itlwas commited on
Commit
a056069
·
verified ·
1 Parent(s): 2ab5e2f

Upload README.md with huggingface_hub

Browse files
Files changed (1) hide show
  1. README.md +1026 -0
README.md ADDED
@@ -0,0 +1,1026 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: llama3.2
3
+ language:
4
+ - zh
5
+ - en
6
+ - it
7
+ - de
8
+ - fr
9
+ - ja
10
+ - ko
11
+ base_model: lianghsun/Llama-3.2-Taiwan-3B-Instruct
12
+ datasets:
13
+ - lianghsun/tw-emergency-medicine-bench
14
+ - lianghsun/tw-legal-nlp
15
+ - lianghsun/tw-legal-synthetic-qa
16
+ - lianghsun/tw-law-article-qa
17
+ - lianghsun/tw-judgment-qa
18
+ - lianghsun/tw-judgment-gist-chat
19
+ - lianghsun/tw-bar-examination-2020-chat
20
+ - lianghsun/tw-structured-law-article
21
+ - lianghsun/tw-judgment-gist-chat
22
+ - lianghsun/tw-contract-review-chat
23
+ - lianghsun/reasoning-base-20k-chat
24
+ - lianghsun/vulnerability-mitigation-qa-zh_tw
25
+ - lianghsun/tw-instruct
26
+ - rombodawg/Everything_Instruct_Multilingual
27
+ - xzuyn/manythings-translations-alpaca
28
+ - neural-bridge/rag-dataset-12000
29
+ - minyichen/glaive_toolcall_zh_tw
30
+ pipeline_tag: text-generation
31
+ library_name: transformers
32
+ tags:
33
+ - Taiwan
34
+ - ROC
35
+ - zh-tw
36
+ - instruct
37
+ - chat
38
+ - llama3.2
39
+ - SLM
40
+ - llama-cpp
41
+ - gguf-my-repo
42
+ widget:
43
+ - text: 中華民國憲法第一條
44
+ metrics:
45
+ - accuracy
46
+ model-index:
47
+ - name: Llama-3.2-Taiwan-3B-Instruct
48
+ results:
49
+ - task:
50
+ type: text-generation
51
+ name: Single Choice Question
52
+ dataset:
53
+ name: tw-legal-benchmark-v1
54
+ type: lianghsun/tw-legal-benchmark-v1
55
+ metrics:
56
+ - type: accuracy
57
+ value: 31.1
58
+ name: single choice
59
+ - task:
60
+ type: text-generation
61
+ name: Single Choice Question
62
+ dataset:
63
+ name: (Society) Formosa Taiwan Knowledge Bench
64
+ type: lianghsun/Formosa-bench
65
+ config: society
66
+ split: test
67
+ revision: v2024.11.27
68
+ metrics:
69
+ - type: accuracy
70
+ value: 60.42
71
+ name: single choice
72
+ - task:
73
+ type: text-generation
74
+ name: Single Choice Question
75
+ dataset:
76
+ name: (Governmnt) Formosa Taiwan Knowledge Bench
77
+ type: lianghsun/Formosa-bench
78
+ config: governmnt
79
+ split: test
80
+ revision: v2024.11.27
81
+ metrics:
82
+ - type: accuracy
83
+ value: 44.25
84
+ name: single choice
85
+ - task:
86
+ type: text-generation
87
+ name: Single Choice Question
88
+ dataset:
89
+ name: (Geography) Formosa Taiwan Knowledge Bench
90
+ type: lianghsun/Formosa-bench
91
+ config: geography
92
+ split: test
93
+ revision: v2024.11.27
94
+ metrics:
95
+ - type: accuracy
96
+ value: 47.54
97
+ name: single choice
98
+ - task:
99
+ type: text-generation
100
+ name: Single Choice Question
101
+ dataset:
102
+ name: (History) Formosa Taiwan Knowledge Bench
103
+ type: lianghsun/Formosa-bench
104
+ config: history
105
+ split: test
106
+ revision: v2024.11.27
107
+ metrics:
108
+ - type: accuracy
109
+ value: 60
110
+ name: single choice
111
+ - task:
112
+ type: question-answering
113
+ name: Single Choice Question
114
+ dataset:
115
+ name: (geography_of_taiwan) tmmlu++
116
+ type: ikala/tmmluplus
117
+ config: geography_of_taiwan
118
+ split: test
119
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
120
+ metrics:
121
+ - type: accuracy
122
+ value: 36.2
123
+ name: single choice
124
+ - task:
125
+ type: question-answering
126
+ name: Single Choice Question
127
+ dataset:
128
+ name: (dentistry) tmmlu++
129
+ type: ikala/tmmluplus
130
+ config: dentistry
131
+ split: test
132
