Hugging Face's logo

llmware
/
industry-bert-contracts-ov

OpenVINO
bert
green
p1
llmware-encoder
ov
Model card Files Community
doberst commited on
Commit
112a83a
•
1 Parent(s): 8689c51

Upload 9 files

Browse files
Files changed (9) hide show
  1. config.json +27 -0
  2. openvino_model.bin +3 -0
  3. openvino_model.xml +0 -0
  4. openvino_tokenizer.bin +3 -0
  5. openvino_tokenizer.xml +817 -0
  6. special_tokens_map.json +7 -0
  7. tokenizer.json +0 -0
  8. tokenizer_config.json +62 -0
  9. vocab.txt +0 -0
config.json ADDED
@@ -0,0 +1,27 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "llmware/industry-bert-contracts-v0.1",
3
+ "architectures": [
4
+ "BertModel"
5
+ ],
6
+ "attention_probs_dropout_prob": 0.1,
7
+ "classifier_dropout": null,
8
+ "description": "Sentence transformer embedding model finetuned on wide range of commercial contracts and related legal materials",
9
+ "gradient_checkpointing": false,
10
+ "hidden_act": "gelu",
11
+ "hidden_dropout_prob": 0.1,
12
+ "hidden_size": 768,
13
+ "initializer_range": 0.02,
14
+ "intermediate_size": 3072,
15
+ "layer_norm_eps": 1e-12,
16
+ "max_position_embeddings": 512,
17
+ "model_name": "industry-bert-contracts-v0.1",
18
+ "model_type": "bert",
19
+ "num_attention_heads": 12,
20
+ "num_hidden_layers": 12,
21
+ "pad_token_id": 0,
22
+ "position_embedding_type": "absolute",
23
+ "transformers_version": "4.41.2",
24
+ "type_vocab_size": 2,
25
+ "use_cache": true,
26
+ "vocab_size": 30522
27
+ }
openvino_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c268f1650273b5484541a17f9cdf9d67256b4ff128d8be55dd4d3a3d6b458683
3
+ size 77965700
openvino_model.xml ADDED
The diff for this file is too large to render. See raw diff
 
openvino_tokenizer.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:894fba85fad2fd0adb66c78d39a774551537fc1293b0910431d70a8d047163ee
3
+ size 323338
openvino_tokenizer.xml ADDED
@@ -0,0 +1,817 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ <?xml version="1.0"?>
2
+ <net name="tokenizer" version="11">
3
+ <layers>
4
+ <layer id="0" name="Parameter_11087" type="Parameter" version="opset1">
5
+ <data shape="?" element_type="string" />
6
+ <output>
7
+ <port id="0" precision="STRING" names="Parameter_11087">
8
+ <dim>-1</dim>
9
+ </port>
10
+ </output>
11
+ </layer>
12
+ <layer id="1" name="Constant_11185" type="Const" version="opset1">
13
+ <data element_type="i32" shape="" offset="0" size="4" />
14
+ <output>
15
+ <port id="0" precision="I32" />
16
+ </output>
17
+ </layer>
18
+ <layer id="2" name="Constant_11186" type="Const" version="opset1">
19
+ <data element_type="i32" shape="" offset="4" size="4" />
20
+ <output>
21
+ <port id="0" precision="I32" />
22
+ </output>
23
+ </layer>
24
+ <layer id="3" name="Constant_11187" type="Const" version="opset1">
25
+ <data element_type="i32" shape="1" offset="8" size="4" />
26
+ <output>
27
+ <port id="0" precision="I32">
28
+ <dim>1</dim>
29
+ </port>
30
+ </output>
31
+ </layer>
32
+ <layer id="4" name="Constant_11100" type="Const" version="opset1">
33
+ <data element_type="i32" shape="" offset="0" size="4" />
34
+ <output>
35
+ <port id="0" precision="I32" />
36
+ </output>
37
+ </layer>
38
+ <layer id="5" name="StringTensorUnpack_11088" type="StringTensorUnpack" version="extension">
39
+ <data mode="begins_ends" />
40
+ <input>
41
+ <port id="0" precision="STRING">
42
+ <dim>-1</dim>
43
+ </port>
44
+ </input>
45
+ <output>
46
+ <port id="1" precision="I32">
47
+ <dim>-1</dim>
48
+ </port>
49
+ <port id="2" precision="I32">
50
+ <dim>-1</dim>
51
+ </port>
52
+ <port id="3" precision="U8">
53
+ <dim>-1</dim>
54
+ </port>
55
+ </output>
56
+ </layer>
57
+ <layer id="6" name="NormalizeUnicode_11089" type="NormalizeUnicode" version="extension">
