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RedPajama-INCITE-Chat-3B-v1-fp16-ov

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Files changed (10) hide show
  1. README.md +5 -37
  2. config.json +5 -2
  3. generation_config.json +1 -1
  4. openvino_detokenizer.bin +2 -2
  5. openvino_detokenizer.xml +24 -29
  6. openvino_model.bin +2 -2
  7. openvino_model.xml +0 -0
  8. openvino_tokenizer.bin +2 -2
  9. openvino_tokenizer.xml +190 -370
  10. tokenizer.json +0 -0
README.md CHANGED
@@ -3,7 +3,7 @@ license: apache-2.0
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  license_link: https://choosealicense.com/licenses/apache-2.0/
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  ---
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  # RedPajama-INCITE-Chat-3B-v1-fp16-ov
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- * Model creator: [Together](https://huggingface.co/togethercomputer)
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  * Original model: [RedPajama-INCITE-Chat-3B-v1](https://huggingface.co/togethercomputer/RedPajama-INCITE-Chat-3B-v1)
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  ## Description
@@ -12,11 +12,10 @@ license_link: https://choosealicense.com/licenses/apache-2.0/
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  The provided OpenVINO™ IR model is compatible with:
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- * OpenVINO version 2024.2.0 and higher
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- * Optimum Intel 1.19.0 and higher
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-
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- ## Running Model Inference with [Optimum Intel](https://huggingface.co/docs/optimum/intel/index)
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  1. Install packages required for using [Optimum Intel](https://huggingface.co/docs/optimum/intel/index) integration with the OpenVINO backend:
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@@ -43,40 +42,9 @@ print(text)
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  For more examples and possible optimizations, refer to the [OpenVINO Large Language Model Inference Guide](https://docs.openvino.ai/2024/learn-openvino/llm_inference_guide.html).
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- ## Running Model Inference with [OpenVINO GenAI](https://github.com/openvinotoolkit/openvino.genai)
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-
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- 1. Install packages required for using OpenVINO GenAI.
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- ```
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- pip install openvino-genai huggingface_hub
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- ```
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-
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- 2. Download model from HuggingFace Hub
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-
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- ```
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- import huggingface_hub as hf_hub
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-
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- model_id = "OpenVINO/RedPajama-INCITE-Chat-3B-v1-fp16-ov"
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- model_path = "RedPajama-INCITE-Chat-3B-v1-fp16-ov"
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-
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- hf_hub.snapshot_download(model_id, local_dir=model_path)
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-
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- ```
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-
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- 3. Run model inference:
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-
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- ```
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- import openvino_genai as ov_genai
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-
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- device = "CPU"
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- pipe = ov_genai.LLMPipeline(model_path, device)
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- print(pipe.generate("What is OpenVINO?", max_length=200))
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- ```
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-
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- More GenAI usage examples can be found in OpenVINO GenAI library [docs](https://github.com/openvinotoolkit/openvino.genai/blob/master/src/README.md) and [samples](https://github.com/openvinotoolkit/openvino.genai?tab=readme-ov-file#openvino-genai-samples)
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-
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  ## Limitations
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- Check the original model card for [limitations]().
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  ## Legal information
82
 
 
3
  license_link: https://choosealicense.com/licenses/apache-2.0/
4
  ---
5
  # RedPajama-INCITE-Chat-3B-v1-fp16-ov
6
+ * Model creator: [Togethercomputer](https://huggingface.co/togethercomputer)
7
  * Original model: [RedPajama-INCITE-Chat-3B-v1](https://huggingface.co/togethercomputer/RedPajama-INCITE-Chat-3B-v1)
8
 
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  ## Description
 
12
 
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  The provided OpenVINO™ IR model is compatible with:
14
 
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+ * OpenVINO version 2024.4.0 and higher
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+ * Optimum Intel 1.20.0 and higher
 
 
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+ ## Running Model Inference
19
 
20
  1. Install packages required for using [Optimum Intel](https://huggingface.co/docs/optimum/intel/index) integration with the OpenVINO backend:
21
 
 
42
 
43
  For more examples and possible optimizations, refer to the [OpenVINO Large Language Model Inference Guide](https://docs.openvino.ai/2024/learn-openvino/llm_inference_guide.html).
44
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Limitations
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+ Check the original model card for [original model card](https://huggingface.co/togethercomputer/RedPajama-INCITE-Chat-3B-v1) for limitations.
48
 