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
133
+ metrics:
134
+ - type: accuracy
135
+ value: 33.83
136
+ name: single choice
137
+ - task:
138
+ type: question-answering
139
+ name: Single Choice Question
140
+ dataset:
141
+ name: (technical) tmmlu++
142
+ type: ikala/tmmluplus
143
+ config: technical
144
+ split: test
145
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
146
+ metrics:
147
+ - type: accuracy
148
+ value: 35.07
149
+ name: single choice
150
+ - task:
151
+ type: question-answering
152
+ name: Single Choice Question
153
+ dataset:
154
+ name: (statistics_and_machine_learning) tmmlu++
155
+ type: ikala/tmmluplus
156
+ config: statistics_and_machine_learning
157
+ split: test
158
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
159
+ metrics:
160
+ - type: accuracy
161
+ value: 28.57
162
+ name: single choice
163
+ - task:
164
+ type: question-answering
165
+ name: Single Choice Question
166
+ dataset:
167
+ name: (clinical_psychology) tmmlu++
168
+ type: ikala/tmmluplus
169
+ config: clinical_psychology
170
+ split: test
171
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
172
+ metrics:
173
+ - type: accuracy
174
+ value: 29.6
175
+ name: single choice
176
+ - task:
177
+ type: question-answering
178
+ name: Single Choice Question
179
+ dataset:
180
+ name: (tve_design) tmmlu++
181
+ type: ikala/tmmluplus
182
+ config: tve_design
183
+ split: test
184
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
185
+ metrics:
186
+ - type: accuracy
187
+ value: 38.54
188
+ name: single choice
189
+ - task:
190
+ type: question-answering
191
+ name: Single Choice Question
192
+ dataset:
193
+ name: (three_principles_of_people) tmmlu++
194
+ type: ikala/tmmluplus
195
+ config: three_principles_of_people
196
+ split: test
197
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
198
+ metrics:
199
+ - type: accuracy
200
+ value: 48.2
201
+ name: single choice
202
+ - task:
203
+ type: question-answering
204
+ name: Single Choice Question
205
+ dataset:
206
+ name: (introduction_to_law) tmmlu++
207
+ type: ikala/tmmluplus
208
+ config: introduction_to_law
209
+ split: test
210
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
211
+ metrics:
212
+ - type: accuracy
213
+ value: 29.96
214
+ name: single choice
215
+ - task:
216
+ type: question-answering
217
+ name: Single Choice Question
218
+ dataset:
219
+ name: (linear_algebra) tmmlu++
220
+ type: ikala/tmmluplus
221
+ config: linear_algebra
222
+ split: test
223
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
224
+ metrics:
225
+ - type: accuracy
226
+ value: 21.43
227
+ name: single choice
228
+ - task:
229
+ type: question-answering
230
+ name: Single Choice Question
231
+ dataset:
232
+ name: (agriculture) tmmlu++
233
+ type: ikala/tmmluplus
234
+ config: agriculture
235
+ split: test
236
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
237
+ metrics:
238
+ - type: accuracy
239
+ value: 24.5
240
+ name: single choice
241
+ - task:
242
+ type: question-answering
243
+ name: Single Choice Question
244
+ dataset:
245
+ name: (jce_humanities) tmmlu++
246
+ type: ikala/tmmluplus
247
+ config: jce_humanities
248
+ split: test
249
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
250
+ metrics:
251
+ - type: accuracy
252
+ value: 38.89
253
+ name: single choice
254
+ - task:
255
+ type: question-answering
256
+ name: Single Choice Question
257
+ dataset:
258
+ name: (music) tmmlu++
259
+ type: ikala/tmmluplus
260
+ config: music
261
+ split: test
262
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
263
+ metrics:
264
+ - type: accuracy
265
+ value: 25.9
266
+ name: single choice
267
+ - task:
268
+ type: question-answering
269
+ name: Single Choice Question
270
+ dataset:
271
+ name: (secondary_physics) tmmlu++
272
+ type: ikala/tmmluplus
273
+ config: secondary_physics
274
+ split: test
275
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
276
+ metrics:
277
+ - type: accuracy
278
+ value: 33.04
279
+ name: single choice
280
+ - task:
281
+ type: question-answering
282
+ name: Single Choice Question
283
+ dataset:
284
+ name: (physics) tmmlu++
285
+ type: ikala/tmmluplus
286
+ config: physics
287
+ split: test
288
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
289
+ metrics:
290
+ - type: accuracy
291
+ value: 27.84
292
+ name: single choice
293
+ - task:
294
+ type: question-answering
295
+ name: Single Choice Question
296
+ dataset:
297
+ name: (advance_chemistry) tmmlu++
298
+ type: ikala/tmmluplus
299
+ config: advance_chemistry
300
+ split: test
301
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
302
+ metrics:
303
+ - type: accuracy
304
+ value: 27.64
305
+ name: single choice
306
+ - task:
307
+ type: question-answering
308
+ name: Single Choice Question
309
+ dataset:
310
+ name: (junior_science_exam) tmmlu++
311
+ type: ikala/tmmluplus
312
+ config: junior_science_exam
313
+ split: test
314
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
315
+ metrics:
316
+ - type: accuracy
317
+ value: 30.05
318
+ name: single choice
319
+ - task:
320
+ type: question-answering
321
+ name: Single Choice Question
322
+ dataset:
323
+ name: (veterinary_pathology) tmmlu++
324
+ type: ikala/tmmluplus
325
+ config: veterinary_pathology
326
+ split: test
327
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
328
+ metrics:
329
+ - type: accuracy
330
+ value: 25.09
331
+ name: single choice
332
+ - task:
333
+ type: question-answering
334
+ name: Single Choice Question
335
+ dataset:
336
+ name: (financial_analysis) tmmlu++
337
+ type: ikala/tmmluplus
338
+ config: financial_analysis
339
+ split: test
340
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
341
+ metrics:
342
+ - type: accuracy
343
+ value: 25.13
344
+ name: single choice
345
+ - task:
346
+ type: question-answering
347
+ name: Single Choice Question
348
+ dataset:
349
+ name: (national_protection) tmmlu++
350
+ type: ikala/tmmluplus
351
+ config: national_protection
352
+ split: test
353
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
354
+ metrics:
355
+ - type: accuracy
356
+ value: 42.65
357
+ name: single choice
358
+ - task:
359
+ type: question-answering
360
+ name: Single Choice Question
361
+ dataset:
362
+ name: (macroeconomics) tmmlu++
363
+ type: ikala/tmmluplus
364
+ config: macroeconomics
365
+ split: test
366
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
367
+ metrics:
368
+ - type: accuracy
369
+ value: 26.76
370
+ name: single choice
371
+ - task:
372
+ type: question-answering
373
+ name: Single Choice Question
374
+ dataset:
375
+ name: (politic_science) tmmlu++
376
+ type: ikala/tmmluplus
377
+ config: politic_science
378
+ split: test
379
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
380
+ metrics:
381
+ - type: accuracy
382
+ value: 27.44
383
+ name: single choice
384
+ - task:
385
+ type: question-answering
386
+ name: Single Choice Question
387
+ dataset:
388
+ name: (ttqav2) tmmlu++
389
+ type: ikala/tmmluplus
390
+ config: ttqav2
391
+ split: test
392
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
393
+ metrics:
394
+ - type: accuracy
395
+ value: 61.06
396
