CoolFace
Modelpublic

cross-encoder/ms-marco-MiniLM-L6-v2

sourceHugging Faceapache-2.0updated 1mo agoView on Hugging Face
347likes88.6mdownloads
openvino_model_qint8_quantized.xml11290 linesDownload Raw Back to openvino
1<?xml version="1.0"?>
2<net name="Model110" version="11">
3	<layers>
4		<layer id="2" name="input_ids" type="Parameter" version="opset1">
5			<data shape="?,?" element_type="i64" />
6			<output>
7				<port id="0" precision="I64" names="input_ids">
8					<dim>-1</dim>
9					<dim>-1</dim>
10				</port>
11			</output>
12		</layer>
13		<layer id="1" name="attention_mask" type="Parameter" version="opset1">
14			<data shape="?,?" element_type="i64" />
15			<output>
16				<port id="0" precision="I64" names="attention_mask">
17					<dim>-1</dim>
18					<dim>-1</dim>
19				</port>
20			</output>
21		</layer>
22		<layer id="0" name="token_type_ids" type="Parameter" version="opset1">
23			<data shape="?,?" element_type="i64" />
24			<output>
25				<port id="0" precision="I64" names="token_type_ids">
26					<dim>-1</dim>
27					<dim>-1</dim>
28				</port>
29			</output>
30		</layer>
31		<layer id="3" name="Constant_299926" type="Const" version="opset1">
32			<data element_type="i8" shape="30522, 384" offset="0" size="11720448" />
33			<output>
34				<port id="0" precision="I8">
35					<dim>30522</dim>
36					<dim>384</dim>
37				</port>
38			</output>
39		</layer>
40		<layer id="4" name="Convert_299927" type="Convert" version="opset1">
41			<data destination_type="f32" />
42			<input>
43				<port id="0" precision="I8">
44					<dim>30522</dim>
45					<dim>384</dim>
46				</port>
47			</input>
48			<output>
49				<port id="1" precision="FP32">
50					<dim>30522</dim>
51					<dim>384</dim>
52				</port>
53			</output>
54		</layer>
55		<layer id="5" name="Constant_299928" type="Const" version="opset1">
56			<data element_type="f32" shape="30522, 1" offset="11720448" size="122088" />
57			<output>
58				<port id="0" precision="FP32">
59					<dim>30522</dim>
60					<dim>1</dim>
61				</port>
62			</output>
63		</layer>
64		<layer id="6" name="__module.bert.embeddings.word_embeddings/aten::embedding/Gather/fq_weights_0" type="Multiply" version="opset1">
65			<data auto_broadcast="numpy" />
66			<input>
67				<port id="0" precision="FP32">
68					<dim>30522</dim>
69					<dim>384</dim>
70				</port>
71				<port id="1" precision="FP32">
72					<dim>30522</dim>
73					<dim>1</dim>
74				</port>
75			</input>
76			<output>
77				<port id="2" precision="FP32">
78					<dim>30522</dim>
79					<dim>384</dim>
80				</port>
81			</output>
82		</layer>
83		<layer id="7" name="__module.bert.embeddings.word_embeddings/aten::embedding/Convert" type="Convert" version="opset1">
84			<data destination_type="i32" />
85			<input>
86				<port id="0" precision="I64">
87					<dim>-1</dim>
88					<dim>-1</dim>
89				</port>
90			</input>
91			<output>
92				<port id="1" precision="I32">
93					<dim>-1</dim>
94					<dim>-1</dim>
95				</port>
96			</output>
97		</layer>
98		<layer id="8" name="__module.bert.embeddings.word_embeddings/aten::embedding/Constant" type="Const" version="opset1">
99			<data element_type="i32" shape="" offset="11842536" size="4" />
100			<output>
101				<port id="0" precision="I32" />
102			</output>
103		</layer>
104		<layer id="9" name="__module.bert.embeddings.word_embeddings/aten::embedding/Gather" type="Gather" version="opset8">
105			<data batch_dims="0" />
106			<input>
107				<port id="0" precision="FP32">