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  ## Legal information
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  </output>
80
  </layer>
81
- <layer id="6" name="Constant_486924" type="Const" version="opset1">
82
  <data element_type="i64" shape="" offset="0" size="8" />
83
  <output>
84
  <port id="0" precision="I64" />
85
  </output>
86
  </layer>
87
- <layer id="7" name="Gather_486925" type="Gather" version="opset8">
88
  <data batch_dims="0" />
89
  <input>
90
  <port id="0" precision="I64">
@@ -97,13 +72,13 @@
97
  <port id="3" precision="I64" />
98
  </output>
99
  </layer>
100
- <layer id="8" name="Constant_486927" type="Const" version="opset1">
101
  <data element_type="i64" shape="" offset="8" size="8" />
102
  <output>
103
  <port id="0" precision="I64" />
104
  </output>
105
  </layer>
106
- <layer id="9" name="Range_486928" type="Range" version="opset4">
107
  <data output_type="i32" />
108
  <input>
109
  <port id="0" precision="I64" />
@@ -116,19 +91,19 @@
116
  </port>
117
  </output>
118
  </layer>
119
- <layer id="10" name="Constant_486930" type="Const" version="opset1">
120
  <data element_type="i64" shape="" offset="8" size="8" />
121
  <output>
122
  <port id="0" precision="I64" />
123
  </output>
124
  </layer>
125
- <layer id="11" name="Constant_486931" type="Const" version="opset1">
126
  <data element_type="i64" shape="" offset="8" size="8" />
127
  <output>
128
  <port id="0" precision="I64" />
129
  </output>
130
  </layer>
131
- <layer id="12" name="Add_486932" type="Add" version="opset1">
132
  <data auto_broadcast="numpy" />
133
  <input>
134
  <port id="0" precision="I64" />
@@ -138,13 +113,13 @@
138
  <port id="2" precision="I64" />
139
  </output>
140
  </layer>
141
- <layer id="13" name="Constant_486933" type="Const" version="opset1">
142
  <data element_type="i64" shape="" offset="8" size="8" />
143
  <output>
144
  <port id="0" precision="I64" />
145
  </output>
146
  </layer>
147
- <layer id="14" name="Range_486934" type="Range" version="opset4">
148
  <data output_type="i32" />
149
  <input>
150
  <port id="0" precision="I64" />
@@ -157,16 +132,15 @@
157
  </port>
158
  </output>
159
  </layer>
160
- <layer id="15" name="Constant_486997" type="Const" version="opset1">
161
- <data element_type="u8" shape="620" offset="16" size="620" />
162
  <output>
163
  <port id="0" precision="U8">
164
- <dim>620</dim>
165
  </port>
166
  </output>
167
  </layer>
168
- <layer id="16" name="RegexSplit_486998" type="RegexSplit" version="extension">
169
- <data behaviour="isolate" invert="false" max_splits="-1" />
170
  <input>
171
  <port id="0" precision="I32">
172
  <dim>-1</dim>
@@ -184,7 +158,7 @@
184
  <dim>-1</dim>
185
  </port>
186
  <port id="5" precision="U8">
187
- <dim>620</dim>
188
  </port>
189
  </input>
190
  <output>
@@ -203,45 +177,13 @@
203
  <port id="10" precision="U8">
204
  <dim>-1</dim>
205
  </port>
206
- </output>
207
- </layer>
208
- <layer id="17" name="Constant_487003" type="Const" version="opset1">
209
- <data element_type="u8" shape="64" offset="636" size="64" />
210
- <output>
211
- <port id="0" precision="U8">
212
- <dim>64</dim>
213
- </port>
214
- </output>
215
- </layer>
216
- <layer id="18" name="Constant_487000" type="Const" version="opset1">
217
- <data element_type="u8" shape="399" offset="700" size="399" />
218
- <output>
219
- <port id="0" precision="U8">
220
- <dim>399</dim>
221
- </port>
222
- </output>
223
- </layer>
224
- <layer id="19" name="StringTensorUnpack_487001" type="StringTensorUnpack" version="extension">
225
- <data mode="begins_ends" />
226
- <input>
227
- <port id="0" precision="U8">
228
- <dim>399</dim>
229
- </port>
230
- </input>
231
- <output>
232
- <port id="1" precision="I32">
233
- <dim>-1</dim>
234
- </port>
235
- <port id="2" precision="I32">
236
- <dim>-1</dim>
237
- </port>
238
- <port id="3" precision="U8">
239
  <dim>-1</dim>
240
  </port>
241
  </output>
242
  </layer>
243
- <layer id="20" name="RegexSplit_487004" type="RegexSplit" version="extension">
244
- <data behaviour="isolate" invert="false" max_splits="-1" />
245
  <input>
246
  <port id="0" precision="I32">
247
  <dim>-1</dim>
@@ -249,47 +191,38 @@
249
  <port id="1" precision="I32">
250
  <dim>-1</dim>
251
  </port>
252
- <port id="2" precision="I32">
253
- <dim>-1</dim>
254
- </port>
255
- <port id="3" precision="I32">
256
- <dim>-1</dim>
257
- </port>
258
- <port id="4" precision="U8">
259
- <dim>-1</dim>
260
- </port>
261
- <port id="5" precision="U8">
262
- <dim>64</dim>
263
- </port>
264
- <port id="6" precision="I32">
265
- <dim>-1</dim>
266
- </port>
267
- <port id="7" precision="I32">
268
  <dim>-1</dim>
269
  </port>
270
- <port id="8" precision="U8">
271
  <dim>-1</dim>
272
  </port>
273
  </input>
274
  <output>
275
- <port id="9" precision="I32">
276
  <dim>-1</dim>
277
  </port>
278
- <port id="10" precision="I32">
279
  <dim>-1</dim>
280
  </port>
281
- <port id="11" precision="I32">
282
  <dim>-1</dim>
283
  </port>
284
- <port id="12" precision="I32">
285
  <dim>-1</dim>
286
  </port>
287
- <port id="13" precision="U8">
288
- <dim>-1</dim>
 