+ name: single choice
397
+ - task:
398
+ type: question-answering
399
+ name: Single Choice Question
400
+ dataset:
401
+ name: (junior_chinese_exam) tmmlu++
402
+ type: ikala/tmmluplus
403
+ config: junior_chinese_exam
404
+ split: test
405
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
406
+ metrics:
407
+ - type: accuracy
408
+ value: 30.86
409
+ name: single choice
410
+ - task:
411
+ type: question-answering
412
+ name: Single Choice Question
413
+ dataset:
414
+ name: (traditional_chinese_medicine_clinical_medicine) tmmlu++
415
+ type: ikala/tmmluplus
416
+ config: traditional_chinese_medicine_clinical_medicine
417
+ split: test
418
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
419
+ metrics:
420
+ - type: accuracy
421
+ value: 25.9
422
+ name: single choice
423
+ - task:
424
+ type: question-answering
425
+ name: Single Choice Question
426
+ dataset:
427
+ name: (junior_math_exam) tmmlu++
428
+ type: ikala/tmmluplus
429
+ config: junior_math_exam
430
+ split: test
431
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
432
+ metrics:
433
+ - type: accuracy
434
+ value: 21.71
435
+ name: single choice
436
+ - task:
437
+ type: question-answering
438
+ name: Single Choice Question
439
+ dataset:
440
+ name: (auditing) tmmlu++
441
+ type: ikala/tmmluplus
442
+ config: auditing
443
+ split: test
444
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
445
+ metrics:
446
+ - type: accuracy
447
+ value: 21.82
448
+ name: single choice
449
+ - task:
450
+ type: question-answering
451
+ name: Single Choice Question
452
+ dataset:
453
+ name: (anti_money_laundering) tmmlu++
454
+ type: ikala/tmmluplus
455
+ config: anti_money_laundering
456
+ split: test
457
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
458
+ metrics:
459
+ - type: accuracy
460
+ value: 37.31
461
+ name: single choice
462
+ - task:
463
+ type: question-answering
464
+ name: Single Choice Question
465
+ dataset:
466
+ name: (pharmacology) tmmlu++
467
+ type: ikala/tmmluplus
468
+ config: pharmacology
469
+ split: test
470
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
471
+ metrics:
472
+ - type: accuracy
473
+ value: 30.68
474
+ name: single choice
475
+ - task:
476
+ type: question-answering
477
+ name: Single Choice Question
478
+ dataset:
479
+ name: (trust_practice) tmmlu++
480
+ type: ikala/tmmluplus
481
+ config: trust_practice
482
+ split: test
483
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
484
+ metrics:
485
+ - type: accuracy
486
+ value: 28.18
487
+ name: single choice
488
+ - task:
489
+ type: question-answering
490
+ name: Single Choice Question
491
+ dataset:
492
+ name: (tve_mathematics) tmmlu++
493
+ type: ikala/tmmluplus
494
+ config: tve_mathematics
495
+ split: test
496
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
497
+ metrics:
498
+ - type: accuracy
499
+ value: 18.67
500
+ name: single choice
501
+ - task:
502
+ type: question-answering
503
+ name: Single Choice Question
504
+ dataset:
505
+ name: (human_behavior) tmmlu++
506
+ type: ikala/tmmluplus
507
+ config: human_behavior
508
+ split: test
509
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
510
+ metrics:
511
+ - type: accuracy
512
+ value: 32.04
513
+ name: single choice
514
+ - task:
515
+ type: question-answering
516
+ name: Single Choice Question
517
+ dataset:
518
+ name: (pharmacy) tmmlu++
519
+ type: ikala/tmmluplus
520
+ config: pharmacy
521
+ split: test
522
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
523
+ metrics:
524
+ - type: accuracy
525
+ value: 22.76
526
+ name: single choice
527