108					<dim>30522</dim>
109					<dim>384</dim>
110				</port>
111				<port id="1" precision="I32">
112					<dim>-1</dim>
113					<dim>-1</dim>
114				</port>
115				<port id="2" precision="I32" />
116			</input>
117			<output>
118				<port id="3" precision="FP32" names="48,inputs_embeds">
119					<dim>-1</dim>
120					<dim>-1</dim>
121					<dim>384</dim>
122				</port>
123			</output>
124		</layer>
125		<layer id="10" name="Constant_299930" type="Const" version="opset1">
126			<data element_type="i8" shape="2, 384" offset="11842540" size="768" />
127			<output>
128				<port id="0" precision="I8">
129					<dim>2</dim>
130					<dim>384</dim>
131				</port>
132			</output>
133		</layer>
134		<layer id="11" name="Convert_299931" type="Convert" version="opset1">
135			<data destination_type="f32" />
136			<input>
137				<port id="0" precision="I8">
138					<dim>2</dim>
139					<dim>384</dim>
140				</port>
141			</input>
142			<output>
143				<port id="1" precision="FP32">
144					<dim>2</dim>
145					<dim>384</dim>
146				</port>
147			</output>
148		</layer>
149		<layer id="12" name="Constant_299932" type="Const" version="opset1">
150			<data element_type="f32" shape="2, 1" offset="11843308" size="8" />
151			<output>
152				<port id="0" precision="FP32">
153					<dim>2</dim>
154					<dim>1</dim>
155				</port>
156			</output>
157		</layer>
158		<layer id="13" name="__module.bert.embeddings.token_type_embeddings/aten::embedding/Gather/fq_weights_0" type="Multiply" version="opset1">
159			<data auto_broadcast="numpy" />
160			<input>
161				<port id="0" precision="FP32">
162					<dim>2</dim>
163					<dim>384</dim>
164				</port>
165				<port id="1" precision="FP32">
166					<dim>2</dim>
167					<dim>1</dim>
168				</port>
169			</input>
170			<output>
171				<port id="2" precision="FP32">
172					<dim>2</dim>
173					<dim>384</dim>
174				</port>
175			</output>
176		</layer>
177		<layer id="14" name="__module.bert.embeddings.token_type_embeddings/aten::embedding/Convert" type="Convert" version="opset1">
178			<data destination_type="i32" />
179			<input>
180				<port id="0" precision="I64">
181					<dim>-1</dim>
182					<dim>-1</dim>
183				</port>
184			</input>
185			<output>
186				<port id="1" precision="I32">
187					<dim>-1</dim>
188					<dim>-1</dim>
189				</port>
190			</output>
191		</layer>
192		<layer id="15" name="__module.bert.embeddings.token_type_embeddings/aten::embedding/Constant" type="Const" version="opset1">
193			<data element_type="i32" shape="" offset="11842536" size="4" />
194			<output>
195				<port id="0" precision="I32" />
196			</output>
197		</layer>
198		<layer id="16" name="__module.bert.embeddings.token_type_embeddings/aten::embedding/Gather" type="Gather" version="opset8">
199			<data batch_dims="0" />
200			<input>
201				<port id="0" precision="FP32">
202					<dim>2</dim>
203					<dim>384</dim>
204				</port>
205				<port id="1" precision="I32">
206					<dim>-1</dim>
207					<dim>-1</dim>
208				</port>
209				<port id="2" precision="I32" />
210			</input>
211			<output>
212				<port id="3" precision="FP32" names="50,token_type_embeddings.1">
213					<dim>-1</dim>
214					<dim>-1</dim>
215					<dim>384</dim>
216				</port>
217			</output>
218		</layer>
219		<layer id="17" name="__module.bert.embeddings/aten::add/Add" type="Add" version="opset1">
220			<data auto_broadcast="numpy" />
221			<input>
222				<port id="0" precision="FP32">
223					<dim>-1</dim>