58
+ <data normalization_form="NFD" />
59
+ <input>
60
+ <port id="0" precision="I32">
61
+ <dim>-1</dim>
62
+ </port>
63
+ <port id="1" precision="I32">
64
+ <dim>-1</dim>
65
+ </port>
66
+ <port id="2" precision="U8">
67
+ <dim>-1</dim>
68
+ </port>
69
+ </input>
70
+ <output>
71
+ <port id="3" precision="I32">
72
+ <dim>-1</dim>
73
+ </port>
74
+ <port id="4" precision="I32">
75
+ <dim>-1</dim>
76
+ </port>
77
+ <port id="5" precision="U8">
78
+ <dim>-1</dim>
79
+ </port>
80
+ </output>
81
+ </layer>
82
+ <layer id="7" name="Constant_11091" type="Const" version="opset1">
83
+ <data element_type="u8" shape="6" offset="12" size="6" />
84
+ <output>
85
+ <port id="0" precision="U8">
86
+ <dim>6</dim>
87
+ </port>
88
+ </output>
89
+ </layer>
90
+ <layer id="8" name="Constant_11093" type="Const" version="opset1">
91
+ <data element_type="u8" shape="0" offset="18" size="1" />
92
+ <output>
93
+ <port id="0" precision="U8">
94
+ <dim>0</dim>
95
+ </port>
96
+ </output>
97
+ </layer>
98
+ <layer id="9" name="RegexNormalization_11094" type="RegexNormalization" version="extension">
99
+ <data global_replace="true" />
100
+ <input>
101
+ <port id="0" precision="I32">
102
+ <dim>-1</dim>
103
+ </port>
104
+ <port id="1" precision="I32">
105
+ <dim>-1</dim>
106
+ </port>
107
+ <port id="2" precision="U8">
108
+ <dim>-1</dim>
109
+ </port>
110
+ <port id="3" precision="U8">
111
+ <dim>6</dim>
112
+ </port>
113
+ <port id="4" precision="U8">
114
+ <dim>0</dim>
115
+ </port>
116
+ </input>
117
+ <output>
118
+ <port id="5" precision="I32">
119
+ <dim>-1</dim>
120
+ </port>
121
+ <port id="6" precision="I32">
122
+ <dim>-1</dim>
123
+ </port>
124
+ <port id="7" precision="U8">
125
+ <dim>-1</dim>
126
+ </port>
127
+ </output>
128
+ </layer>
129
+ <layer id="10" name="CaseFold_11095" type="CaseFold" version="extension">
130
+ <data encoding="utf-8" />
131
+ <input>
132
+ <port id="0" precision="I32">
133
+ <dim>-1</dim>
134
+ </port>
135
+ <port id="1" precision="I32">
136
+ <dim>-1</dim>
137
+ </port>
138
+ <port id="2" precision="U8">
139
+ <dim>-1</dim>
140
+ </port>
141
+ </input>
142
+ <output>
143
+ <port id="3" precision="I32">
144
+ <dim>-1</dim>
145
+ </port>
146
+ <port id="4" precision="I32">
147
+ <dim>-1</dim>
148
+ </port>
149
+ <port id="5" precision="U8">
150
+ <dim>-1</dim>
151
+ </port>
152
+ </output>
153
+ </layer>
154
+ <layer id="11" name="ShapeOf_11096" type="ShapeOf" version="opset3">
155
+ <data output_type="i64" />
156
+ <input>
157
+ <port id="0" precision="I32">
158
+ <dim>-1</dim>
159
+ </port>
160
+ </input>
161
+ <output>
162
+ <port id="1" precision="I64">
163
+ <dim>1</dim>
164
+ </port>
165
+ </output>
166
+ </layer>
167
+ <layer id="12" name="Constant_11097" type="Const" version="opset1">
168
+ <data element_type="i32" shape="" offset="0" size="4" />
169
+ <output>
170
+ <port id="0" precision="I32" />
171
+ </output>
172
+ </layer>
173
+ <layer id="13" name="Constant_11098" type="Const" version="opset1">
174
+ <data element_type="i32" shape="" offset="0" size="4" />
175
+ <output>
176
+ <port id="0" precision="I32" />
177
+ </output>
178
+ </layer>
179
+ <layer id="14" name="Gather_11099" type="Gather" version="opset8">
180
+ <data batch_dims="0" />
181
+ <input>
182
+ <port id="0" precision="I64">
183
+ <dim>1</dim>
184
+ </port>
185
+ <port id="1" precision="I32" />
186
+ <port id="2" precision="I32" />
187
+ </input>
188
+ <output>
189
+ <port id="3" precision="I64" />
190
+ </output>
191
+ </layer>
192
+ <layer id="15" name="Constant_11101" type="Const" version="opset1">
193
+ <data element_type="i32" shape="" offset="4" size="4" />
194
+ <output>
195
+ <port id="0" precision="I32" />
196
+ </output>
197
+ </layer>
198
