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sneakykilli
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Qatar_BERTopic

Text Classification
BERTopic
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Add BERTopic model

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  1. README.md +91 -0
  2. config.json +17 -0
  3. ctfidf.safetensors +3 -0
  4. ctfidf_config.json +0 -0
  5. topic_embeddings.safetensors +3 -0
  6. topics.json +1807 -0
README.md ADDED
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1
+
2
+ ---
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+ tags:
4
+ - bertopic
5
+ library_name: bertopic
6
+ pipeline_tag: text-classification
7
+ ---
8
+
9
+ # Qatar_BERTopic
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+
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
+
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+ ## Usage
15
+
16
+ To use this model, please install BERTopic:
17
+
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+ ```
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+ pip install -U bertopic
20
+ ```
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+
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+ You can use the model as follows:
23
+
24
+ ```python
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+ from bertopic import BERTopic
26
+ topic_model = BERTopic.load("sneakykilli/Qatar_BERTopic")
27
+
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+ topic_model.get_topic_info()
29
+ ```
30
+
31
+ ## Topic overview
32
+
33
+ * Number of topics: 22
34
+ * Number of training documents: 714
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
+ | -1 | doha - qatar - airline - airlines - refund | 5 | -1_doha_qatar_airline_airlines |
42
+ | 0 | doha - qatar - airline - airlines - flights | 211 | 0_doha_qatar_airline_airlines |
43
+ | 1 | refund - refunded - refunds - booking - voucher | 78 | 1_refund_refunded_refunds_booking |
44
+ | 2 | doha - qatar - baggage - luggage - airline | 72 | 2_doha_qatar_baggage_luggage |
45
+ | 3 | airline - passengers - flights - attendant - steward | 49 | 3_airline_passengers_flights_attendant |
46
+ | 4 | qatar - airline - airlines - flights - carriers | 44 | 4_qatar_airline_airlines_flights |
47
+ | 5 | baggage - doha - airlines - airline - luggage | 39 | 5_baggage_doha_airlines_airline |
48
+ | 6 | airline - airlines - flights - emirates - flight | 35 | 6_airline_airlines_flights_emirates |
49
+ | 7 | refund - airline - flights - flight - cancel | 32 | 7_refund_airline_flights_flight |
50
+ | 8 | airline - airlines - seats - qatar - seating | 28 | 8_airline_airlines_seats_qatar |
51
+ | 9 | qatar - doha - airlines - flights - emirates | 18 | 9_qatar_doha_airlines_flights |
52
+ | 10 | customer - complaints - service - terrible - horrible | 17 | 10_customer_complaints_service_terrible |
53
+ | 11 | qatar - complaint - doha - complaints - airline | 15 | 11_qatar_complaint_doha_complaints |
54
+ | 12 | avios - qatar - booking - compensation - aviso | 14 | 12_avios_qatar_booking_compensation |
55
+ | 13 | airline - airlines - flight - airplane - horrible | 9 | 13_airline_airlines_flight_airplane |
56
+ | 14 | doha - qatar - flights - cancellation - airlines | 8 | 14_doha_qatar_flights_cancellation |
57
+ | 15 | doha - qatar - qatari - emirates - flight | 8 | 15_doha_qatar_qatari_emirates |
58
+ | 16 | doha - qatar - airlines - bangkok - airport | 8 | 16_doha_qatar_airlines_bangkok |
59
+ | 17 | seats - seating - airline - booked - seat | 7 | 17_seats_seating_airline_booked |
60
+ | 18 | qatar - opodo - airline - refunded - voucher | 6 | 18_qatar_opodo_airline_refunded |
61
+ | 19 | doha - qatar - flight - destinations - airways | 6 | 19_doha_qatar_flight_destinations |
62
+ | 20 | qatar - airlines - disability - flight - wheelchair | 5 | 20_qatar_airlines_disability_flight |
63
+
64
+ </details>
65
+
66
+ ## Training hyperparameters
67
+
68
+ * calculate_probabilities: False
69
+ * language: None
70
+ * low_memory: False
71
+ * min_topic_size: 5
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+ * n_gram_range: (1, 1)
73
+ * 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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+ * zeroshot_min_similarity: 0.7
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+ * zeroshot_topic_list: None
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+
80
+ ## Framework versions
81
+
82
+ * Numpy: 1.24.3
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+ * HDBSCAN: 0.8.33
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+ * UMAP: 0.5.5
85
+ * Pandas: 2.0.3
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+ * Scikit-Learn: 1.2.2
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+ * Sentence-transformers: 2.3.1
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+ * Transformers: 4.36.2
89
+ * Numba: 0.57.1
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+ * Plotly: 5.16.1
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+ * Python: 3.10.12
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