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
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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27
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+ revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
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2215
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2216
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+ - type: cos_sim_f1
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+ - type: dot_ap
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+ - type: dot_f1
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2231
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2232
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+ value: 60.0
2234
+ - type: euclidean_accuracy
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2236
+ - type: euclidean_ap
2237
+ value: 95.21411049527
2238
+ - type: euclidean_f1
2239
+ value: 91.06090373280944
2240
+ - type: euclidean_precision
2241
+ value: 89.47876447876449
2242
+ - type: euclidean_recall
2243
+ value: 92.7
2244
+ - type: manhattan_accuracy
2245
+ value: 99.81782178217821
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+ - type: manhattan_ap
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+ value: 95.32449994414968
2248
+ - type: manhattan_f1
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+ value: 90.86395233366436
2250
+ - type: manhattan_precision
2251
+ value: 90.23668639053254
2252
+ - type: manhattan_recall
2253
+ value: 91.5
2254
+ - type: max_accuracy
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+ value: 99.81980198019802
2256
+ - type: max_ap
2257
+ value: 95.32449994414968
2258
+ - type: max_f1
2259
+ value: 91.06090373280944
2260
+ - task:
2261
+ type: Clustering
2262
+ dataset:
2263
+ type: mteb/stackexchange-clustering
2264
+ name: MTEB StackExchangeClustering
2265
+ config: default
2266
+ split: test
2267
+ revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
2268
+ metrics:
2269
+ - type: v_measure
2270
+ value: 59.08045614613064
2271
+ - task:
2272
+ type: Clustering
2273
+ dataset:
2274
+ type: mteb/stackexchange-clustering-p2p
2275
+ name: MTEB StackExchangeClusteringP2P
2276
+ config: default
2277
+ split: test
2278
+ revision: 815ca46b2622cec33ccafc3735d572c266efdb44
2279
+ metrics:
2280
+ - type: v_measure
2281
+ value: 30.297802606804748
2282
+ - task:
2283
+ type: Reranking
2284
+ dataset:
2285
+ type: mteb/stackoverflowdupquestions-reranking
2286
+ name: MTEB StackOverflowDupQuestions
2287
+ config: default
2288
+ split: test
2289
+ revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
2290
+ metrics:
2291
+ - type: map
2292
+ value: 49.12801740706292
2293
+ - type: mrr
2294
+ value: 50.05592956879722
2295
+ - task:
2296
+ type: Summarization
2297
+ dataset:
2298
+ type: mteb/summeval
2299
+ name: MTEB SummEval
2300
+ config: default
2301
+ split: test
2302
+ revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
2303
+ metrics:
2304
+ - type: cos_sim_pearson
2305
+ value: 23.380995453661917
2306
+ - type: cos_sim_spearman
2307
+ value: 24.941761858688917
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+ - type: dot_pearson
2309
+ value: 24.930577961642413
2310
+ - type: dot_spearman
2311
+ value: 24.804715835064492
2312
+ - task:
2313
+ type: Retrieval
2314
+ dataset:
2315
+ type: trec-covid
2316
+ name: MTEB TRECCOVID
2317
+ config: default
2318
+ split: test
2319
+ revision: None
2320
+ metrics:
2321
+ - type: map_at_1
2322
+ value: 0.243
2323
+ - type: map_at_10
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+ value: 1.886
2325
+ - type: map_at_100
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+ value: 10.040000000000001
2327
+ - type: map_at_1000
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+ value: 23.768
2329
+ - type: map_at_3
2330
+ value: 0.674
2331
+ - type: map_at_5
2332
+ value: 1.079
2333
+ - type: mrr_at_1
2334
+ value: 88.0
2335
+ - type: mrr_at_10
2336
+ value: 93.667
2337
+ - type: mrr_at_100
2338
+ value: 93.667
2339
+ - type: mrr_at_1000
2340
+ value: 93.667
2341
+ - type: mrr_at_3
2342
+ value: 93.667
2343
+ - type: mrr_at_5
2344
+ value: 93.667
2345
+ - type: ndcg_at_1
2346
+ value: 83.0
2347
+ - type: ndcg_at_10
2348
+ value: 76.777
2349
+ - type: ndcg_at_100
2350
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2351
+ - type: ndcg_at_1000
2352
+ value: 47.912
2353
+ - type: ndcg_at_3
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+ value: 81.358
2355
+ - type: ndcg_at_5
2356
+ value: 80.74799999999999
2357
+ - type: precision_at_1
2358
+ value: 88.0
2359
+ - type: precision_at_10
2360
+ value: 80.80000000000001
2361
+ - type: precision_at_100
2362
+ value: 56.02
2363
+ - type: precision_at_1000
2364
+ value: 21.51
2365
+ - type: precision_at_3
2366
+ value: 86.0
2367
+ - type: precision_at_5
2368
+ value: 86.0
2369
+ - type: recall_at_1
2370
+ value: 0.243
2371
+ - type: recall_at_10
2372
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2373
+ - type: recall_at_100
2374
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2375
+ - type: recall_at_1000
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+ value: 44.433
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+ - type: recall_at_3
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2379