+ <layer id="16" name="Range_11102" type="Range" version="opset4">
199
+ <data output_type="i32" />
200
+ <input>
201
+ <port id="0" precision="I32" />
202
+ <port id="1" precision="I64" />
203
+ <port id="2" precision="I32" />
204
+ </input>
205
+ <output>
206
+ <port id="3" precision="I32">
207
+ <dim>-1</dim>
208
+ </port>
209
+ </output>
210
+ </layer>
211
+ <layer id="17" name="Constant_11104" type="Const" version="opset1">
212
+ <data element_type="i32" shape="" offset="4" size="4" />
213
+ <output>
214
+ <port id="0" precision="I32" />
215
+ </output>
216
+ </layer>
217
+ <layer id="18" name="Constant_11105" type="Const" version="opset1">
218
+ <data element_type="i64" shape="" offset="19" size="8" />
219
+ <output>
220
+ <port id="0" precision="I64" />
221
+ </output>
222
+ </layer>
223
+ <layer id="19" name="Add_11106" type="Add" version="opset1">
224
+ <data auto_broadcast="numpy" />
225
+ <input>
226
+ <port id="0" precision="I64" />
227
+ <port id="1" precision="I64" />
228
+ </input>
229
+ <output>
230
+ <port id="2" precision="I64" />
231
+ </output>
232
+ </layer>
233
+ <layer id="20" name="Constant_11107" type="Const" version="opset1">
234
+ <data element_type="i32" shape="" offset="4" size="4" />
235
+ <output>
236
+ <port id="0" precision="I32" />
237
+ </output>
238
+ </layer>
239
+ <layer id="21" name="Range_11108" type="Range" version="opset4">
240
+ <data output_type="i32" />
241
+ <input>
242
+ <port id="0" precision="I32" />
243
+ <port id="1" precision="I64" />
244
+ <port id="2" precision="I32" />
245
+ </input>
246
+ <output>
247
+ <port id="3" precision="I32">
248
+ <dim>-1</dim>
249
+ </port>
250
+ </output>
251
+ </layer>
252
+ <layer id="22" name="Constant_11171" type="Const" version="opset1">
253
+ <data element_type="u8" shape="3" offset="27" size="3" />
254
+ <output>
255
+ <port id="0" precision="U8">
256
+ <dim>3</dim>
257
+ </port>
258
+ </output>
259
+ </layer>
260
+ <layer id="23" name="RegexSplit_11172" type="RegexSplit" version="extension">
261
+ <data behaviour="remove" invert="false" max_splits="-1" />
262
+ <input>
263
+ <port id="0" precision="I32">
264
+ <dim>-1</dim>
265
+ </port>
266
+ <port id="1" precision="I32">
267
+ <dim>-1</dim>
268
+ </port>
269
+ <port id="2" precision="I32">
270
+ <dim>-1</dim>
271
+ </port>
272
+ <port id="3" precision="I32">
273
+ <dim>-1</dim>
274
+ </port>
275
+ <port id="4" precision="U8">
276
+ <dim>-1</dim>
277
+ </port>
278
+ <port id="5" precision="U8">
279
+ <dim>3</dim>
280
+ </port>
281
+ </input>
282
+ <output>
283
+ <port id="6" precision="I32">
284
+ <dim>-1</dim>
285
+ </port>
286
+ <port id="7" precision="I32">
287
+ <dim>-1</dim>
288
+ </port>
289
+ <port id="8" precision="I32">
290
+ <dim>-1</dim>
291
+ </port>
292
+ <port id="9" precision="I32">
293
+ <dim>-1</dim>
294
+ </port>
295
+ <port id="10" precision="U8">
296
+ <dim>-1</dim>
297
+ </port>
298
+ </output>
299
+ </layer>
300
+ <layer id="24" name="Constant_11174" type="Const" version="opset1">
301
+ <data element_type="u8" shape="202" offset="30" size="202" />
302
+ <output>
303
+ <port id="0" precision="U8">
304
+ <dim>202</dim>
305
+ </port>
306
+ </output>
307
+ </layer>
308
+ <layer id="25" name="RegexSplit_11175" type="RegexSplit" version="extension">
309
+ <data behaviour="isolate" invert="false" max_splits="-1" />
310
+ <input>
311
+ <port id="0" precision="I32">
312
+ <dim>-1</dim>
313
+ </port>
314
+ <port id="1" precision="I32">
315
+ <dim>-1</dim>
316
+ </port>
317
+ <port id="2" precision="I32">
318
+ <dim>-1</dim>
319
+ </port>
320
+ <port id="3" precision="I32">
321
+ <dim>-1</dim>
322
+ </port>
323
+ <port id="4" precision="U8">
324
+ <dim>-1</dim>
325
+ </port>
326
+ <port id="5" precision="U8">
327
+ <dim>202</dim>
328