 
 
 
 
289
  </port>
290
  </output>
291
  </layer>
292
- <layer id="21" name="BytesToChars_487005" type="BytesToChars" version="extension">
 
293
  <input>
294
  <port id="0" precision="I32">
295
  <dim>-1</dim>
@@ -306,38 +239,47 @@
306
  <port id="4" precision="U8">
307
  <dim>-1</dim>
308
  </port>
 
 
 
 
 
 
309
  </input>
310
  <output>
311
- <port id="5" precision="I32">
312
  <dim>-1</dim>
313
  </port>
314
- <port id="6" precision="I32">
315
  <dim>-1</dim>
316
  </port>
317
- <port id="7" precision="I32">
318
  <dim>-1</dim>
319
  </port>
320
- <port id="8" precision="I32">
321
  <dim>-1</dim>
322
  </port>
323
- <port id="9" precision="U8">
 
 
 
324
  <dim>-1</dim>
325
  </port>
326
  </output>
327
  </layer>
328
- <layer id="22" name="Constant_487007" type="Const" version="opset1">
329
- <data element_type="u8" shape="558397" offset="1099" size="558397" />
330
  <output>
331
  <port id="0" precision="U8">
332
- <dim>558397</dim>
333
  </port>
334
  </output>
335
  </layer>
336
- <layer id="23" name="StringTensorUnpack_487008" type="StringTensorUnpack" version="extension">
337
  <data mode="begins_ends" />
338
  <input>
339
  <port id="0" precision="U8">
340
- <dim>558397</dim>
341
  </port>
342
  </input>
343
  <output>
@@ -352,19 +294,19 @@
352
  </port>
353
  </output>
354
  </layer>
355
- <layer id="24" name="Constant_487088" type="Const" version="opset1">
356
- <data element_type="u8" shape="606619" offset="559496" size="606619" />
357
  <output>
358
  <port id="0" precision="U8">
359
- <dim>606619</dim>
360
  </port>
361
  </output>
362
  </layer>
363
- <layer id="25" name="StringTensorUnpack_487089" type="StringTensorUnpack" version="extension">
364
  <data mode="begins_ends" />
365
  <input>
366
  <port id="0" precision="U8">
367
- <dim>606619</dim>
368
  </port>
369
  </input>
370
  <output>
@@ -379,25 +321,19 @@
379
  </port>
380
  </output>
381
  </layer>
382
- <layer id="26" name="Constant_487016" type="Const" version="opset1">
383
- <data element_type="i64" shape="" offset="0" size="8" />
384
- <output>
385
- <port id="0" precision="I64" />
386
- </output>
387
- </layer>
388
- <layer id="27" name="Constant_487010" type="Const" version="opset1">
389
- <data element_type="u8" shape="399" offset="700" size="399" />
390
  <output>
391
  <port id="0" precision="U8">
392
- <dim>399</dim>
393
  </port>
394
  </output>
395
  </layer>
396
- <layer id="28" name="StringTensorUnpack_487011" type="StringTensorUnpack" version="extension">
397
  <data mode="begins_ends" />
398
  <input>
399
  <port id="0" precision="U8">
400
- <dim>399</dim>
401
  </port>
402
  </input>
403
  <output>
@@ -412,150 +348,43 @@
412
  </port>
413
  </output>
414
  </layer>
415
- <layer id="29" name="ShapeOf_487012" type="ShapeOf" version="opset3">
416
- <data output_type="i64" />
417
- <input>
418
- <port id="0" precision="I32">
419
- <dim>-1</dim>
420
- </port>
421
- </input>
422
- <output>
423
- <port id="1" precision="I64">
424
- <dim>1</dim>
425
- </port>
426
- </output>
427
- </layer>
428
- <layer id="30" name="Constant_487013" type="Const" version="opset1">
429
- <data element_type="i64" shape="" offset="0" size="8" />
430
- <output>
431
- <port id="0" precision="I64" />
432
- </output>
433
- </layer>
434
- <layer id="31" name="Constant_487014" type="Const" version="opset1">
435
- <data element_type="i64" shape="" offset="0" size="8" />
436
  <output>
437
- <port id="0" precision="I64" />
438
- </output>
439
- </layer>
440
- <layer id="32" name="Gather_487015" type="Gather" version="opset8">
441
- <data batch_dims="0" />
442
- <input>
443
- <port id="0" precision="I64">
444
- <dim>1</dim>
445
  </port>
446
- <port id="1" precision="I64" />
447
- <port id="2" precision="I64" />
