Datasets:
mteb
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1
  ---
 
 
2
  language:
3
- - en
 
 
 
 
 
 
 
 
 
 
 
4
  ---
 
5
 
6
- 10 sets with the following stats:
 
 
 
 
7
 
8
- 1. 91 labels & 15592 samples
9
- 2. 64 labels & 79172 samples
10
- 3. 38 labels & 1942 samples
11
- 4. 11 labels & 13224 samples
12
- 5. 64 labels & 92303 samples
13
- 6. 87 labels & 28607 samples
14
- 7. 10 labels & 69146 samples
15
- 8. 48 labels & 67469 samples
16
- 9. 64 labels & 29683 samples
17
- 10. 31 labels & 62261 samples
18
 
 
 
 
 
 
19
 
20
- Selected at random using the script available on the mteb github repository.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  ---
2
+ annotations_creators:
3
+ - derived
4
  language:
5
+ - eng
6
+ license: unknown
7
+ multilinguality: monolingual
8
+ source_datasets:
9
+ - mteb/reddit-clustering-p2p
10
+ task_categories:
11
+ - text-clustering
12
+ task_ids:
13
+ - Thematic clustering
14
+ tags:
15
+ - mteb
16
+ - text
17
  ---
18
+ <!-- adapted from https://github.com/huggingface/huggingface_hub/blob/v0.30.2/src/huggingface_hub/templates/datasetcard_template.md -->
19
 
20
+ <div align="center" style="padding: 40px 20px; background-color: white; border-radius: 12px; box-shadow: 0 2px 10px rgba(0, 0, 0, 0.05); max-width: 600px; margin: 0 auto;">
21
+ <h1 style="font-size: 3.5rem; color: #1a1a1a; margin: 0 0 20px 0; letter-spacing: 2px; font-weight: 700;">RedditClusteringP2P.v2</h1>
22
+ <div style="font-size: 1.5rem; color: #4a4a4a; margin-bottom: 5px; font-weight: 300;">An <a href="https://github.com/embeddings-benchmark/mteb" style="color: #2c5282; font-weight: 600; text-decoration: none;" onmouseover="this.style.textDecoration='underline'" onmouseout="this.style.textDecoration='none'">MTEB</a> dataset</div>
23
+ <div style="font-size: 0.9rem; color: #2c5282; margin-top: 10px;">Massive Text Embedding Benchmark</div>
24
+ </div>
25
 
26
+ Clustering of title+posts from reddit. Clustering of 10 sets of 50k paragraphs and 40 sets of 10k paragraphs.
 
 
 
 
 
 
 
 
 
27
 
28
+ | | |
29
+ |---------------|---------------------------------------------|
30
+ | Task category | t2c |
31
+ | Domains | Web, Social, Written |
32
+ | Reference | https://arxiv.org/abs/2104.07081 |
33
 