+ - task:
528
+ type: question-answering
529
+ name: Single Choice Question
530
+ dataset:
531
+ name: (tve_chinese_language) tmmlu++
532
+ type: ikala/tmmluplus
533
+ config: tve_chinese_language
534
+ split: test
535
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
536
+ metrics:
537
+ - type: accuracy
538
+ value: 36.65
539
+ name: single choice
540
+ - task:
541
+ type: question-answering
542
+ name: Single Choice Question
543
+ dataset:
544
+ name: (optometry) tmmlu++
545
+ type: ikala/tmmluplus
546
+ config: optometry
547
+ split: test
548
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
549
+ metrics:
550
+ - type: accuracy
551
+ value: 25.11
552
+ name: single choice
553
+ - task:
554
+ type: question-answering
555
+ name: Single Choice Question
556
+ dataset:
557
+ name: (physical_education) tmmlu++
558
+ type: ikala/tmmluplus
559
+ config: physical_education
560
+ split: test
561
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
562
+ metrics:
563
+ - type: accuracy
564
+ value: 30.73
565
+ name: single choice
566
+ - task:
567
+ type: question-answering
568
+ name: Single Choice Question
569
+ dataset:
570
+ name: (organic_chemistry) tmmlu++
571
+ type: ikala/tmmluplus
572
+ config: organic_chemistry
573
+ split: test
574
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
575
+ metrics:
576
+ - type: accuracy
577
+ value: 35.78
578
+ name: single choice
579
+ - task:
580
+ type: question-answering
581
+ name: Single Choice Question
582
+ dataset:
583
+ name: (tve_natural_sciences) tmmlu++
584
+ type: ikala/tmmluplus
585
+ config: tve_natural_sciences
586
+ split: test
587
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
588
+ metrics:
589
+ - type: accuracy
590
+ value: 33.73
591
+ name: single choice
592
+ - task:
593
+ type: question-answering
594
+ name: Single Choice Question
595
+ dataset:
596
+ name: (education) tmmlu++
597
+ type: ikala/tmmluplus
598
+ config: education
599
+ split: test
600
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
601
+ metrics:
602
+ - type: accuracy
603
+ value: 37.9
604
+ name: single choice
605
+ - task:
606
+ type: question-answering
607
+ name: Single Choice Question
608
+ dataset:
609
+ name: (mechanical) tmmlu++
610
+ type: ikala/tmmluplus
611
+ config: mechanical
612
+ split: test
613
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
614
+ metrics:
615
+ - type: accuracy
616
+ value: 42.37
617
+ name: single choice
618
+ - task:
619
+ type: question-answering
620
+ name: Single Choice Question
621
+ dataset:
622
+ name: (taiwanese_hokkien) tmmlu++
623
+ type: ikala/tmmluplus
624
+ config: taiwanese_hokkien
625
+ split: test
626
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
627
+ metrics:
628
+ - type: accuracy
629
+ value: 14.73
630
+ name: single choice
631
+ - task:
632
+ type: question-answering
633
+ name: Single Choice Question
634
+ dataset:
635
+ name: (nautical_science) tmmlu++
636
+ type: ikala/tmmluplus
637
+ config: nautical_science
638
+ split: test
639
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
640
+ metrics:
641
+ - type: accuracy
642
+ value: 30.49
643
+ name: single choice
644
+ - task:
645
+ type: question-answering
646
+ name: Single Choice Question
647
+ dataset:
648
+ name: (business_management) tmmlu++
649
+ type: ikala/tmmluplus
650
+ config: business_management
651
+ split: test
652
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
653
+ metrics:
654
+ - type: accuracy
655
+ value: 39.57
656
+ name: single choice
657
+ - task:
658
+ type: question-answering
659