+ </port>
329
+ </input>
330
+ <output>
331
+ <port id="6" precision="I32">
332
+ <dim>-1</dim>
333
+ </port>
334
+ <port id="7" precision="I32">
335
+ <dim>-1</dim>
336
+ </port>
337
+ <port id="8" precision="I32">
338
+ <dim>-1</dim>
339
+ </port>
340
+ <port id="9" precision="I32">
341
+ <dim>-1</dim>
342
+ </port>
343
+ <port id="10" precision="U8">
344
+ <dim>-1</dim>
345
+ </port>
346
+ </output>
347
+ </layer>
348
+ <layer id="26" name="Constant_11177" type="Const" version="opset1">
349
+ <data element_type="u8" shape="323082" offset="232" size="323082" />
350
+ <output>
351
+ <port id="0" precision="U8">
352
+ <dim>323082</dim>
353
+ </port>
354
+ </output>
355
+ </layer>
356
+ <layer id="27" name="StringTensorUnpack_11178" type="StringTensorUnpack" version="extension">
357
+ <data mode="begins_ends" />
358
+ <input>
359
+ <port id="0" precision="U8">
360
+ <dim>323082</dim>
361
+ </port>
362
+ </input>
363
+ <output>
364
+ <port id="1" precision="I32">
365
+ <dim>-1</dim>
366
+ </port>
367
+ <port id="2" precision="I32">
368
+ <dim>-1</dim>
369
+ </port>
370
+ <port id="3" precision="U8">
371
+ <dim>-1</dim>
372
+ </port>
373
+ </output>
374
+ </layer>
375
+ <layer id="28" name="Constant_11179" type="Const" version="opset1">
376
+ <data element_type="i32" shape="" offset="323314" size="4" />
377
+ <output>
378
+ <port id="0" precision="I32" />
379
+ </output>
380
+ </layer>
381
+ <layer id="29" name="WordpieceTokenizer_11180" type="WordpieceTokenizer" version="extension">
382
+ <data suffix_indicator="##" max_bytes_per_word="100" />
383
+ <input>
384
+ <port id="0" precision="I32">
385
+ <dim>-1</dim>
386
+ </port>
387
+ <port id="1" precision="I32">
388
+ <dim>-1</dim>
389
+ </port>
390
+ <port id="2" precision="I32">
391
+ <dim>-1</dim>
392
+ </port>
393
+ <port id="3" precision="I32">
394
+ <dim>-1</dim>
395
+ </port>
396
+ <port id="4" precision="U8">
397
+ <dim>-1</dim>
398
+ </port>
399
+ <port id="5" precision="I32">
400
+ <dim>-1</dim>
401
+ </port>
402
+ <port id="6" precision="I32">
403
+ <dim>-1</dim>
404
+ </port>
405
+ <port id="7" precision="U8">
406
+ <dim>-1</dim>
407
+ </port>
408
+ <port id="8" precision="I32" />
409
+ </input>
410
+ <output>
411
+ <port id="9" precision="I32">
412
+ <dim>-1</dim>
413
+ </port>
414
+ <port id="10" precision="I32">
415
+ <dim>-1</dim>
416
+ </port>
417
+ <port id="11" precision="I32">
418
+ <dim>-1</dim>
419
+ </port>
420
+ </output>
421
+ </layer>
422
+ <layer id="30" name="Subtract_11181" type="Subtract" version="opset1">
423
+ <data auto_broadcast="numpy" />
424
+ <input>
425
+ <port id="0" precision="I32">
426
+ <dim>-1</dim>
427
+ </port>
428
+ <port id="1" precision="I32">
429
+ <dim>-1</dim>
430
+ </port>
431
+ </input>
432
+ <output>
433
+ <port id="2" precision="I32">
434
+ <dim>-1</dim>
435
+ </port>
436
+ </output>
437
+ </layer>
438
+ <layer id="31" name="Constant_11182" type="Const" version="opset1">
439
+ <data element_type="i32" shape="" offset="323318" size="4" />
440
+ <output>
441
+ <port id="0" precision="I32" />
442
+ </output>
443
+ </layer>
444
+ <layer id="32" name="Minimum_11183" type="Minimum" version="opset1">
445
+ <data auto_broadcast="numpy" />
446
+ <input>
447
+ <port id="0" precision="I32">
448
+ <dim>-1</dim>
449
+ </port>
450
+ <port id="1" precision="I32" />
451
+ </input>
452
+ <output>
453
+ <port id="2" precision="I32">
454
+ <dim>-1</dim>
455
+ </port>
456
+ </output>
457
+ </layer>
458
+ <layer id="33" name="Add_11184" type="Add" version="opset1">
459
+ <data auto_broadcast="numpy" />
460
+ <input>
461
+ <port id="0" precision="I32">
462
+ <dim>-1</dim>
463
+ </port>
464
+ <port id="1" precision="I32">
465
+ <dim>-1</dim>
466
+ </port>
467
+ </input>
468
+ <output>
469
