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gemma-2-2b-it-openvino-8bit

Text Generation
Transformers
Safetensors
OpenVINO
gemma2
conversational
nncf
8-bit precision
text-generation-inference
Inference Endpoints
Model card Files Community
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Upload openvino_tokenizer.xml with huggingface_hub

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  1. openvino_tokenizer.xml +51 -51
openvino_tokenizer.xml CHANGED
@@ -1,27 +1,27 @@
1
  <?xml version="1.0"?>
2
  <net name="tokenizer" version="11">
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@@ -29,13 +29,13 @@
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  <port id="0" precision="STRING">
@@ -54,7 +54,7 @@
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@@ -67,19 +67,19 @@
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@@ -92,13 +92,13 @@
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@@ -111,19 +111,19 @@
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@@ -133,13 +133,13 @@
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@@ -152,7 +152,7 @@
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@@ -160,7 +160,7 @@
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@@ -202,7 +202,7 @@
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@@ -210,7 +210,7 @@
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@@ -218,7 +218,7 @@
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@@ -255,7 +255,7 @@
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@@ -263,7 +263,7 @@
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@@ -309,7 +309,7 @@
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@@ -317,7 +317,7 @@
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@@ -336,7 +336,7 @@
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@@ -344,7 +344,7 @@
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@@ -363,7 +363,7 @@
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@@ -371,7 +371,7 @@
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@@ -390,7 +390,7 @@
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@@ -398,7 +398,7 @@
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  <data mode="begins_ends" />
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  <port id="0" precision="U8">
@@ -417,7 +417,7 @@
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  <data element_type="i32" shape="248" offset="12244631" size="992" />
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  <port id="0" precision="I32">
@@ -425,7 +425,7 @@
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- <layer id="33" name="BPETokenizer_1041077" type="BPETokenizer" version="extension">
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@@ -495,7 +495,7 @@
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  <port id="0" precision="I32">
@@ -511,13 +511,13 @@
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  <data auto_broadcast="numpy" />
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@@ -531,7 +531,7 @@
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  <port id="0" precision="I32">
@@ -547,7 +547,7 @@
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@@ -555,7 +555,7 @@
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@@ -596,7 +596,7 @@
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@@ -612,13 +612,13 @@
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@@ -630,13 +630,13 @@
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@@ -662,7 +662,7 @@
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@@ -677,7 +677,7 @@
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@@ -692,7 +692,7 @@
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@@ -715,7 +715,7 @@
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  </output>
220
  </layer>
221
+ <layer id="21" name="RegexNormalization_1672253" type="RegexNormalization" version="extension">
222
  <data global_replace="true" />
223
  <input>
224
  <port id="0" precision="I32">
 
255
  </port>
256
  </output>
257
  </layer>
258
+ <layer id="22" name="Constant_1672255" type="Const" version="opset1">
259
  <data element_type="u8" shape="1" offset="6423" size="1" />
260
  <output>
261
  <port id="0" precision="U8">
 
263
  </port>
264
  </output>
265
  </layer>
266
+ <layer id="23" name="RegexSplit_1672256" type="RegexSplit" version="extension">
267
  <data behaviour="mergedwithprevious" invert="false" max_splits="-1" />
268
  <input>
269
  <port id="0" precision="I32">
 
309
  </port>
310
  </output>
311
  </layer>
312
+ <layer id="24" name="Constant_1672258" type="Const" version="opset1">
313
  <data element_type="u8" shape="2955910" offset="6427" size="2955910" />
314
  <output>
315
  <port id="0" precision="U8">
 
317
  </port>
318
  </output>
319
  </layer>
320
+ <layer id="25" name="StringTensorUnpack_1672259" type="StringTensorUnpack" version="extension">
321
  <data mode="begins_ends" />
322
  <input>
323
  <port id="0" precision="U8">
 
336
  </port>
337
  </output>
338
  </layer>
339
+ <layer id="26" name="Constant_1672264" type="Const" version="opset1">
340
  <data element_type="u8" shape="5031736" offset="2962337" size="5031736" />
341
  <output>
342
  <port id="0" precision="U8">
 
344
  </port>
345
  </output>
346
  </layer>
347
+ <layer id="27" name="StringTensorUnpack_1672265" type="StringTensorUnpack" version="extension">
348
  <data mode="begins_ends" />
349
  <input>
350
  <port id="0" precision="U8">
 
363
  </port>
364
  </output>
365
  </layer>
366
+ <layer id="28" name="Constant_1672267" type="Const" version="opset1">
367
  <data element_type="u8" shape="4245743" offset="7994073" size="4245743" />
368
  <output>
369
  <port id="0" precision="U8">
 
371
  </port>
372
  </output>
373
  </layer>
374
+ <layer id="29" name="StringTensorUnpack_1672268" type="StringTensorUnpack" version="extension">
375
  <data mode="begins_ends" />
376
  <input>
377
  <port id="0" precision="U8">
 
390
  </port>
391
  </output>
392
  </layer>
393
+ <layer id="30" name="Constant_1672261" type="Const" version="opset1">
394
  <data element_type="u8" shape="4815" offset="12239816" size="4815" />
395
  <output>
396
  <port id="0" precision="U8">
 