+ name: Single Choice Question
660
+ dataset:
661
+ name: (logic_reasoning) tmmlu++
662
+ type: ikala/tmmluplus
663
+ config: logic_reasoning
664
+ split: test
665
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
666
+ metrics:
667
+ - type: accuracy
668
+ value: 27.34
669
+ name: single choice
670
+ - task:
671
+ type: question-answering
672
+ name: Single Choice Question
673
+ dataset:
674
+ name: (marketing_management) tmmlu++
675
+ type: ikala/tmmluplus
676
+ config: marketing_management
677
+ split: test
678
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
679
+ metrics:
680
+ - type: accuracy
681
+ value: 39.78
682
+ name: single choice
683
+ - task:
684
+ type: question-answering
685
+ name: Single Choice Question
686
+ dataset:
687
+ name: (economics) tmmlu++
688
+ type: ikala/tmmluplus
689
+ config: economics
690
+ split: test
691
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
692
+ metrics:
693
+ - type: accuracy
694
+ value: 25.95
695
+ name: single choice
696
+ - task:
697
+ type: question-answering
698
+ name: Single Choice Question
699
+ dataset:
700
+ name: (basic_medical_science) tmmlu++
701
+ type: ikala/tmmluplus
702
+ config: basic_medical_science
703
+ split: test
704
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
705
+ metrics:
706
+ - type: accuracy
707
+ value: 28.41
708
+ name: single choice
709
+ - task:
710
+ type: question-answering
711
+ name: Single Choice Question
712
+ dataset:
713
+ name: (occupational_therapy_for_psychological_disorders) tmmlu++
714
+ type: ikala/tmmluplus
715
+ config: occupational_therapy_for_psychological_disorders
716
+ split: test
717
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
718
+ metrics:
719
+ - type: accuracy
720
+ value: 35.73
721
+ name: single choice
722
+ - task:
723
+ type: question-answering
724
+ name: Single Choice Question
725
+ dataset:
726
+ name: (general_principles_of_law) tmmlu++
727
+ type: ikala/tmmluplus
728
+ config: general_principles_of_law
729
+ split: test
730
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
731
+ metrics:
732
+ - type: accuracy
733
+ value: 31.13
734
+ name: single choice
735
+ - task:
736
+ type: question-answering
737
+ name: Single Choice Question
738
+ dataset:
739
+ name: (junior_chemistry) tmmlu++
740
+ type: ikala/tmmluplus
741
+ config: junior_chemistry
742
+ split: test
743
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
744
+ metrics:
745
+ - type: accuracy
746
+ value: 24.88
747
+ name: single choice
748
+ - task:
749
+ type: question-answering
750
+ name: Single Choice Question
751
+ dataset:
752
+ name: (veterinary_pharmacology) tmmlu++
753
+ type: ikala/tmmluplus
754
+ config: veterinary_pharmacology
755
+ split: test
756
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
757
+ metrics:
758
+ - type: accuracy
759
+ value: 36.3
760
+ name: single choice
761
+ - task:
762
+ type: question-answering
763
+ name: Single Choice Question
764
+ dataset:
765
+ name: (educational_psychology) tmmlu++
766
+ type: ikala/tmmluplus
767
+ config: educational_psychology
768
+ split: test
769
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
770
+ metrics:
771
+ - type: accuracy
772
+ value: 33.52
773
+ name: single choice
774
+ - task:
775
+ type: question-answering
776
+ name: Single Choice Question
777
+ dataset:
778
+ name: (finance_banking) tmmlu++
779
+ type: ikala/tmmluplus
780
+ config: finance_banking
781
+ split: test
782
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
783
+ metrics:
784
+ - type: accuracy
785
+ value: 32.59
786