34
+
35
+ ## How to evaluate on this task
36
+
37
+ You can evaluate an embedding model on this dataset using the following code:
38
+
39
+ ```python
40
+ import mteb
41
+
42
+ task = mteb.get_tasks(["RedditClusteringP2P.v2"])
43
+ evaluator = mteb.MTEB(task)
44
+
45
+ model = mteb.get_model(YOUR_MODEL)
46
+ evaluator.run(model)
47
+ ```
48
+
49
+ <!-- Datasets want link to arxiv in readme to autolink dataset with paper -->
50
+ To learn more about how to run models on `mteb` task check out the [GitHub repitory](https://github.com/embeddings-benchmark/mteb).
51
+
52
+ ## Citation
53
+
54
+ If you use this dataset, please cite the dataset as well as [mteb](https://github.com/embeddings-benchmark/mteb), as this dataset likely includes additional processing as a part of the [MMTEB Contribution](https://github.com/embeddings-benchmark/mteb/tree/main/docs/mmteb).
55
+
56
+ ```bibtex
57
+
58
+ @article{geigle:2021:arxiv,
59
+ archiveprefix = {arXiv},
60
+ author = {Gregor Geigle and
61
+ Nils Reimers and
62
+ Andreas R{\"u}ckl{\'e} and
63
+ Iryna Gurevych},
64
+ eprint = {2104.07081},
65
+ journal = {arXiv preprint},
66
+ title = {TWEAC: Transformer with Extendable QA Agent Classifiers},
67
+ url = {http://arxiv.org/abs/2104.07081},
68
+ volume = {abs/2104.07081},
69
+ year = {2021},
70
+ }
71
+
72
+
73
+ @article{enevoldsen2025mmtebmassivemultilingualtext,
74
+ title={MMTEB: Massive Multilingual Text Embedding Benchmark},
75
+ author={Kenneth Enevoldsen and Isaac Chung and Imene Kerboua and Márton Kardos and Ashwin Mathur and David Stap and Jay Gala and Wissam Siblini and Dominik Krzemiński and Genta Indra Winata and Saba Sturua and Saiteja Utpala and Mathieu Ciancone and Marion Schaeffer and Gabriel Sequeira and Diganta Misra and Shreeya Dhakal and Jonathan Rystrøm and Roman Solomatin and Ömer Çağatan and Akash Kundu and Martin Bernstorff and Shitao Xiao and Akshita Sukhlecha and Bhavish Pahwa and Rafał Poświata and Kranthi Kiran GV and Shawon Ashraf and Daniel Auras and Björn Plüster and Jan Philipp Harries and Loïc Magne and Isabelle Mohr and Mariya Hendriksen and Dawei Zhu and Hippolyte Gisserot-Boukhlef and Tom Aarsen and Jan Kostkan and Konrad Wojtasik and Taemin Lee and Marek Šuppa and Crystina Zhang and Roberta Rocca and Mohammed Hamdy and Andrianos Michail and John Yang and Manuel Faysse and Aleksei Vatolin and Nandan Thakur and Manan Dey and Dipam Vasani and Pranjal Chitale and Simone Tedeschi and Nguyen Tai and Artem Snegirev and Michael Günther and Mengzhou Xia and Weijia Shi and Xing Han Lù and Jordan Clive and Gayatri Krishnakumar and Anna Maksimova and Silvan Wehrli and Maria Tikhonova and Henil Panchal and Aleksandr Abramov and Malte Ostendorff and Zheng Liu and Simon Clematide and Lester James Miranda and Alena Fenogenova and Guangyu Song and Ruqiya Bin Safi and Wen-Ding Li and Alessia Borghini and Federico Cassano and Hongjin Su and Jimmy Lin and Howard Yen and Lasse Hansen and Sara Hooker and Chenghao Xiao and Vaibhav Adlakha and Orion Weller and Siva Reddy and Niklas Muennighoff},
76
+ publisher = {arXiv},
77
+ journal={arXiv preprint arXiv:2502.13595},
78
+ year={2025},
79
+ url={https://arxiv.org/abs/2502.13595},
80
+ doi = {10.48550/arXiv.2502.13595},
81
+ }
82
+
83
+ @article{muennighoff2022mteb,
84
+ author = {Muennighoff, Niklas and Tazi, Nouamane and Magne, Lo{\"\i}c and Reimers, Nils},
85
+ title = {MTEB: Massive Text Embedding Benchmark},