224					<dim>-1</dim>
225					<dim>384</dim>
226				</port>
227				<port id="1" precision="FP32">
228					<dim>-1</dim>
229					<dim>-1</dim>
230					<dim>384</dim>
231				</port>
232			</input>
233			<output>
234				<port id="2" precision="FP32" names="51_1">
235					<dim>-1</dim>
236					<dim>-1</dim>
237					<dim>384</dim>
238				</port>
239			</output>
240		</layer>
241		<layer id="18" name="Constant_299934" type="Const" version="opset1">
242			<data element_type="i8" shape="512, 384" offset="11843316" size="196608" />
243			<output>
244				<port id="0" precision="I8">
245					<dim>512</dim>
246					<dim>384</dim>
247				</port>
248			</output>
249		</layer>
250		<layer id="19" name="Convert_299935" type="Convert" version="opset1">
251			<data destination_type="f32" />
252			<input>
253				<port id="0" precision="I8">
254					<dim>512</dim>
255					<dim>384</dim>
256				</port>
257			</input>
258			<output>
259				<port id="1" precision="FP32">
260					<dim>512</dim>
261					<dim>384</dim>
262				</port>
263			</output>
264		</layer>
265		<layer id="20" name="Constant_299936" type="Const" version="opset1">
266			<data element_type="f32" shape="512, 1" offset="12039924" size="2048" />
267			<output>
268				<port id="0" precision="FP32">
269					<dim>512</dim>
270					<dim>1</dim>
271				</port>
272			</output>
273		</layer>
274		<layer id="21" name="__module.bert.embeddings.position_embeddings/aten::embedding/Gather/fq_weights_0" type="Multiply" version="opset1">
275			<data auto_broadcast="numpy" />
276			<input>
277				<port id="0" precision="FP32">
278					<dim>512</dim>
279					<dim>384</dim>
280				</port>
281				<port id="1" precision="FP32">
282					<dim>512</dim>
283					<dim>1</dim>
284				</port>
285			</input>
286			<output>
287				<port id="2" precision="FP32">
288					<dim>512</dim>
289					<dim>384</dim>
290				</port>
291			</output>
292		</layer>
293		<layer id="22" name="__module.bert.embeddings/aten::slice/Slice" type="Const" version="opset1">
294			<data element_type="i64" shape="1, 512" offset="12041972" size="4096" />
295			<output>
296				<port id="0" precision="I64" names="45">
297					<dim>1</dim>
298					<dim>512</dim>
299				</port>
300			</output>
301		</layer>
302		<layer id="23" name="__module.bert.embeddings/aten::slice/Reshape" type="Const" version="opset1">
303			<data element_type="i64" shape="1" offset="12046068" size="8" />
304			<output>
305				<port id="0" precision="I64">
306					<dim>1</dim>
307				</port>
308			</output>
309		</layer>
310		<layer id="24" name="ShapeOf_90427" type="ShapeOf" version="opset3">
311			<data output_type="i64" />
312			<input>
313				<port id="0" precision="I64">
314					<dim>-1</dim>
315					<dim>-1</dim>
316				</port>
317			</input>
318			<output>
319				<port id="1" precision="I64">
320					<dim>2</dim>
321				</port>
322			</output>
323		</layer>
324		<layer id="25" name="Constant_90546" type="Const" version="opset1">
325			<data element_type="i64" shape="1" offset="12046076" size="8" />
326			<output>
327				<port id="0" precision="I64">
328					<dim>1</dim>
329				</port>
330			</output>
331		</layer>
332		<layer id="26" name="Constant_90429" type="Const" version="opset1">
333			<data element_type="i64" shape="" offset="12046068" size="8" />
334			<output>
335				<port id="0" precision="I64" />
336			</output>
337		</layer>
338		<layer id="27" name="Gather_90430" type="Gather" version="opset8">
339			<data batch_dims="0" />
340			<input>