+ name: single choice
787
+ - task:
788
+ type: question-answering
789
+ name: Single Choice Question
790
+ dataset:
791
+ name: (official_document_management) tmmlu++
792
+ type: ikala/tmmluplus
793
+ config: official_document_management
794
+ split: test
795
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
796
+ metrics:
797
+ - type: accuracy
798
+ value: 32.43
799
+ name: single choice
800
+ - task:
801
+ type: question-answering
802
+ name: Single Choice Question
803
+ dataset:
804
+ name: (fire_science) tmmlu++
805
+ type: ikala/tmmluplus
806
+ config: fire_science
807
+ split: test
808
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
809
+ metrics:
810
+ - type: accuracy
811
+ value: 30.65
812
+ name: single choice
813
+ - task:
814
+ type: question-answering
815
+ name: Single Choice Question
816
+ dataset:
817
+ name: (junior_social_studies) tmmlu++
818
+ type: ikala/tmmluplus
819
+ config: junior_social_studies
820
+ split: test
821
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
822
+ metrics:
823
+ - type: accuracy
824
+ value: 47.62
825
+ name: single choice
826
+ - task:
827
+ type: question-answering
828
+ name: Single Choice Question
829
+ dataset:
830
+ name: (accounting) tmmlu++
831
+ type: ikala/tmmluplus
832
+ config: accounting
833
+ split: test
834
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
835
+ metrics:
836
+ - type: accuracy
837
+ value: 20.94
838
+ name: single choice
839
+ - task:
840
+ type: question-answering
841
+ name: Single Choice Question
842
+ dataset:
843
+ name: (engineering_math) tmmlu++
844
+ type: ikala/tmmluplus
845
+ config: engineering_math
846
+ split: test
847
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
848
+ metrics:
849
+ - type: accuracy
850
+ value: 27.18
851
+ name: single choice
852
+ - task:
853
+ type: question-answering
854
+ name: Single Choice Question
855
+ dataset:
856
+ name: (education_(profession_level)) tmmlu++
857
+ type: ikala/tmmluplus
858
+ config: education_(profession_level)
859
+ split: test
860
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
861
+ metrics:
862
+ - type: accuracy
863
+ value: 24.07
864
+ name: single choice
865
+ - task:
866
+ type: question-answering
867
+ name: Single Choice Question
868
+ dataset:
869
+ name: (chinese_language_and_literature) tmmlu++
870
+ type: ikala/tmmluplus
871
+ config: chinese_language_and_literature
872
+ split: test
873
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
874
+ metrics:
875
+ - type: accuracy
876
+ value: 27.64
877
+ name: single choice
878
+ - task:
879
+ type: question-answering
880
+ name: Single Choice Question
881
+ dataset:
882
+ name: (management_accounting) tmmlu++
883
+ type: ikala/tmmluplus
884
+ config: management_accounting
885
+ split: test
886
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
887
+ metrics:
888
+ - type: accuracy
889
+ value: 24.19
890
+ name: single choice
891
+ - task:
892
+ type: question-answering
893
+ name: Single Choice Question
894
+ dataset:
895
+ name: (culinary_skills) tmmlu++
896
+ type: ikala/tmmluplus
897
+ config: culinary_skills
898
+ split: test
899
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
900
+ metrics:
901
+ - type: accuracy
902
+ value: 39.38
903
+ name: single choice
904
+ - task:
905
+ type: question-answering
906
+ name: Single Choice Question
907
+ dataset:
908
+ name: (administrative_law) tmmlu++
909
+ type: ikala/tmmluplus
910
+ config: administrative_law
911
+ split: test
912
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
913
+ metrics:
914
+ - type: accuracy
