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KingKazma
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xsum_22457_3000_1500_test

Text Classification
BERTopic
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  1. README.md +77 -0
  2. config.json +15 -0
  3. topic_embeddings.safetensors +3 -0
  4. topics.json +2005 -0
README.md ADDED
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1
+
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+ ---
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+ tags:
4
+ - bertopic
5
+ library_name: bertopic
6
+ pipeline_tag: text-classification
7
+ ---
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+
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+ # xsum_22457_3000_1500_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.
13
+
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+ ## Usage
15
+
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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("KingKazma/xsum_22457_3000_1500_test")
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+
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+ topic_model.get_topic_info()
29
+ ```
30
+
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+ ## Topic overview
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+
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+ * Number of topics: 10
34
+ * Number of training documents: 1500
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+
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+ <details>
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+ <summary>Click here for an overview of all topics.</summary>
38
+
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+ | Topic ID | Topic Keywords | Topic Frequency | Label |
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+ |----------|----------------|-----------------|-------|
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+ | -1 | said - club - player - game - football | 10 | -1_said_club_player_game |
42
+ | 0 | said - mr - people - would - year | 167 | 0_said_mr_people_would |
43
+ | 1 | kick - shot - free - goal - right | 1066 | 1_kick_shot_free_goal |
44
+ | 2 | midfielder - loan - season - club - league | 69 | 2_midfielder_loan_season_club |
45
+ | 3 | race - sport - gold - medal - olympic | 53 | 3_race_sport_gold_medal |
46
+ | 4 | celtic - club - aberdeen - cup - player | 39 | 4_celtic_club_aberdeen_cup |
47
+ | 5 | england - cricket - wicket - test - captain | 33 | 5_england_cricket_wicket_test |
48
+ | 6 | cup - wales - rugby - game - fa | 33 | 6_cup_wales_rugby_game |
49
+ | 7 | wimbledon - player - murray - im - atp | 18 | 7_wimbledon_player_murray_im |
50
+ | 8 | armstrong - banned - antidoping - rugby - sky | 12 | 8_armstrong_banned_antidoping_rugby |
51
+
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+ </details>
53
+
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+ ## Training hyperparameters
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+
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+ * calculate_probabilities: True
57
+ * language: english
58
+ * low_memory: False
59
+ * min_topic_size: 10
60
+ * n_gram_range: (1, 1)
61
+ * nr_topics: None
62
+ * seed_topic_list: None
63
+ * top_n_words: 10
64
+ * verbose: False
65
+
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+ ## Framework versions
67
+
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+ * Numpy: 1.22.4
69
+ * HDBSCAN: 0.8.33
70
+ * UMAP: 0.5.3
71
+ * Pandas: 1.5.3
72
+ * Scikit-Learn: 1.2.2
73
+ * Sentence-transformers: 2.2.2
74
+ * Transformers: 4.31.0
75
+ * Numba: 0.57.1
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+ * Plotly: 5.13.1
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+ * Python: 3.10.12
config.json ADDED
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+ {
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+ "calculate_probabilities": true,
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+ "low_memory": false,
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+ "min_topic_size": 10,
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+ ],
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+ "nr_topics": null,
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+ "seed_topic_list": null,
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+ "verbose": false,
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+ "embedding_model": "sentence-transformers/all-MiniLM-L6-v2"
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+ }
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:767f35cd3730abe6be3664f1fc8120b8db7a08e5515a749b9670c052f7bb4fca
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+ size 15448
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