341				<port id="0" precision="I64">
342					<dim>2</dim>
343				</port>
344				<port id="1" precision="I64">
345					<dim>1</dim>
346				</port>
347				<port id="2" precision="I64" />
348			</input>
349			<output>
350				<port id="3" precision="I64" names="35,41,43,44,61">
351					<dim>1</dim>
352				</port>
353			</output>
354		</layer>
355		<layer id="28" name="__module.bert.embeddings/aten::slice/Reshape_2" type="Const" version="opset1">
356			<data element_type="i64" shape="1" offset="12046076" size="8" />
357			<output>
358				<port id="0" precision="I64">
359					<dim>1</dim>
360				</port>
361			</output>
362		</layer>
363		<layer id="29" name="__module.bert.embeddings/aten::slice/Reshape_3" type="Const" version="opset1">
364			<data element_type="i64" shape="1" offset="12046076" size="8" />
365			<output>
366				<port id="0" precision="I64">
367					<dim>1</dim>
368				</port>
369			</output>
370		</layer>
371		<layer id="30" name="__module.bert.embeddings/aten::slice/Slice_1" type="Slice" version="opset8">
372			<input>
373				<port id="0" precision="I64">
374					<dim>1</dim>
375					<dim>512</dim>
376				</port>
377				<port id="1" precision="I64">
378					<dim>1</dim>
379				</port>
380				<port id="2" precision="I64">
381					<dim>1</dim>
382				</port>
383				<port id="3" precision="I64">
384					<dim>1</dim>
385				</port>
386				<port id="4" precision="I64">
387					<dim>1</dim>
388				</port>
389			</input>
390			<output>
391				<port id="5" precision="I64" names="46">
392					<dim>1</dim>
393					<dim>-1</dim>
394				</port>
395			</output>
396		</layer>
397		<layer id="31" name="__module.bert.embeddings.position_embeddings/aten::embedding/Convert" type="Convert" version="opset1">
398			<data destination_type="i32" />
399			<input>
400				<port id="0" precision="I64">
401					<dim>1</dim>
402					<dim>-1</dim>
403				</port>
404			</input>
405			<output>
406				<port id="1" precision="I32">
407					<dim>1</dim>
408					<dim>-1</dim>
409				</port>
410			</output>
411		</layer>
412		<layer id="32" name="__module.bert.embeddings.position_embeddings/aten::embedding/Constant" type="Const" version="opset1">
413			<data element_type="i32" shape="" offset="11842536" size="4" />
414			<output>
415				<port id="0" precision="I32" />
416			</output>
417		</layer>
418		<layer id="33" name="__module.bert.embeddings.position_embeddings/aten::embedding/Gather" type="Gather" version="opset8">
419			<data batch_dims="0" />
420			<input>
421				<port id="0" precision="FP32">
422					<dim>512</dim>
423					<dim>384</dim>
424				</port>
425				<port id="1" precision="I32">
426					<dim>1</dim>
427					<dim>-1</dim>
428				</port>
429				<port id="2" precision="I32" />
430			</input>
431			<output>
432				<port id="3" precision="FP32" names="53,position_embeddings.1">
433					<dim>1</dim>
434					<dim>-1</dim>
435					<dim>384</dim>
436				</port>
437			</output>
438		</layer>
439		<layer id="34" name="__module.bert.embeddings/aten::add_/Add" type="Add" version="opset1">
440			<data auto_broadcast="numpy" />
441			<input>
442				<port id="0" precision="FP32">
443					<dim>-1</dim>
444					<dim>-1</dim>
445					<dim>384</dim>
446				</port>
447				<port id="1" precision="FP32">
448					<dim>1</dim>
449					<dim>-1</dim>
450					<dim>384</dim>
451				</port>
452			</input>
453			<output>
454				<port id="2" precision="FP32" names="51,embeddings.1">
455					<dim>-1</dim>
456					<dim>-1</dim>
457					<dim>384</dim>