915
+ value: 25.71
916
+ name: single choice
917
+ - task:
918
+ type: question-answering
919
+ name: Single Choice Question
920
+ dataset:
921
+ name: (insurance_studies) tmmlu++
922
+ type: ikala/tmmluplus
923
+ config: insurance_studies
924
+ split: test
925
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
926
+ metrics:
927
+ - type: accuracy
928
+ value: 33.42
929
+ name: single choice
930
+ - task:
931
+ type: question-answering
932
+ name: Single Choice Question
933
+ dataset:
934
+ name: (real_estate) tmmlu++
935
+ type: ikala/tmmluplus
936
+ config: real_estate
937
+ split: test
938
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
939
+ metrics:
940
+ - type: accuracy
941
+ value: 22.83
942
+ name: single choice
943
+ - task:
944
+ type: question-answering
945
+ name: Single Choice Question
946
+ dataset:
947
+ name: (computer_science) tmmlu++
948
+ type: ikala/tmmluplus
949
+ config: computer_science
950
+ split: test
951
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
952
+ metrics:
953
+ - type: accuracy
954
+ value: 31.61
955
+ name: single choice
956
+ - task:
957
+ type: question-answering
958
+ name: Single Choice Question
959
+ dataset:
960
+ name: (taxation) tmmlu++
961
+ type: ikala/tmmluplus
962
+ config: taxation
963
+ split: test
964
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
965
+ metrics:
966
+ - type: accuracy
967
+ value: 27.47
968
+ name: single choice
969
+ - task:
970
+ type: question-answering
971
+ name: Single Choice Question
972
+ dataset:
973
+ name: (trade) tmmlu++
974
+ type: ikala/tmmluplus
975
+ config: trade
976
+ split: test
977
+ revision: c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
978
+ metrics:
979
+ - type: accuracy
980
+ value: 20.32
981
+ name: single choice
982
+ ---
983
+
984
+ # itlwas/Llama-3.2-Taiwan-3B-Instruct-Q4_K_M-GGUF
985
+ This model was converted to GGUF format from [`lianghsun/Llama-3.2-Taiwan-3B-Instruct`](https://huggingface.co/lianghsun/Llama-3.2-Taiwan-3B-Instruct) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
986
+ Refer to the [original model card](https://huggingface.co/lianghsun/Llama-3.2-Taiwan-3B-Instruct) for more details on the model.
987
+
988
+ ## Use with llama.cpp
989
+ Install llama.cpp through brew (works on Mac and Linux)
990
+
991
+ ```bash
992
+ brew install llama.cpp
993
+
994
+ ```
995
+ Invoke the llama.cpp server or the CLI.
996
+
997
+ ### CLI:
998
+ ```bash
999
+ llama-cli --hf-repo itlwas/Llama-3.2-Taiwan-3B-Instruct-Q4_K_M-GGUF --hf-file llama-3.2-taiwan-3b-instruct-q4_k_m.gguf -p "The meaning to life and the universe is"
1000
+ ```
1001
+
1002
+ ### Server:
1003
+ ```bash
1004
+ llama-server --hf-repo itlwas/Llama-3.2-Taiwan-3B-Instruct-Q4_K_M-GGUF --hf-file llama-3.2-taiwan-3b-instruct-q4_k_m.gguf -c 2048
1005
+ ```
1006
+
1007
+ Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
1008
+
1009
+ Step 1: Clone llama.cpp from GitHub.
1010
+ ```
1011
+ git clone https://github.com/ggerganov/llama.cpp
1012
+ ```
1013
+
1014
+ Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
1015
+ ```
1016
+ cd llama.cpp && LLAMA_CURL=1 make
1017
+ ```
1018
+
1019
+ Step 3: Run inference through the main binary.
1020
+ ```
1021
+ ./llama-cli --hf-repo itlwas/Llama-3.2-Taiwan-3B-Instruct-Q4_K_M-GGUF --hf-file llama-3.2-taiwan-3b-instruct-q4_k_m.gguf -p "The meaning to life and the universe is"
1022
+ ```
1023
+ or
1024
+ ```
1025
+ ./llama-server --hf-repo itlwas/Llama-3.2-Taiwan-3B-Instruct-Q4_K_M-GGUF --hf-file llama-3.2-taiwan-3b-instruct-q4_k_m.gguf -c 2048
1026
+ ```