448
- </input>
449
- <output>
450
- <port id="3" precision="I64" />
451
  </output>
452
  </layer>
453
- <layer id="33" name="Constant_487017" type="Const" version="opset1">
454
- <data element_type="i64" shape="" offset="8" size="8" />
455
- <output>
456
- <port id="0" precision="I64" />
457
- </output>
458
- </layer>
459
- <layer id="34" name="Range_487018" type="Range" version="opset4">
460
- <data output_type="i32" />
461
  <input>
462
- <port id="0" precision="I64" />
463
- <port id="1" precision="I64" />
464
- <port id="2" precision="I64" />
465
- </input>
466
- <output>
467
- <port id="3" precision="I32">
468
- <dim>-1</dim>
469
  </port>
470
- </output>
471
- </layer>
472
- <layer id="35" name="Constant_487020" type="Const" version="opset1">
473
- <data element_type="i64" shape="" offset="8" size="8" />
474
- <output>
475
- <port id="0" precision="I64" />
476
- </output>
477
- </layer>
478
- <layer id="36" name="Constant_487021" type="Const" version="opset1">
479
- <data element_type="i64" shape="" offset="8" size="8" />
480
- <output>
481
- <port id="0" precision="I64" />
482
- </output>
483
- </layer>
484
- <layer id="37" name="Add_487022" type="Add" version="opset1">
485
- <data auto_broadcast="numpy" />
486
- <input>
487
- <port id="0" precision="I64" />
488
- <port id="1" precision="I64" />
489
  </input>
490
  <output>
491
- <port id="2" precision="I64" />
492
- </output>
493
- </layer>
494
- <layer id="38" name="Constant_487023" type="Const" version="opset1">
495
- <data element_type="i64" shape="" offset="8" size="8" />
496
- <output>
497
- <port id="0" precision="I64" />
498
- </output>
499
- </layer>
500
- <layer id="39" name="Range_487024" type="Range" version="opset4">
501
- <data output_type="i32" />
502
- <input>
503
- <port id="0" precision="I64" />
504
- <port id="1" precision="I64" />
505
- <port id="2" precision="I64" />
506
- </input>
507
- <output>
508
- <port id="3" precision="I32">
509
- <dim>-1</dim>
510
- </port>
511
- </output>
512
- </layer>
513
- <layer id="40" name="BytesToChars_487086" type="BytesToChars" version="extension">
514
- <input>
515
- <port id="0" precision="I32">
516
- <dim>-1</dim>
517
- </port>
518
  <port id="1" precision="I32">
519
  <dim>-1</dim>
520
  </port>
521
  <port id="2" precision="I32">
522
  <dim>-1</dim>
523
  </port>
524
- <port id="3" precision="I32">
525
- <dim>-1</dim>
526
- </port>
527
- <port id="4" precision="U8">
528
- <dim>-1</dim>
529
- </port>
530
- </input>
531
- <output>
532
- <port id="5" precision="I32">
533
- <dim>-1</dim>
534
- </port>
535
- <port id="6" precision="I32">
536
- <dim>-1</dim>
537
- </port>
538
- <port id="7" precision="I32">
539
- <dim>-1</dim>
540
- </port>
541
- <port id="8" precision="I32">
542
- <dim>-1</dim>
543
- </port>
544
- <port id="9" precision="U8">
545
  <dim>-1</dim>
546
  </port>
547
  </output>
548
  </layer>
549
- <layer id="41" name="Constant_487090" type="Const" version="opset1">
550
- <data element_type="i32" shape="23" offset="1166115" size="92" />
551
  <output>
552
  <port id="0" precision="I32">
553
- <dim>23</dim>
554
  </port>
555
  </output>
556
  </layer>
557
- <layer id="42" name="BPETokenizer_487091" type="BPETokenizer" version="extension">
558
- <data unk_token="" fuse_unk="false" suffix_indicator="" end_suffix="" byte_fallback="false" />
559
  <input>
560
  <port id="0" precision="I32">
561
  <dim>-1</dim>
@@ -600,22 +429,31 @@
600
  <dim>-1</dim>
601
  </port>
602
  <port id="14" precision="I32">
603
- <dim>23</dim>
604
  </port>
605
- </input>
606
- <output>
607
  <port id="15" precision="I32">
608
  <dim>-1</dim>
609
  </port>
610
- <port id="16" precision="I32">
611
  <dim>-1</dim>
612
  </port>
613
  <port id="17" precision="I32">
 