+ <port id="2" precision="I32">
470
+ <dim>-1</dim>
471
+ </port>
472
+ </output>
473
+ </layer>
474
+ <layer id="34" name="Constant_11188" type="Const" version="opset1">
475
+ <data element_type="i32" shape="" offset="0" size="4" />
476
+ <output>
477
+ <port id="0" precision="I32" />
478
+ </output>
479
+ </layer>
480
+ <layer id="35" name="Constant_11189" type="Const" version="opset1">
481
+ <data element_type="i32" shape="" offset="4" size="4" />
482
+ <output>
483
+ <port id="0" precision="I32" />
484
+ </output>
485
+ </layer>
486
+ <layer id="36" name="Constant_11190" type="Const" version="opset1">
487
+ <data element_type="i32" shape="1" offset="323322" size="4" />
488
+ <output>
489
+ <port id="0" precision="I32">
490
+ <dim>1</dim>
491
+ </port>
492
+ </output>
493
+ </layer>
494
+ <layer id="37" name="Constant_11191" type="Const" version="opset1">
495
+ <data element_type="i32" shape="3" offset="323326" size="12" />
496
+ <output>
497
+ <port id="0" precision="I32">
498
+ <dim>3</dim>
499
+ </port>
500
+ </output>
501
+ </layer>
502
+ <layer id="38" name="CombineSegments_11192" type="CombineSegments" version="extension">
503
+ <input>
504
+ <port id="0" precision="I32" />
505
+ <port id="1" precision="I32" />
506
+ <port id="2" precision="I32">
507
+ <dim>1</dim>
508
+ </port>
509
+ <port id="3" precision="I32">
510
+ <dim>-1</dim>
511
+ </port>
512
+ <port id="4" precision="I32">
513
+ <dim>-1</dim>
514
+ </port>
515
+ <port id="5" precision="I32">
516
+ <dim>-1</dim>
517
+ </port>
518
+ <port id="6" precision="I32" />
519
+ <port id="7" precision="I32" />
520
+ <port id="8" precision="I32">
521
+ <dim>1</dim>
522
+ </port>
523
+ <port id="9" precision="I32">
524
+ <dim>3</dim>
525
+ </port>
526
+ </input>
527
+ <output>
528
+ <port id="10" precision="I32">
529
+ <dim>-1</dim>
530
+ </port>
531
+ <port id="11" precision="I32">
532
+ <dim>-1</dim>
533
+ </port>
534
+ <port id="12" precision="I32">
535
+ <dim>-1</dim>
536
+ </port>
537
+ <port id="13" precision="I32">
538
+ <dim>-1</dim>
539
+ </port>
540
+ <port id="14" precision="I32">
541
+ <dim>-1</dim>
542
+ </port>
543
+ <port id="15" precision="I32">
544
+ <dim>-1</dim>
545
+ </port>
546
+ </output>
547
+ </layer>
548
+ <layer id="39" name="Subtract_11193" type="Subtract" version="opset1">
549
+ <data auto_broadcast="numpy" />
550
+ <input>
551
+ <port id="0" precision="I32">
552
+ <dim>-1</dim>
553
+ </port>
554
+ <port id="1" precision="I32">
555
+ <dim>-1</dim>
556
+ </port>
557
+ </input>
558
+ <output>
559
+ <port id="2" precision="I32">
560
+ <dim>-1</dim>
561
+ </port>
562
+ </output>
563
+ </layer>
564
+ <layer id="40" name="Constant_11194" type="Const" version="opset1">
565
+ <data element_type="i32" shape="" offset="0" size="4" />
566
+ <output>
567
+ <port id="0" precision="I32" />
568
+ </output>
569
+ </layer>
570
+ <layer id="41" name="ReduceMax_11195" type="ReduceMax" version="opset1">
571
+ <data keep_dims="false" />
572
+ <input>
573
+ <port id="0" precision="I32">
574
+ <dim>-1</dim>
575
+ </port>
576
+ <port id="1" precision="I32" />
577
+ </input>
578
+ <output>
579
+ <port id="2" precision="I32" />
580
+ </output>
581
+ </layer>
582
+ <layer id="42" name="Constant_11196" type="Const" version="opset1">
583
+ <data element_type="i32" shape="" offset="0" size="4" />
584
+ <output>
585
+ <port id="0" precision="I32" />
586
+ </output>
587
+ </layer>
588
+ <layer id="43" name="RaggedToDense_11197" type="RaggedToDense" version="extension">
589
+ <data pad_right="true" />
590
+ <input>
591
+ <port id="0" precision="I32">
592
+ <dim>-1</dim>
593
+ </port>
594
+ <port id="1" precision="I32">
595
+ <dim>-1</dim>
596
+ </port>
597
+ <port id="2" precision="I32">
598
+ <dim>-1</dim>
599
+ </port>
600