398
  </port>
399
  </output>
400
  </layer>
401
+ <layer id="31" name="StringTensorUnpack_1672262" type="StringTensorUnpack" version="extension">
402
  <data mode="begins_ends" />
403
  <input>
404
  <port id="0" precision="U8">
 
417
  </port>
418
  </output>
419
  </layer>
420
+ <layer id="32" name="Constant_1672269" type="Const" version="opset1">
421
  <data element_type="i32" shape="248" offset="12244631" size="992" />
422
  <output>
423
  <port id="0" precision="I32">
 
425
  </port>
426
  </output>
427
  </layer>
428
+ <layer id="33" name="BPETokenizer_1672270" type="BPETokenizer" version="extension">
429
  <data unk_token="&lt;unk>" fuse_unk="true" suffix_indicator="" end_suffix="" byte_fallback="true" cache_capacity="51200" />
430
  <input>
431
  <port id="0" precision="I32">
 
495
  </port>
496
  </output>
497
  </layer>
498
+ <layer id="34" name="Subtract_1672271" type="Subtract" version="opset1">
499
  <data auto_broadcast="numpy" />
500
  <input>
501
  <port id="0" precision="I32">
 
511
  </port>
512
  </output>
513
  </layer>
514
+ <layer id="35" name="Constant_1672272" type="Const" version="opset1">
515
  <data element_type="i32" shape="" offset="12245623" size="4" />
516
  <output>
517
  <port id="0" precision="I32" />
518
  </output>
519
  </layer>
520
+ <layer id="36" name="Minimum_1672273" type="Minimum" version="opset1">
521
  <data auto_broadcast="numpy" />
522
  <input>
523
  <port id="0" precision="I32">
 
531
  </port>
532
  </output>
533
  </layer>
534
+ <layer id="37" name="Add_1672274" type="Add" version="opset1">
535
  <data auto_broadcast="numpy" />
536
  <input>
537
  <port id="0" precision="I32">
 
547
  </port>
548
  </output>
549
  </layer>
550
+ <layer id="38" name="Constant_1672278" type="Const" version="opset1">
551
  <data element_type="i32" shape="2" offset="12" size="8" />
552
  <output>
553
  <port id="0" precision="I32">
 
555
  </port>
556
  </output>
557
  </layer>
558
+ <layer id="39" name="CombineSegments_1672279" type="CombineSegments" version="extension">
559
  <input>
560
  <port id="0" precision="I32" />
561
  <port id="1" precision="I32" />
 
596
  </port>
597
  </output>
598
  </layer>
599
+ <layer id="40" name="Subtract_1672280" type="Subtract" version="opset1">
600
  <data auto_broadcast="numpy" />
601
  <input>
602
  <port id="0" precision="I32">
 
612
  </port>
613
  </output>
614
  </layer>
615
+ <layer id="41" name="Constant_1672281" type="Const" version="opset1">
616
  <data element_type="i32" shape="" offset="0" size="4" />
617
  <output>
618
  <port id="0" precision="I32" />
619
  </output>
620
  </layer>
621
+ <layer id="42" name="ReduceMax_1672282" type="ReduceMax" version="opset1">
622
  <data keep_dims="false" />
623
  <input>
624
  <port id="0" precision="I32">
 
630
  <port id="2" precision="I32" />
631
  </output>
632
  </layer>
633
+ <layer id="43" name="Constant_1672283" type="Const" version="opset1">
634
  <data element_type="i32" shape="" offset="0" size="4" />
635
  <output>
636
  <port id="0" precision="I32" />
637
  </output>
638
  </layer>
639
+ <layer id="44" name="RaggedToDense_1672284" type="RaggedToDense" version="extension">
640
  <data pad_right="false" />
641
  <input>
642
  <port id="0" precision="I32">
 
662
  </port>
663
  </output>
664
  </layer>
665
+ <layer id="45" name="Convert_1672285" type="Convert" version="opset1">
666
  <data destination_type="i32" />
667
  <input>
668
  <port id="0" precision="BOOL">
 
677
  </port>
678
  </output>
679
  </layer>
680
+ <layer id="46" name="Convert_1672285" type="Convert" version="opset1">
681
  <data destination_type="i64" />
682
  <input>
683
  <port id="0" precision="I32">
 
692
  </port>
693
  </output>
694
  </layer>
695
+ <layer id="48" name="RaggedToDense_1672284.0" type="Convert" version="opset1">
696
  <data destination_type="i64" />
697
  <input>
698
  <port id="0" precision="I32">
 
707
  </port>
708
  </output>
709
  </layer>
710
+ <layer id="49" name="Result_1672288" type="Result" version="opset1">
711
  <input>
712
  <port id="0" precision="I64">
713
  <dim>-1</dim>
 
715
  </port>
716
  </input>
717
  </layer>
718
+ <layer id="47" name="Result_1672290" type="Result" version="opset1">
719
  <input>
720
  <port id="0" precision="I64">
721
  <dim>-1</dim>