 
 
 
 
 
 
 
 
 
 
614
  <dim>-1</dim>
615
  </port>
616
  </output>
617
  </layer>
618
- <layer id="43" name="Subtract_487092" type="Subtract" version="opset1">
619
  <data auto_broadcast="numpy" />
620
  <input>
621
  <port id="0" precision="I32">
@@ -631,13 +469,13 @@
631
  </port>
632
  </output>
633
  </layer>
634
- <layer id="44" name="Constant_487093" type="Const" version="opset1">
635
- <data element_type="i32" shape="" offset="1166207" size="4" />
636
  <output>
637
  <port id="0" precision="I32" />
638
  </output>
639
  </layer>
640
- <layer id="45" name="Minimum_487094" type="Minimum" version="opset1">
641
  <data auto_broadcast="numpy" />
642
  <input>
643
  <port id="0" precision="I32">
@@ -651,7 +489,7 @@
651
  </port>
652
  </output>
653
  </layer>
654
- <layer id="46" name="Add_487095" type="Add" version="opset1">
655
  <data auto_broadcast="numpy" />
656
  <input>
657
  <port id="0" precision="I32">
@@ -667,15 +505,15 @@
667
  </port>
668
  </output>
669
  </layer>
670
- <layer id="47" name="Constant_487096" type="Const" version="opset1">
671
- <data element_type="i32" shape="1" offset="1166211" size="4" />
672
  <output>
673
  <port id="0" precision="I32">
674
  <dim>1</dim>
675
  </port>
676
  </output>
677
  </layer>
678
- <layer id="48" name="CombineSegments_487097" type="CombineSegments" version="extension">
679
  <input>
680
  <port id="0" precision="I32">
681
  <dim>-1</dim>
@@ -711,7 +549,7 @@
711
  </port>
712
  </output>
713
  </layer>
714
- <layer id="49" name="Subtract_487098" type="Subtract" version="opset1">
715
  <data auto_broadcast="numpy" />
716
  <input>
717
  <port id="0" precision="I32">
@@ -727,13 +565,13 @@
727
  </port>
728
  </output>
729
  </layer>
730
- <layer id="50" name="Constant_487099" type="Const" version="opset1">
731
- <data element_type="i32" shape="" offset="1166211" size="4" />
732
  <output>
733
  <port id="0" precision="I32" />
734
  </output>
735
  </layer>
736
- <layer id="51" name="ReduceMax_487100" type="ReduceMax" version="opset1">
737
  <data keep_dims="false" />
738
  <input>
739
  <port id="0" precision="I32">
@@ -745,14 +583,14 @@
745
  <port id="2" precision="I32" />
746
  </output>
747
  </layer>
748
- <layer id="52" name="Constant_487101" type="Const" version="opset1">
749
- <data element_type="i32" shape="" offset="1166211" size="4" />
750
  <output>
751
  <port id="0" precision="I32" />
752
  </output>
753
  </layer>
754
- <layer id="53" name="RaggedToDense_487102" type="RaggedToDense" version="extension">
755
- <data pad_right="true" />
756
  <input>
757
  <port id="0" precision="I32">
758
  <dim>-1</dim>
@@ -777,7 +615,7 @@
777
  </port>
778
  </output>
779
  </layer>
780
- <layer id="54" name="Convert_487103" type="Convert" version="opset1">
781
  <data destination_type="i32" />
782
  <input>
783
  <port id="0" precision="BOOL">
@@ -792,7 +630,7 @@
792
  </port>
793
  </output>
794
  </layer>
795
- <layer id="55" name="Convert_487103" type="Convert" version="opset1">
796
  <data destination_type="i64" />
797
  <input>
798
  <port id="0" precision="I32">
@@ -807,7 +645,7 @@
807
  </port>
808
  </output>
809
  </layer>
810
- <layer id="57" name="RaggedToDense_487102.0" type="Convert" version="opset1">
811
  <data destination_type="i64" />
812
  <input>
813
  <port id="0" precision="I32">
@@ -822,7 +660,7 @@
822
  </port>
823
  </output>
824
  </layer>
825
- <layer id="58" name="Result_487106" type="Result" version="opset1">
826
  <input>
827
  <port id="0" precision="I64">
828
  <dim>-1</dim>
@@ -830,7 +668,7 @@
830
  </port>
831
  </input>
832
  </layer>
833
- <layer id="56" name="Result_487108" type="Result" version="opset1">
834
  <input>
835
  <port id="0" precision="I64">
836
  <dim>-1</dim>
@@ -841,103 +679,85 @@
841
  </layers>
842
  <edges>