86
+ publisher = {arXiv},
87
+ journal={arXiv preprint arXiv:2210.07316},
88
+ year = {2022}
89
+ url = {https://arxiv.org/abs/2210.07316},
90
+ doi = {10.48550/ARXIV.2210.07316},
91
+ }
92
+ ```
93
+
94
+ # Dataset Statistics
95
+ <details>
96
+ <summary> Dataset Statistics</summary>
97
+
98
+ The following code contains the descriptive statistics from the task. These can also be obtained using:
99
+
100
+ ```python
101
+ import mteb
102
+
103
+ task = mteb.get_task("RedditClusteringP2P.v2")
104
+
105
+ desc_stats = task.metadata.descriptive_stats
106
+ ```
107
+
108
+ ```json
109
+ {
110
+ "test": {
111
+ "num_samples": 459389,
112
+ "number_of_characters": 334286895,
113
+ "min_text_length": 79,
114
+ "average_text_length": 727.6771864367671,
115
+ "max_text_length": 4359,
116
+ "min_labels_per_text": 2,
117
+ "average_labels_per_text": 1.0,
118
+ "max_labels_per_text": 77908,
119
+ "unique_labels": 440,
120
+ "labels": {
121
+ "FortNiteBR": {
122
+ "count": 436
123
+ },
124
+ "buildapc": {
125
+ "count": 8484
126
+ },
127
+ "offmychest": {
128
+ "count": 570
129
+ },
130
+ "nus": {
131
+ "count": 45
132
+ },
133
+ "relationship_advice": {
134
+ "count": 16651
135
+ },
136
+ "premed": {
137
+ "count": 201
138
+ },
139
+ "dogecoin": {
140
+ "count": 8108
141
+ },
142
+ "GamingLaptops": {
143
+ "count": 183
144
+ },
145
+ "asktransgender": {
146
+ "count": 326
147
+ },
148
+ "MachineLearning": {
149
+ "count": 61
150
+ },
151
+ "puppy101": {
152
+ "count": 1597
153
+ },
154
+ "GunAccessoriesForSale": {
155
+ "count": 2619
156
+ },
157
+ "Random_Acts_Of_Amazon": {
158
+ "count": 1115
159
+ },
160
+ "Catholicism": {
161
+ "count": 183
162
+ },
163
+ "MonsterHunter": {
164
+ "count": 218
165
+ },
166
+ "tipofmypenis": {
167
+ "count": 87
168
+ },
169
+ "samsung": {
170
+ "count": 69
171
+ },
172
+ "PersonalFinanceCanada": {
173
+ "count": 341
174
+ },
175
+ "Dyson_Sphere_Program": {
176
+ "count": 55
177
+ },
178
+ "bleach": {
179
+ "count": 41
180
+ },
181
+ "AmItheAsshole": {
182
+ "count": 3730
183
+ },
184
+ "WallStreetbetsELITE": {
185
+ "count": 328
186
+ },
187
+ "GlobalPowers": {
188
+ "count": 35
189
+ },
190
+ "ABraThatFits": {
191
+ "count": 159
192
+ },
193
+ "PokemonGoFriends": {
194
+ "count": 1165
195
+ },
196
+ "NoMansSkyTheGame": {
197
+ "count": 259
198
+ },
199
+ "masseffect": {
200
+ "count": 233
201
+ },
202
+ "dating_advice": {
203
+ "count": 559
204
+ },
205
+ "yoga": {
206
+ "count": 50
207
+ },
208
+ "depression": {
209
+ "count": 515
210
+ },
211
+ "COVID19positive": {
212
+ "count": 180
213
+ },
214
+ "generationology": {
215
+ "count": 37
216
+ },
217
+ "feedthebeast": {
218
+ "count": 192
219
+ },
220
+ "EliteDangerous": {
221
+ "count": 270
222
+ },
223
+ "alcoholicsanonymous": {
224
+ "count": 93
225
+ },
226
+ "GoRVing": {
227
+ "count": 35
228
+ },
229
+ "thedivision": {
230
+ "count": 111
231
+ },
232
+ "breakingmom": {
233
+ "count": 105
234
+ },
235
+ "AskAnAmerican": {
236
+ "count": 80
237
+ },
238
+ "HypnoFair": {
239
+ "count": 5
240
+ },
241
+ "JustUnsubbed": {
242
+ "count": 13
243
+ },
244
+ "socialanxiety": {
245
+ "count": 123
246
+ },
247
+ "dirtykikpals": {
248
+ "count": 202
249
+ },
250
+ "askTO": {
251
+ "count": 126
252
+ },
253
+ "AskCulinary": {
254
+ "count": 108
255
+ },
256
+ "Bogleheads": {
257
+ "count": 71
258
+ },
259
+ "dragonquest": {
260
+ "count": 45
261
+ },
262
+ "NoContract": {
263
+ "count": 30
