_opening_cbc |
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+ | 27 | nhl - players - nhl players - send players - olympics nhl | 49 | 27_nhl_players_nhl players_send players |
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+ | 28 | medals grabs - gold delegations - heres breakdown - breakdown - count stands | 47 | 28_medals grabs_gold delegations_heres breakdown_breakdown |
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+ | 29 | president thomas - bach - thomas bach - thomas - ioc president | 47 | 29_president thomas_bach_thomas bach_thomas |
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+ | 30 | nathan chen - chen - nathan - skater nathan - elton | 45 | 30_nathan chen_chen_nathan_skater nathan |
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+ | 31 | snowfall - heavy - heavy snowfall - weather - snow | 43 | 31_snowfall_heavy_heavy snowfall_weather |
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+ | 32 | jamaicas - jamaica - benjamin alexander - benjamin - alexander | 43 | 32_jamaicas_jamaica_benjamin alexander_benjamin |
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+ | 33 | countdown - countdown beijing - day countdown - days - days beijing | 42 | 33_countdown_countdown beijing_day countdown_days |
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+ | 34 | reuterspictures - pictures - day pictures - pictures beijing - olympics day | 40 | 34_reuterspictures_pictures_day pictures_pictures beijing |
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+ | 35 | bank - commemorative - yuan - digital - coins | 40 | 35_bank_commemorative_yuan_digital |
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+ | 36 | yuzuruhanyu - hanyu - yuzuru - japanese - yuzuru hanyu | 39 | 36_yuzuruhanyu_hanyu_yuzuru_japanese |
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+ | 37 | xi - president xi - xi jinping - jinping - chinese president | 37 | 37_xi_president xi_xi jinping_jinping |
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+ | 38 | aerials - xu mengtao - mengtao - xu - womens aerials | 34 | 38_aerials_xu mengtao_mengtao_xu |
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+ | 39 | tickets - sell - sell tickets - sold - spectators | 33 | 39_tickets_sell_sell tickets_sold |
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+ | 40 | technologies - aerospace - technology - technologies used - scitech | 33 | 40_technologies_aerospace_technology_technologies used |
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+ | 41 | sui - cong - wenjing - sui wenjing - han cong | 32 | 41_sui_cong_wenjing_sui wenjing |
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+ | 42 | erin - jackson - erin jackson - woman - black | 32 | 42_erin_jackson_erin jackson_woman |
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+ | 43 | burner - personal - phones - apps smartphonelike - smartphonelike device | 31 | 43_burner_personal_phones_apps smartphonelike |
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+ | 44 | leduc - nonbinary - openly - timothy leduc - timothy | 30 | 44_leduc_nonbinary_openly_timothy leduc |
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+ | 45 | summer winter - host summer - city host - summer - city | 27 | 45_summer winter_host summer_city host_summer |
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+ | 46 | ukraine - invasion - ukraines - ukraine beijing - invasion ukraine | 26 | 46_ukraine_invasion_ukraines_ukraine beijing |
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+ | 47 | ralph lauren - lauren - uniforms - ralph - lauren unveiled | 26 | 47_ralph lauren_lauren_uniforms_ralph |
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+ | 48 | argentine - fernandez - president alberto - argentine president - alberto fernandez | 25 | 48_argentine_fernandez_president alberto_argentine president |
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+ | 49 | truce - olympic truce - antonio guterres - secretarygeneral antonio - guterres | 25 | 49_truce_olympic truce_antonio guterres_secretarygeneral antonio |
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+ | 50 | peng - shuai - peng shuai - tennis - chinese tennis | 25 | 50_peng_shuai_peng shuai_tennis |
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+ | 51 | zhangjiakou - chongli district - chongli - hebei - cohost | 23 | 51_zhangjiakou_chongli district_chongli_hebei |
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+ | 52 | athletes watch - watch beijing - names - biggest names - look biggest | 23 | 52_athletes watch_watch beijing_names_biggest names |
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+ | 53 | railway - highspeed - train - highspeed railway - beijingzhangjiakou highspeed | 23 | 53_railway_highspeed_train_highspeed railway |
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+ | 54 | peel - laura peel - laura - kerry - aerial | 22 | 54_peel_laura peel_laura_kerry |
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+ | 55 | shougang - shougang park - industrial - park - big air | 20 | 55_shougang_shougang park_industrial_park |
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+
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+ </details>
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+
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+ ## Training hyperparameters
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+
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+ * calculate_probabilities: True
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+ * language: None
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+ * low_memory: False
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+ * 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: True
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+ * zeroshot_min_similarity: 0.7
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+ * zeroshot_topic_list: None
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+
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+ ## Framework versions
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+
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+ * Numpy: 2.0.2
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+ * HDBSCAN: 0.8.40
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+ * UMAP: 0.5.7
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+ * Pandas: 2.2.2
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+ * Scikit-Learn: 1.6.1
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+ * Sentence-transformers: 3.4.1
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+ * Transformers: 4.51.3
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+ * Numba: 0.60.0
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+ * Plotly: 5.24.1
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+ * Python: 3.11.12
config.json ADDED
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+ {
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+ "calculate_probabilities": true,
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+ "language": null,
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+ "low_memory": false,
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+ "min_topic_size": 10,
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+ "n_gram_range": [
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+ 1,
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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": true,
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+ "zeroshot_min_similarity": 0.7,
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+ "zeroshot_topic_list": null
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+ }
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topic_embeddings.safetensors ADDED
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topics.json ADDED
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