+ <port id="3" precision="I32" />
601
+ <port id="4" precision="I32" />
602
+ </input>
603
+ <output>
604
+ <port id="5" precision="I32">
605
+ <dim>-1</dim>
606
+ <dim>-1</dim>
607
+ </port>
608
+ <port id="6" precision="BOOL">
609
+ <dim>-1</dim>
610
+ <dim>-1</dim>
611
+ </port>
612
+ </output>
613
+ </layer>
614
+ <layer id="44" name="Convert_11198" type="Convert" version="opset1">
615
+ <data destination_type="i32" />
616
+ <input>
617
+ <port id="0" precision="BOOL">
618
+ <dim>-1</dim>
619
+ <dim>-1</dim>
620
+ </port>
621
+ </input>
622
+ <output>
623
+ <port id="1" precision="I32">
624
+ <dim>-1</dim>
625
+ <dim>-1</dim>
626
+ </port>
627
+ </output>
628
+ </layer>
629
+ <layer id="45" name="Convert_11198" type="Convert" version="opset1">
630
+ <data destination_type="i64" />
631
+ <input>
632
+ <port id="0" precision="I32">
633
+ <dim>-1</dim>
634
+ <dim>-1</dim>
635
+ </port>
636
+ </input>
637
+ <output>
638
+ <port id="1" precision="I64" names="attention_mask">
639
+ <dim>-1</dim>
640
+ <dim>-1</dim>
641
+ </port>
642
+ </output>
643
+ </layer>
644
+ <layer id="47" name="Constant_11199" type="Const" version="opset1">
645
+ <data element_type="i32" shape="" offset="0" size="4" />
646
+ <output>
647
+ <port id="0" precision="I32" />
648
+ </output>
649
+ </layer>
650
+ <layer id="48" name="RaggedToDense_11200" type="RaggedToDense" version="extension">
651
+ <data pad_right="true" />
652
+ <input>
653
+ <port id="0" precision="I32">
654
+ <dim>-1</dim>
655
+ </port>
656
+ <port id="1" precision="I32">
657
+ <dim>-1</dim>
658
+ </port>
659
+ <port id="2" precision="I32">
660
+ <dim>-1</dim>
661
+ </port>
662
+ <port id="3" precision="I32" />
663
+ <port id="4" precision="I32" />
664
+ </input>
665
+ <output>
666
+ <port id="5" precision="I32">
667
+ <dim>-1</dim>
668
+ <dim>-1</dim>
669
+ </port>
670
+ <port id="6" precision="BOOL">
671
+ <dim>-1</dim>
672
+ <dim>-1</dim>
673
+ </port>
674
+ </output>
675
+ </layer>
676
+ <layer id="49" name="RaggedToDense_11200.0" type="Convert" version="opset1">
677
+ <data destination_type="i64" />
678
+ <input>
679
+ <port id="0" precision="I32">
680
+ <dim>-1</dim>
681
+ <dim>-1</dim>
682
+ </port>
683
+ </input>
684
+ <output>
685
+ <port id="1" precision="I64" names="token_type_ids">
686
+ <dim>-1</dim>
687
+ <dim>-1</dim>
688
+ </port>
689
+ </output>
690
+ </layer>
691
+ <layer id="51" name="RaggedToDense_11197.0" type="Convert" version="opset1">
692
+ <data destination_type="i64" />
693
+ <input>
694
+ <port id="0" precision="I32">
695
+ <dim>-1</dim>
696
+ <dim>-1</dim>
697
+ </port>
698
+ </input>
699
+ <output>
700
+ <port id="1" precision="I64" names="input_ids">
701
+ <dim>-1</dim>
702
+ <dim>-1</dim>
703
+ </port>
704
+ </output>
705
+ </layer>
706
+ <layer id="52" name="Result_11201" type="Result" version="opset1">
707
+ <input>
708
+ <port id="0" precision="I64">
709
+ <dim>-1</dim>
710
+ <dim>-1</dim>
711
+ </port>
712
+ </input>
713
+ </layer>
714
+ <layer id="50" name="Result_11202" type="Result" version="opset1">
715
+ <input>
716
+ <port id="0" precision="I64">
717
+ <dim>-1</dim>
718
+ <dim>-1</dim>
719
+ </port>
720
+ </input>
721
+ </layer>
722
+ <layer id="46" name="Result_11203" type="Result" version="opset1">
723
+ <input>
724
+ <port id="0" precision="I64">
725
+ <dim>-1</dim>
726
+ <dim>-1</dim>
727
+ </port>
728
+ </input>
729
+ </layer>
730
+ </layers>
731
+ <edges>
732
+ <edge from-layer="0" from-port="0" to-layer="5" to-port="0" />
733
+ <edge from-layer="1" from-port="0" to-layer="38" to-port="0" />
734
+ <edge from-layer="2" from-port="0" to-layer="38" to-port="1" />
735
+ <edge from-layer="3" from-port="0" to-layer="38" to-port="2" />
736
+ <edge from-layer="4" from-port="0" to-layer="16" to-port="0" />