264
+ },
265
+ "gorillaz": {
266
+ "count": 14
267
+ },
268
+ "MondoGore": {
269
+ "count": 8
270
+ },
271
+ "comicswap": {
272
+ "count": 56
273
+ },
274
+ "VirtualYoutubers": {
275
+ "count": 92
276
+ },
277
+ "Gta5Modding": {
278
+ "count": 28
279
+ },
280
+ "obs": {
281
+ "count": 61
282
+ },
283
+ "vcu": {
284
+ "count": 9
285
+ },
286
+ "KingkillerChronicle": {
287
+ "count": 17
288
+ },
289
+ "AmongUs": {
290
+ "count": 41
291
+ },
292
+ "wireshark": {
293
+ "count": 3
294
+ },
295
+ "Dodocodes": {
296
+ "count": 46
297
+ },
298
+ "Aliexpress": {
299
+ "count": 40
300
+ },
301
+ "LearnerDriverUK": {
302
+ "count": 12
303
+ },
304
+ "PanicAttack": {
305
+ "count": 23
306
+ },
307
+ "KassadinMains": {
308
+ "count": 10
309
+ },
310
+ "islam": {
311
+ "count": 93
312
+ },
313
+ "chronotrigger": {
314
+ "count": 4
315
+ },
316
+ "skincareexchange": {
317
+ "count": 13
318
+ },
319
+ "PokemonHome": {
320
+ "count": 21
321
+ },
322
+ "survivinginfidelity": {
323
+ "count": 71
324
+ },
325
+ "igcse": {
326
+ "count": 21
327
+ },
328
+ "C25K": {
329
+ "count": 21
330
+ },
331
+ "aorus": {
332
+ "count": 2
333
+ },
334
+ "idleon": {
335
+ "count": 19
336
+ },
337
+ "photography": {
338
+ "count": 22
339
+ },
340
+ "cryptocoins": {
341
+ "count": 7
342
+ },
343
+ "CanaryWharfBets": {
344
+ "count": 7
345
+ },
346
+ "KillingEve": {
347
+ "count": 7
348
+ },
349
+ "GameBuilderGarage": {
350
+ "count": 16
351
+ },
352
+ "SauceSharingCommunity": {
353
+ "count": 7
354
+ },
355
+ "turo": {
356
+ "count": 9
357
+ },
358
+ "foodscience": {
359
+ "count": 14
360
+ },
361
+ "HIMYM": {
362
+ "count": 20
363
+ },
364
+ "HauntingOfHillHouse": {
365
+ "count": 4
366
+ },
367
+ "GoodNotes": {
368
+ "count": 8
369
+ },
370
+ "RedditWritesSeinfeld": {
371
+ "count": 6
372
+ },
373
+ "AirReps": {
374
+ "count": 2
375
+ },
376
+ "ADHD": {
377
+ "count": 3811
378
+ },
379
+ "BuddyCrossing": {
380
+ "count": 446
381
+ },
382
+ "libraryofruina": {
383
+ "count": 98
384
+ },
385
+ "SluttyConfessions": {
386
+ "count": 2787
387
+ },
388
+ "tipofmytongue": {
389
+ "count": 7145
390
+ },
391
+ "fleshlight": {
392
+ "count": 128
393
+ },
394
+ "amcstock": {
395
+ "count": 13910
396
+ },
397
+ "teenagers": {
398
+ "count": 77908
399
+ },
400
+ "suggestmeabook": {
401
+ "count": 1540
402
+ },
403
+ "dirtypenpals": {
404
+ "count": 5587
405
+ },
406
+ "MinecraftServer": {
407
+ "count": 177
408
+ },
409
+ "CreditCards": {
410
+ "count": 669
411
+ },
412
+ "Guitar": {
413
+ "count": 10952
414
+ },
415
+ "rpg": {
416
+ "count": 529
417
+ },
418
+ "NoFap": {
419
+ "count": 14853
420
+ },
421
+ "lfg": {
422
+ "count": 1093
423
+ },
424
+ "MarsWallStreet": {
425
+ "count": 935
426
+ },
427
+ "SummonSign": {
428
+ "count": 931
429
+ },
430
+ "AssassinsCreedValhala": {
431
+ "count": 295
432
+ },
433
+ "hoi4": {
434
+ "count": 432
435
+ },
436
+ "Coins4Sale": {
437
+ "count": 260
438
+ },
439
+ "xbox": {
440
+ "count": 459
441
+ },
442
+ "TooAfraidToAsk": {
443
+ "count": 7404
444
+ },
445
+ "NBA2k": {
446
+ "count": 553
447
+ },
448
+ "KGBTR": {
449
+ "count": 943
450
+ },
451
+ "roblox": {
452
+ "count": 220
453
+ },
454
+ "salesforce": {
455
+ "count": 214
456
+ },
457
+ "TwoXChromosomes": {
458
+ "count": 1736
459
+ },
460
+ "mechmarket": {
461
+ "count": 4863
462
+ },
463
+ "Gaming_Headsets": {
464
+ "count": 103
465
+ },
466
+ "pittsburgh": {
467
+ "count": 189
468
+ },
469
+ "CryptoMars": {
