Add BERTopic model
Browse files- README.md +73 -0
- config.json +16 -0
- ctfidf.safetensors +3 -0
- ctfidf_config.json +3775 -0
- topic_embeddings.safetensors +3 -0
- topics.json +418 -0
README.md
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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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# MARTINI_enrich_BERTopic_muhbirajans
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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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## Usage
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To use this model, please install BERTopic:
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```
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pip install -U bertopic
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```
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You can use the model as follows:
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```python
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from bertopic import BERTopic
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topic_model = BERTopic.load("AIDA-UPM/MARTINI_enrich_BERTopic_muhbirajans")
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topic_model.get_topic_info()
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```
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## Topic overview
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* Number of topics: 4
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* Number of training documents: 287
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<details>
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<summary>Click here for an overview of all topics.</summary>
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| Topic ID | Topic Keywords | Topic Frequency | Label |
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|----------|----------------|-----------------|-------|
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| -1 | altaylı - yıldırım - erdogan - ataturk - kapalı | 28 | -1_altaylı_yıldırım_erdogan_ataturk |
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| 0 | erdogan - kılıcdaroglu - ahmet - ittifakı - secimlerde | 118 | 0_erdogan_kılıcdaroglu_ahmet_ittifakı |
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| 1 | kuracagım - kardıcalı - tartıstıgı - kızını - basladı | 100 | 1_kuracagım_kardıcalı_tartıstıgı_kızını |
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| 2 | fiyatı - sanlıurfa - buyuksehir - sıgınmacısı - yılın | 41 | 2_fiyatı_sanlıurfa_buyuksehir_sıgınmacısı |
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</details>
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## Training hyperparameters
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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: False
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* zeroshot_min_similarity: 0.7
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* zeroshot_topic_list: None
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## Framework versions
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* Numpy: 1.26.4
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* HDBSCAN: 0.8.40
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* UMAP: 0.5.7
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* Pandas: 2.2.3
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* Scikit-Learn: 1.5.2
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* Sentence-transformers: 3.3.1
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* Transformers: 4.46.3
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* Numba: 0.60.0
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* Plotly: 5.24.1
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* Python: 3.10.12
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config.json
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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": false,
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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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ctfidf.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:6b3d97b7b485cd4306b242ff3bef32a1f8eb6cf9da548a2ff44d81e2654915f1
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size 82508
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ctfidf_config.json
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|
| 1 |
+
{
|
| 2 |
+
"ctfidf_model": {
|
| 3 |
+
"bm25_weighting": false,
|
| 4 |
+
"reduce_frequent_words": true
|
| 5 |
+
},
|
| 6 |
+
"vectorizer_model": {
|
| 7 |
+
"params": {
|
| 8 |
+
"analyzer": "word",
|
| 9 |
+
"binary": false,
|
| 10 |
+
"decode_error": "strict",
|
| 11 |
+
"encoding": "utf-8",
|
| 12 |
+
"input": "content",
|
| 13 |
+
"lowercase": true,
|
| 14 |
+
"max_df": 0.8,
|
| 15 |
+
"max_features": null,
|
| 16 |
+
"min_df": 1,
|
| 17 |
+
"ngram_range": [
|
| 18 |
+
1,
|
| 19 |
+
1
|
| 20 |
+
],
|
| 21 |
+
"stop_words": [
|
| 22 |
+
"acaba",
|
| 23 |
+
"ama",
|
| 24 |
+
"asl\u0131nda",
|
| 25 |
+
"az",
|
| 26 |
+
"baz\u0131",
|
| 27 |
+
"belki",
|
| 28 |
+
"biri",
|
| 29 |
+
"birka\u00e7",
|
| 30 |
+
"bir\u015fey",
|
| 31 |
+
"biz",
|
| 32 |
+
"bu",
|
| 33 |
+
"\u00e7ok",
|
| 34 |
+
"\u00e7\u00fcnk\u00fc",
|
| 35 |
+
"da",
|
| 36 |
+
"daha",
|
| 37 |
+
"de",
|
| 38 |
+
"defa",
|
| 39 |
+
"diye",
|
| 40 |
+
"e\u011fer",
|
| 41 |
+
"en",
|
| 42 |
+
"gibi",
|
| 43 |
+
"hem",
|
| 44 |
+
"hep",
|
| 45 |
+
"hepsi",
|
| 46 |
+
"her",
|
| 47 |
+
"hi\u00e7",
|
| 48 |
+
"i\u00e7in",
|
| 49 |
+
"ile",
|
| 50 |
+
"ise",
|
| 51 |
+
"kez",
|
| 52 |
+
"ki",
|
| 53 |
+
"kim",
|
| 54 |
+
"m\u0131",
|
| 55 |
+
"mu",
|
| 56 |
+
"m\u00fc",
|
| 57 |
+
"nas\u0131l",
|
| 58 |
+
"ne",
|
| 59 |
+
"neden",
|
| 60 |
+
"nerde",
|
| 61 |
+
"nerede",
|
| 62 |
+
"nereye",
|
| 63 |
+
"ni\u00e7in",
|
| 64 |
+
"niye",
|
| 65 |
+
"o",
|
| 66 |
+
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|
| 67 |
+
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|
| 68 |
+
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|
| 69 |
+
"\u015fu",
|
| 70 |
+
"t\u00fcm",
|
| 71 |
+
"ve",
|
| 72 |
+
"veya",
|
| 73 |
+
"ya",
|
| 74 |
+
"yani",
|
| 75 |
+
"muhbirajans"
|
| 76 |
+
],
|
| 77 |
+
"strip_accents": "unicode",
|
| 78 |
+
"token_pattern": "(?u)\\b\\w\\w+\\b",
|
| 79 |
+
"vocabulary": null
|
| 80 |
+
},
|
| 81 |
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|
| 82 |
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|
| 83 |
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|
| 84 |
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|
| 85 |
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|
| 86 |
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|
| 87 |
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|
| 88 |
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|
| 89 |
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|
| 90 |
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| 91 |