737
+ <edge from-layer="5" from-port="1" to-layer="6" to-port="0" />
738
+ <edge from-layer="5" from-port="2" to-layer="6" to-port="1" />
739
+ <edge from-layer="5" from-port="3" to-layer="6" to-port="2" />
740
+ <edge from-layer="6" from-port="3" to-layer="9" to-port="0" />
741
+ <edge from-layer="6" from-port="4" to-layer="9" to-port="1" />
742
+ <edge from-layer="6" from-port="5" to-layer="9" to-port="2" />
743
+ <edge from-layer="7" from-port="0" to-layer="9" to-port="3" />
744
+ <edge from-layer="8" from-port="0" to-layer="9" to-port="4" />
745
+ <edge from-layer="9" from-port="5" to-layer="10" to-port="0" />
746
+ <edge from-layer="9" from-port="6" to-layer="10" to-port="1" />
747
+ <edge from-layer="9" from-port="7" to-layer="10" to-port="2" />
748
+ <edge from-layer="10" from-port="3" to-layer="11" to-port="0" />
749
+ <edge from-layer="10" from-port="3" to-layer="23" to-port="2" />
750
+ <edge from-layer="10" from-port="4" to-layer="23" to-port="3" />
751
+ <edge from-layer="10" from-port="5" to-layer="23" to-port="4" />
752
+ <edge from-layer="11" from-port="1" to-layer="14" to-port="0" />
753
+ <edge from-layer="12" from-port="0" to-layer="14" to-port="1" />
754
+ <edge from-layer="13" from-port="0" to-layer="14" to-port="2" />
755
+ <edge from-layer="14" from-port="3" to-layer="19" to-port="0" />
756
+ <edge from-layer="14" from-port="3" to-layer="16" to-port="1" />
757
+ <edge from-layer="15" from-port="0" to-layer="16" to-port="2" />
758
+ <edge from-layer="16" from-port="3" to-layer="23" to-port="0" />
759
+ <edge from-layer="17" from-port="0" to-layer="21" to-port="0" />
760
+ <edge from-layer="18" from-port="0" to-layer="19" to-port="1" />
761
+ <edge from-layer="19" from-port="2" to-layer="21" to-port="1" />
762
+ <edge from-layer="20" from-port="0" to-layer="21" to-port="2" />
763
+ <edge from-layer="21" from-port="3" to-layer="23" to-port="1" />
764
+ <edge from-layer="22" from-port="0" to-layer="23" to-port="5" />
765
+ <edge from-layer="23" from-port="6" to-layer="25" to-port="0" />
766
+ <edge from-layer="23" from-port="7" to-layer="25" to-port="1" />
767
+ <edge from-layer="23" from-port="8" to-layer="25" to-port="2" />
768
+ <edge from-layer="23" from-port="9" to-layer="25" to-port="3" />
769
+ <edge from-layer="23" from-port="10" to-layer="25" to-port="4" />
770
+ <edge from-layer="24" from-port="0" to-layer="25" to-port="5" />
771
+ <edge from-layer="25" from-port="8" to-layer="29" to-port="2" />
772
+ <edge from-layer="25" from-port="9" to-layer="29" to-port="3" />
773
+ <edge from-layer="25" from-port="10" to-layer="29" to-port="4" />
774
+ <edge from-layer="25" from-port="6" to-layer="29" to-port="0" />
775
+ <edge from-layer="25" from-port="7" to-layer="29" to-port="1" />
776
+ <edge from-layer="26" from-port="0" to-layer="27" to-port="0" />
777
+ <edge from-layer="27" from-port="3" to-layer="29" to-port="7" />
778
+ <edge from-layer="27" from-port="1" to-layer="29" to-port="5" />
779
+ <edge from-layer="27" from-port="2" to-layer="29" to-port="6" />
780
+ <edge from-layer="28" from-port="0" to-layer="29" to-port="8" />
781
+ <edge from-layer="29" from-port="10" to-layer="30" to-port="0" />
782
+ <edge from-layer="29" from-port="9" to-layer="30" to-port="1" />
783
+ <edge from-layer="29" from-port="9" to-layer="33" to-port="0" />
784
+ <edge from-layer="29" from-port="9" to-layer="38" to-port="3" />
785
+ <edge from-layer="29" from-port="11" to-layer="38" to-port="5" />
786
+ <edge from-layer="30" from-port="2" to-layer="32" to-port="0" />
787
+ <edge from-layer="31" from-port="0" to-layer="32" to-port="1" />
788
+ <edge from-layer="32" from-port="2" to-layer="33" to-port="1" />
789
+ <edge from-layer="33" from-port="2" to-layer="38" to-port="4" />