470
+ "count": 1606
471
+ },
472
+ "FridayNightFunkin": {
473
+ "count": 378
474
+ },
475
+ "vaginismus": {
476
+ "count": 122
477
+ },
478
+ "transpositive": {
479
+ "count": 10
480
+ },
481
+ "comicbooks": {
482
+ "count": 274
483
+ },
484
+ "BDSMcommunity": {
485
+ "count": 185
486
+ },
487
+ "aliens": {
488
+ "count": 201
489
+ },
490
+ "Scotch": {
491
+ "count": 64
492
+ },
493
+ "KikRoleplay": {
494
+ "count": 141
495
+ },
496
+ "Kayaking": {
497
+ "count": 91
498
+ },
499
+ "196": {
500
+ "count": 47
501
+ },
502
+ "digimon": {
503
+ "count": 140
504
+ },
505
+ "Evernote": {
506
+ "count": 42
507
+ },
508
+ "logh": {
509
+ "count": 22
510
+ },
511
+ "arlington": {
512
+ "count": 15
513
+ },
514
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+ "lockpicking": {
1301
+ "count": 103
1302
+ },
1303
+ "wicked_edge": {
1304
+ "count": 105
1305
+ },
1306
+ "BMW": {
1307
+ "count": 99
1308
+ },
1309
+ "choiceofgames": {
1310
+ "count": 24
1311
+ },
1312
+ "hisdarkmaterials": {
1313
+ "count": 12
1314
+ },
1315
+ "SakuraGakuin": {
1316
+ "count": 24
1317
+ },
1318
+ "detrans": {
1319
+ "count": 55
1320
+ },
1321
+ "Smallville": {
1322
+ "count": 37
1323
+ },
1324
+ "kingofqueens": {
1325
+ "count": 7
1326
+ },
1327
+ "JamesHoffmann": {
1328
+ "count": 22
1329
+ },
1330
+ "stashinvest": {
1331
+ "count": 16
1332
+ },
1333
+ "ABA": {
1334
+ "count": 79
1335
+ },
1336
+ "ladybusiness": {
1337
+ "count": 10
1338
+ },
1339
+ "gamegrumps": {
1340
+ "count": 32
1341
+ },
1342
+ "GodEater": {
1343
+ "count": 21
1344
+ },
1345
+ "tomorrow": {
1346
+ "count": 39
1347
+ },
1348
+ "Tomorrowland": {
1349
+ "count": 9
1350
+ },
1351
+ "BlackCountryNewRoad": {
1352
+ "count": 5
1353
+ },
1354
+ "STAYC": {
1355
+ "count": 3
1356
+ },
1357
+ "SatoshiStreetBets": {
1358
+ "count": 3828
1359
+ },
1360
+ "AskLosAngeles": {
1361
+ "count": 1036
1362
+ },
1363
+ "buildapcforme": {
1364
+ "count": 1689
1365
+ },
1366
+ "ApplyingToCollege": {
1367
+ "count": 10675
1368
+ },
1369
+ "watercooling": {
1370
+ "count": 1209
1371
+ },
1372
+ "BreakUps": {
1373
+ "count": 4914
1374
+ },
1375
+ "FIFA": {
1376
+ "count": 3811
1377
+ },
1378
+ "emacs": {
1379
+ "count": 712
1380
+ },
1381
+ "trakstocks": {
1382
+ "count": 691
1383
+ },
1384
+ "Shittyaskflying": {
1385
+ "count": 147
1386
+ },
1387
+ "AmazonFC": {
1388
+ "count": 1178
1389
+ },
1390
+ "stocks": {
1391
+ "count": 4610
1392
+ },
1393
+ "BangaloreMains": {
1394
+ "count": 26
1395
+ },
1396
+ "pokemon": {
1397
+ "count": 3953
1398
+ },
1399
+ "religion": {
1400
+ "count": 684
1401
+ },
1402
+ "cuboulder": {
1403
+ "count": 269
1404
+ },
1405
+ "self": {
1406
+ "count": 1688
1407
+ },
1408
+ "tarot": {
1409
+ "count": 912
1410
+ },
1411
+ "turtles": {
1412
+ "count": 49
1413
+ },
1414
+ "TheMagnusArchives": {
1415
+ "count": 300
1416
+ },
1417
+ "Superhero_Ideas": {
1418
+ "count": 34
1419
+ },
1420
+ "NTU": {
1421
+ "count": 308
1422
+ },
1423
+ "touhou": {
1424
+ "count": 623
1425
+ },
1426
+ "JoJolion": {
1427
+ "count": 50
1428
+ },
1429
+ "lasers": {
1430
+ "count": 27
1431
+ },
1432
+ "popperpigs": {
1433
+ "count": 67
1434
+ },
1435
+ "aggretsuko": {
1436
+ "count": 20
1437
+ },
1438
+ "Library": {
1439
+ "count": 5
1440
+ }
1441
+ }
1442
+ }
1443
+ }
1444
+ ```
1445
+
1446
+ </details>
1447
+
1448
+ ---
1449
+ *This dataset card was automatically generated using [MTEB](https://github.com/embeddings-benchmark/mteb)*