+ - type: recall_at_5
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+ value: 1.1440000000000001
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+ - task:
2382
+ type: Retrieval
2383
+ dataset:
2384
+ type: webis-touche2020
2385
+ name: MTEB Touche2020
2386
+ config: default
2387
+ split: test
2388
+ revision: None
2389
+ metrics:
2390
+ - type: map_at_1
2391
+ value: 3.066
2392
+ - type: map_at_10
2393
+ value: 10.615
2394
+ - type: map_at_100
2395
+ value: 16.463
2396
+ - type: map_at_1000
2397
+ value: 17.815
2398
+ - type: map_at_3
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2400
+ - type: map_at_5
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+ - type: mrr_at_1
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+ - type: mrr_at_10
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+ value: 53.846000000000004
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+ - type: mrr_at_100
2407
+ value: 54.37
2408
+ - type: mrr_at_1000
2409
+ value: 54.37
2410
+ - type: mrr_at_3
2411
+ value: 48.980000000000004
2412
+ - type: mrr_at_5
2413
+ value: 51.735
2414
+ - type: ndcg_at_1
2415
+ value: 34.694
2416
+ - type: ndcg_at_10
2417
+ value: 26.811
2418
+ - type: ndcg_at_100
2419
+ value: 37.342999999999996
2420
+ - type: ndcg_at_1000
2421
+ value: 47.964
2422
+ - type: ndcg_at_3
2423
+ value: 30.906
2424
+ - type: ndcg_at_5
2425
+ value: 27.77
2426
+ - type: precision_at_1
2427
+ value: 38.775999999999996
2428
+ - type: precision_at_10
2429
+ value: 23.878
2430
+ - type: precision_at_100
2431
+ value: 7.632999999999999
2432
+ - type: precision_at_1000
2433
+ value: 1.469
2434
+ - type: precision_at_3
2435
+ value: 31.973000000000003
2436
+ - type: precision_at_5
2437
+ value: 26.939
2438
+ - type: recall_at_1
2439
+ value: 3.066
2440
+ - type: recall_at_10
2441
+ value: 17.112
2442
+ - type: recall_at_100
2443
+ value: 47.723
2444
+ - type: recall_at_1000
2445
+ value: 79.50500000000001
2446
+ - type: recall_at_3
2447
+ value: 6.825
2448
+ - type: recall_at_5
2449
+ value: 9.584
2450
+ - task:
2451
+ type: Classification
2452
+ dataset:
2453
+ type: mteb/toxic_conversations_50k
2454
+ name: MTEB ToxicConversationsClassification
2455
+ config: default
2456
+ split: test
2457
+ revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
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+ metrics:
2459
+ - type: accuracy
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+ value: 72.76460000000002
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+ - type: ap
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+ value: 14.944240012137053
2463
+ - type: f1
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+ value: 55.89805777266571
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+ - task:
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+ type: Classification
2467
+ dataset:
2468
+ type: mteb/tweet_sentiment_extraction
2469
+ name: MTEB TweetSentimentExtractionClassification
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+ config: default
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+ split: test
2472
+ revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
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+ metrics:
2474
+ - type: accuracy
2475
+ value: 63.30503678551217
2476
+ - type: f1
2477
+ value: 63.57492701921179
2478
+ - task:
2479
+ type: Clustering
2480
+ dataset:
2481
+ type: mteb/twentynewsgroups-clustering
2482
+ name: MTEB TwentyNewsgroupsClustering
2483
+ config: default
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+ split: test
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+ revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
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+ metrics:
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+ - type: v_measure
2488
+ value: 37.51066495006874
2489
+ - task:
2490
+ type: PairClassification
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+ dataset:
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+ type: mteb/twittersemeval2015-pairclassification
2493
+ name: MTEB TwitterSemEval2015
2494
+ config: default
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+ split: test
2496
+ revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
2497
+ metrics:
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+ - type: cos_sim_accuracy
2499
+ value: 86.07021517553794
2500
+ - type: cos_sim_ap
2501
+ value: 74.15520712370555
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+ - type: cos_sim_precision
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+ - type: cos_sim_recall
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+ - type: dot_accuracy
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2510
+ - type: dot_ap
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+ - type: dot_f1
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2514
+ - type: dot_precision
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+ value: 46.32525410476936
2516
+ - type: dot_recall
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+ value: 62.532981530343015
2518
+ - type: euclidean_accuracy
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+ value: 86.04637301066937
2520
+ - type: euclidean_ap
2521
+ value: 73.85333854233123
2522
+ - type: euclidean_f1
2523
+ value: 68.77723660599845
2524