843
  <edge from-layer="0" from-port="0" to-layer="2" to-port="0" />
844
- <edge from-layer="1" from-port="0" to-layer="9" to-port="0" />
845
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846
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907
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939
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941
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942
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943
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1
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2
  <net name="tokenizer" version="11">
3
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4
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5
  <data shape="?" element_type="string" />
6
  <output>
7
+ <port id="0" precision="STRING" names="Parameter_67041">
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11
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14
  <output>
15
  <port id="0" precision="I64" />
16
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17
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19
  <data mode="begins_ends" />
20
  <input>
21
  <port id="0" precision="STRING">
 
34
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35
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36
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37
+ <layer id="3" name="ShapeOf_67043" type="ShapeOf" version="opset3">
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
38
  <data output_type="i64" />
39
  <input>
40
  <port id="0" precision="I32">
 
47
  </port>
48
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49
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50
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51
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52
  <output>
53
  <port id="0" precision="I64" />
54
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55
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56
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57
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58
  <output>
59
  <port id="0" precision="I64" />
60
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61
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62
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63
  <data batch_dims="0" />
64
  <input>
65
  <port id="0" precision="I64">
 
72
  <port id="3" precision="I64" />
73
  </output>
74
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75
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76
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77
  <output>
78
  <port id="0" precision="I64" />
79
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80
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81
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82
  <data output_type="i32" />
83
  <input>
84
  <port id="0" precision="I64" />
 
91
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92
  </output>
93
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94
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95
  <data element_type="i64" shape="" offset="8" size="8" />
96
  <output>
97
  <port id="0" precision="I64" />
98
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99
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100
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101
  <data element_type="i64" shape="" offset="8" size="8" />
102
  <output>
103
  <port id="0" precision="I64" />
104
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105
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106
+ <layer id="11" name="Add_67052" type="Add" version="opset1">
107
  <data auto_broadcast="numpy" />
108
  <input>
109
  <port id="0" precision="I64" />
 