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|
| 92 |
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|
| 93 |
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|
| 94 |
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|
| 95 |
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|
| 96 |
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|
| 97 |
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|
| 98 |
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|
| 99 |
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|
| 100 |
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|
| 101 |
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|
| 102 |
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|
| 103 |
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|
| 104 |
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|
| 105 |
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|
| 106 |
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|
| 107 |
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|
| 108 |
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|
| 109 |
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|
| 110 |
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|
| 111 |
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|
| 112 |
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|
| 113 |
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|
| 114 |
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|
| 115 |
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|
| 116 |
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|
| 117 |
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|
| 118 |
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|
| 119 |
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|
| 120 |
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|
| 121 |
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|
| 122 |
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|
| 123 |
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|
| 124 |
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|
| 125 |
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|
| 126 |
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|
| 127 |
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|
| 128 |
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|
| 129 |
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|
| 130 |
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|
| 131 |
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|
| 132 |
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|
| 133 |
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|
| 134 |
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|
| 135 |
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|
| 136 |
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|
| 137 |
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|
| 138 |
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|
| 139 |
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|
| 140 |
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|
| 141 |
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|
| 142 |
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|
| 143 |
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|
| 144 |
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|
| 145 |
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|
| 146 |
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|
| 147 |
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|
| 148 |
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|
| 149 |
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|
| 150 |
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|
| 151 |
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|
| 152 |
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|
| 153 |
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|
| 154 |
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"once": 2511,
|
| 155 |
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|
| 156 |
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|
| 157 |
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|
| 158 |
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|
| 159 |
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|
| 160 |
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|
| 161 |
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|
| 162 |
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|
| 163 |
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|
| 164 |
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|
| 165 |
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|
| 166 |
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|
| 167 |
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|
| 168 |
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|
| 169 |
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|
| 170 |
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|
| 171 |
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|
| 172 |
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|
| 173 |
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|
| 174 |
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|
| 175 |
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|
| 176 |
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|
| 177 |
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|
| 178 |
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|
| 179 |
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|
| 180 |
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|
| 181 |
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|
| 182 |
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|
| 183 |
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|
| 184 |
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|
| 185 |
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|
| 186 |
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"ev": 1232,
|
| 187 |
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|
| 188 |
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"yol": 3579,
|
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|
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|
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|
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| 3773 |
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|
| 3774 |
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}
|
| 3775 |
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}
|
topic_embeddings.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
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|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:2bd2c75d853074c3a002a8056c442b0e6e853399eb06281f4dcd75c156c9c25e
|
| 3 |
+
size 16472
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topics.json
ADDED
|
@@ -0,0 +1,418 @@
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{
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