+ - type: euclidean_precision
2525
+ value: 66.87437686939182
2526
+ - type: euclidean_recall
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+ value: 70.79155672823218
2528
+ - type: manhattan_accuracy
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+ value: 85.98676759849795
2530
+ - type: manhattan_ap
2531
+ value: 73.56016090035973
2532
+ - type: manhattan_f1
2533
+ value: 68.48878539036647
2534
+ - type: manhattan_precision
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+ value: 63.9505607690547
2536
+ - type: manhattan_recall
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+ value: 73.7203166226913
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+ - type: max_accuracy
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+ value: 86.07021517553794
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+ - type: max_ap
2541
+ value: 74.15520712370555
2542
+ - type: max_f1
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+ value: 68.77723660599845
2544
+ - task:
2545
+ type: PairClassification
2546
+ dataset:
2547
+ type: mteb/twitterurlcorpus-pairclassification
2548
+ name: MTEB TwitterURLCorpus
2549
+ config: default
2550
+ split: test
2551
+ revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
2552
+ metrics:
2553
+ - type: cos_sim_accuracy
2554
+ value: 88.92769821865176
2555
+ - type: cos_sim_ap
2556
+ value: 85.78879502899773
2557
+ - type: cos_sim_f1
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+ value: 78.14414083990464
2559
+ - type: cos_sim_precision
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+ value: 74.61651607480563
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+ - type: cos_sim_recall
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+ value: 82.0218663381583
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+ - type: dot_accuracy
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+ value: 84.95750378390964
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+ - type: dot_ap
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+ value: 75.80219641857563
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+ - type: dot_f1
2568
+ value: 70.13966179585681
2569
+ - type: dot_precision
2570
+ value: 65.71140262361251
2571
+ - type: dot_recall
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+ value: 75.20788420080073
2573
+ - type: euclidean_accuracy
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+ value: 88.93546008460433
2575
+ - type: euclidean_ap
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+ value: 85.72056428301667
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+ - type: euclidean_f1
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+ value: 78.14387902598124
2579
+ - type: euclidean_precision
2580
+ value: 75.3376688344172
2581
+ - type: euclidean_recall
2582
+ value: 81.16723129042192
2583
+ - type: manhattan_accuracy
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+ value: 88.96262661543835
2585
+ - type: manhattan_ap
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+ value: 85.76605136314335
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+ - type: manhattan_f1
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+ value: 78.26696165191743
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+ - type: manhattan_precision
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+ value: 75.0990659496179
2591
+ - type: manhattan_recall
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+ value: 81.71388974437943
2593
+ - type: max_accuracy
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+ value: 88.96262661543835
2595
+ - type: max_ap
2596
+ value: 85.78879502899773
2597
+ - type: max_f1
2598
+ value: 78.26696165191743
2599
+ ---
2600
+
2601
+ ## Usage
2602
+
2603
+ Coming soon
2604
+
config.json ADDED
@@ -0,0 +1,25 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
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+ "_name_or_path": "amlt/1109_tnlrv3_bs32k_ft/all_kd_ft",
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+ "architectures": [
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+ "BertModel"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "classifier_dropout": null,
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+ "hidden_act": "gelu",
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+ "intermediate_size": 1536,
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 0,
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+ "position_embedding_type": "absolute",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.15.0",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 30522
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+ }
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
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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11
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27
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28
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29
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42
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58
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146
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204
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215
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