113
  <port id="2" precision="I64" />
114
  </output>
115
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116
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117
  <data element_type="i64" shape="" offset="8" size="8" />
118
  <output>
119
  <port id="0" precision="I64" />
120
  </output>
121
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122
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123
  <data output_type="i32" />
124
  <input>
125
  <port id="0" precision="I64" />
 
132
  </port>
133
  </output>
134
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135
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136
+ <data element_type="u8" shape="704" offset="16" size="704" />
137
  <output>
138
  <port id="0" precision="U8">
139
+ <dim>704</dim>
140
  </port>
141
  </output>
142
  </layer>
143
+ <layer id="15" name="SpecialTokensSplit_67117" type="SpecialTokensSplit" version="extension">
 
144
  <input>
145
  <port id="0" precision="I32">
146
  <dim>-1</dim>
 
158
  <dim>-1</dim>
159
  </port>
160
  <port id="5" precision="U8">
161
+ <dim>704</dim>
162
  </port>
163
  </input>
164
  <output>
 
177
  <port id="10" precision="U8">
178
  <dim>-1</dim>
179
  </port>
180
+ <port id="11" precision="BOOL">
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
181
  <dim>-1</dim>
182
  </port>
183
  </output>
184
  </layer>
185
+ <layer id="16" name="NormalizeUnicode_67118" type="NormalizeUnicode" version="extension">
186
+ <data normalization_form="NFC" />
187
  <input>
188
  <port id="0" precision="I32">
189
  <dim>-1</dim>
 
191
  <port id="1" precision="I32">
192
  <dim>-1</dim>
193
  </port>
194
+ <port id="2" precision="U8">
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
195
  <dim>-1</dim>
196
  </port>
197
+ <port id="3" precision="BOOL">
198
  <dim>-1</dim>
199
  </port>
200
  </input>
201
  <output>
202
+ <port id="4" precision="I32">
203
  <dim>-1</dim>
204
  </port>
205
+ <port id="5" precision="I32">
206
  <dim>-1</dim>
207
  </port>
208
+ <port id="6" precision="U8">
209
  <dim>-1</dim>
210
  </port>
211
+ <port id="7" precision="BOOL">
212
  <dim>-1</dim>
213
  </port>
214
+ </output>
215
+ </layer>
216
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217
+ <data element_type="u8" shape="64" offset="720" size="64" />
218
+ <output>
219
+ <port id="0" precision="U8">
220
+ <dim>64</dim>
221
  </port>
222
  </output>
223
  </layer>
224
+ <layer id="18" name="RegexSplit_67121" type="RegexSplit" version="extension">
225
+ <data behaviour="isolate" invert="false" max_splits="-1" />
226
  <input>
227
  <port id="0" precision="I32">
228
  <dim>-1</dim>
 
239
  <port id="4" precision="U8">
240
  <dim>-1</dim>
241
  </port>
242
+ <port id="5" precision="BOOL">
243
+ <dim>-1</dim>
244
+ </port>
245
+ <port id="6" precision="U8">
246
+ <dim>64</dim>
247
+ </port>
248
  </input>
249
  <output>
250
+ <port id="7" precision="I32">
251
  <dim>-1</dim>
252
  </port>
253
+ <port id="8" precision="I32">
254
  <dim>-1</dim>
255
  </port>
256
+ <port id="9" precision="I32">
257
  <dim>-1</dim>
258
  </port>
259
+ <port id="10" precision="I32">
260
  <dim>-1</dim>
261
  </port>
262
+ <port id="11" precision="U8">
263
+ <dim>-1</dim>
264
+ </port>
265
+ <port id="12" precision="BOOL">
266
  <dim>-1</dim>
267
  </port>
268
  </output>
269
  </layer>
270
+ <layer id="19" name="Constant_67123" type="Const" version="opset1">
271
+ <data element_type="u8" shape="514030" offset="784" size="514030" />
272
  <output>
273
  <port id="0" precision="U8">
274
+ <dim>514030</dim>
275
  </port>
276
  </output>
277
  </layer>
278
+ <layer id="20" name="StringTensorUnpack_67124" type="StringTensorUnpack" version="extension">
279
  <data mode="begins_ends" />
280
  <input>
281
  <port id="0" precision="U8">
282
+ <dim>514030</dim>
283
  </port>
284
  </input>
285
  <output>
 