790
+ <edge from-layer="34" from-port="0" to-layer="38" to-port="6" />
791
+ <edge from-layer="35" from-port="0" to-layer="38" to-port="7" />
792
+ <edge from-layer="36" from-port="0" to-layer="38" to-port="8" />
793
+ <edge from-layer="37" from-port="0" to-layer="38" to-port="9" />
794
+ <edge from-layer="38" from-port="11" to-layer="39" to-port="0" />
795
+ <edge from-layer="38" from-port="10" to-layer="39" to-port="1" />
796
+ <edge from-layer="38" from-port="10" to-layer="43" to-port="0" />
797
+ <edge from-layer="38" from-port="11" to-layer="43" to-port="1" />
798
+ <edge from-layer="38" from-port="12" to-layer="43" to-port="2" />
799
+ <edge from-layer="38" from-port="13" to-layer="48" to-port="0" />
800
+ <edge from-layer="38" from-port="14" to-layer="48" to-port="1" />
801
+ <edge from-layer="38" from-port="15" to-layer="48" to-port="2" />
802
+ <edge from-layer="39" from-port="2" to-layer="41" to-port="0" />
803
+ <edge from-layer="40" from-port="0" to-layer="41" to-port="1" />
804
+ <edge from-layer="41" from-port="2" to-layer="43" to-port="3" />
805
+ <edge from-layer="41" from-port="2" to-layer="48" to-port="3" />
806
+ <edge from-layer="42" from-port="0" to-layer="43" to-port="4" />
807
+ <edge from-layer="43" from-port="6" to-layer="44" to-port="0" />
808
+ <edge from-layer="43" from-port="5" to-layer="51" to-port="0" />
809
+ <edge from-layer="44" from-port="1" to-layer="45" to-port="0" />
810
+ <edge from-layer="45" from-port="1" to-layer="46" to-port="0" />
811
+ <edge from-layer="47" from-port="0" to-layer="48" to-port="4" />
812
+ <edge from-layer="48" from-port="5" to-layer="49" to-port="0" />
813
+ <edge from-layer="49" from-port="1" to-layer="50" to-port="0" />
814
+ <edge from-layer="51" from-port="1" to-layer="52" to-port="0" />
815
+ </edges>
816
+ <rt_info />
817
+ </net>
special_tokens_map.json ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ {
2
+ "cls_token": "[CLS]",
3
+ "mask_token": "[MASK]",
4
+ "pad_token": "[PAD]",
5
+ "sep_token": "[SEP]",
6
+ "unk_token": "[UNK]"
7
+ }
tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
tokenizer_config.json ADDED
@@ -0,0 +1,62 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "added_tokens_decoder": {
3
+ "0": {
4
+ "content": "[PAD]",
5
+ "lstrip": false,
6
+ "normalized": false,
7
+ "rstrip": false,
8
+ "single_word": false,
9
+ "special": true
10
+ },
11
+ "100": {
12
+ "content": "[UNK]",
13
+ "lstrip": false,
14
+ "normalized": false,
15
+ "rstrip": false,
16
+ "single_word": false,
17
+ "special": true
18
+ },
19
+ "101": {
20
+ "content": "[CLS]",
21
+ "lstrip": false,
22
+ "normalized": false,
23
+ "rstrip": false,
24
+ "single_word": false,
25
+ "special": true
26
+ },
27
+ "102": {
28
+ "content": "[SEP]",
29
+ "lstrip": false,
30
+ "normalized": false,
31
+ "rstrip": false,
32
+ "single_word": false,
33
+ "special": true
34
+ },
35
+ "103": {
36
+ "content": "[MASK]",
37
+ "lstrip": false,
38
+ "normalized": false,
39
+ "rstrip": false,
40
+ "single_word": false,
41
+ "special": true
42
+ }
43
+ },
44
+ "clean_up_tokenization_spaces": true,
45
+ "cls_token": "[CLS]",
46
+ "do_lower_case": true,
47
+ "mask_token": "[MASK]",
48
+ "max_length": 75,
49
+ "model_max_length": 1000000000000000019884624838656,
50
+ "pad_to_multiple_of": null,
51
+ "pad_token": "[PAD]",
52
+ "pad_token_type_id": 0,
53
+ "padding_side": "right",
54
+ "sep_token": "[SEP]",
55
+ "stride": 0,
56
+ "strip_accents": null,
57
+ "tokenize_chinese_chars": true,
58
+ "tokenizer_class": "BertTokenizer",
59
+ "truncation_side": "right",
60
+ "truncation_strategy": "longest_first",
61
+ "unk_token": "[UNK]"
62
+ }
vocab.txt ADDED
The diff for this file is too large to render. See raw diff