294
  </port>
295
  </output>
296
  </layer>
297
+ <layer id="21" name="Constant_67129" type="Const" version="opset1">
298
+ <data element_type="u8" shape="362936" offset="514814" size="362936" />
299
  <output>
300
  <port id="0" precision="U8">
301
+ <dim>362936</dim>
302
  </port>
303
  </output>
304
  </layer>
305
+ <layer id="22" name="StringTensorUnpack_67130" type="StringTensorUnpack" version="extension">
306
  <data mode="begins_ends" />
307
  <input>
308
  <port id="0" precision="U8">
309
+ <dim>362936</dim>
310
  </port>
311
  </input>
312
  <output>
 
321
  </port>
322
  </output>
323
  </layer>
324
+ <layer id="23" name="Constant_67132" type="Const" version="opset1">
325
+ <data element_type="u8" shape="349500" offset="877750" size="349500" />
 
 
 
 
 
 
326
  <output>
327
  <port id="0" precision="U8">
328
+ <dim>349500</dim>
329
  </port>
330
  </output>
331
  </layer>
332
+ <layer id="24" name="StringTensorUnpack_67133" type="StringTensorUnpack" version="extension">
333
  <data mode="begins_ends" />
334
  <input>
335
  <port id="0" precision="U8">
336
+ <dim>349500</dim>
337
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338
  </input>
339
  <output>
 
348
  </port>
349
  </output>
350
  </layer>
351
+ <layer id="25" name="Constant_67126" type="Const" version="opset1">
352
+ <data element_type="u8" shape="414" offset="1227250" size="414" />
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
353
  <output>
354
+ <port id="0" precision="U8">
355
+ <dim>414</dim>
 
 
 
 
 
 
356
  </port>
 
 
 
 
 
357
  </output>
358
  </layer>
359
+ <layer id="26" name="StringTensorUnpack_67127" type="StringTensorUnpack" version="extension">
360
+ <data mode="begins_ends" />
 
 
 
 
 
 
361
  <input>
362
+ <port id="0" precision="U8">
363
+ <dim>414</dim>
 
 
 
 
 
364
  </port>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
365
  </input>
366
  <output>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
367
  <port id="1" precision="I32">
368
  <dim>-1</dim>
369
  </port>
370
  <port id="2" precision="I32">
371
  <dim>-1</dim>
372
  </port>
373
+ <port id="3" precision="U8">
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
374
  <dim>-1</dim>
375
  </port>
376
  </output>
377
  </layer>
378
+ <layer id="27" name="Constant_67134" type="Const" version="opset1">
379
+ <data element_type="i32" shape="24" offset="1227664" size="96" />
380
  <output>
381
  <port id="0" precision="I32">
382
+ <dim>24</dim>
383
  </port>
384
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385
  </layer>
386
+ <layer id="28" name="BPETokenizer_67135" type="BPETokenizer" version="extension">
387
+ <data unk_token="" fuse_unk="false" suffix_indicator="" end_suffix="" byte_fallback="false" cache_capacity="20000" />
388
  <input>
389
  <port id="0" precision="I32">
390
  <dim>-1</dim>
 
429
  <dim>-1</dim>
430
  </port>
431
  <port id="14" precision="I32">
432
+ <dim>-1</dim>
433
  </port>
 
 
434
  <port id="15" precision="I32">
435
  <dim>-1</dim>
436
  </port>
437
+ <port id="16" precision="U8">
438
  <dim>-1</dim>
439
  </port>
440
  <port id="17" precision="I32">
441
+ <dim>24</dim>
442
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443
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444
+ <output>
445
+ <port id="18" precision="I32">
446
+ <dim>-1</dim>
447
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448
+ <port id="19" precision="I32">
449
+ <dim>-1</dim>
450
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451
+ <port id="20" precision="I32">
452
  <dim>-1</dim>
453
  </port>
454
  </output>
455
  </layer>
456
+ <layer id="29" name="Subtract_67136" type="Subtract" version="opset1">
457
  <data auto_broadcast="numpy" />
458
  <input>
459
  <port id="0" precision="I32">
 
469
  </port>
470
  </output>
471
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472
+ <layer id="30" name="Constant_67137" type="Const" version="opset1">
473
+ <data element_type="i32" shape="" offset="1227760" size="4" />
474
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475
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757
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759
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760
  <eos_token_id value="0" />
761
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762
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763
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tokenizer.json CHANGED
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