458				</port>
459			</output>
460		</layer>
461		<layer id="35" name="__module.bert.embeddings.LayerNorm/aten::layer_norm/Multiply" type="Const" version="opset1">
462			<data element_type="i32" shape="1" offset="12046084" size="4" />
463			<output>
464				<port id="0" precision="I32">
465					<dim>1</dim>
466				</port>
467			</output>
468		</layer>
469		<layer id="36" name="__module.bert.embeddings.LayerNorm/aten::layer_norm/MVN" type="MVN" version="opset6">
470			<data eps="9.999999960041972e-13" normalize_variance="true" eps_mode="INSIDE_SQRT" />
471			<input>
472				<port id="0" precision="FP32">
473					<dim>-1</dim>
474					<dim>-1</dim>
475					<dim>384</dim>
476				</port>
477				<port id="1" precision="I32">
478					<dim>1</dim>
479				</port>
480			</input>
481			<output>
482				<port id="2" precision="FP32">
483					<dim>-1</dim>
484					<dim>-1</dim>
485					<dim>384</dim>
486				</port>
487			</output>
488		</layer>
489		<layer id="37" name="Constant_90301" type="Const" version="opset1">
490			<data element_type="f32" shape="1, 1, 384" offset="12046088" size="1536" />
491			<output>
492				<port id="0" precision="FP32">
493					<dim>1</dim>
494					<dim>1</dim>
495					<dim>384</dim>
496				</port>
497			</output>
498		</layer>
499		<layer id="38" name="__module.bert.embeddings.LayerNorm/aten::layer_norm/Multiply_1" type="Multiply" version="opset1">
500			<data auto_broadcast="numpy" />
501			<input>
502				<port id="0" precision="FP32">
503					<dim>-1</dim>
504					<dim>-1</dim>
505					<dim>384</dim>
506				</port>
507				<port id="1" precision="FP32">
508					<dim>1</dim>
509					<dim>1</dim>
510					<dim>384</dim>
511				</port>
512			</input>
513			<output>
514				<port id="2" precision="FP32">
515					<dim>-1</dim>
516					<dim>-1</dim>
517					<dim>384</dim>
518				</port>
519			</output>
520		</layer>
521		<layer id="39" name="Constant_90302" type="Const" version="opset1">
522			<data element_type="f32" shape="1, 1, 384" offset="12047624" size="1536" />
523			<output>
524				<port id="0" precision="FP32">
525					<dim>1</dim>
526					<dim>1</dim>
527					<dim>384</dim>
528				</port>
529			</output>
530		</layer>
531		<layer id="40" name="__module.bert.embeddings.LayerNorm/aten::layer_norm/Add" type="Add" version="opset1">
532			<data auto_broadcast="numpy" />
533			<input>
534				<port id="0" precision="FP32">
535					<dim>-1</dim>
536					<dim>-1</dim>
537					<dim>384</dim>
538				</port>
539				<port id="1" precision="FP32">
540					<dim>1</dim>
541					<dim>1</dim>
542					<dim>384</dim>
543				</port>
544			</input>
545			<output>
546				<port id="2" precision="FP32" names="58,input.1">
547					<dim>-1</dim>
548					<dim>-1</dim>
549					<dim>384</dim>
550				</port>
551			</output>
552		</layer>
553		<layer id="41" name="__module.bert.embeddings.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
554			<data element_type="f32" shape="1, 1, 384" offset="12049160" size="1536" />
555			<output>
556				<port id="0" precision="FP32">
557					<dim>1</dim>
558					<dim>1</dim>
559					<dim>384</dim>
560				</port>
561			</output>
562		</layer>
563		<layer id="42" name="__module.bert.embeddings.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
564			<data auto_broadcast="numpy" />
565			<input>
566				<port id="0" precision="FP32">
567					<dim>-1</dim>
568					<dim>-1</dim>
569					<dim>384</dim>
570				</port>
571				<port id="1" precision="FP32">
572					<dim>1</dim>
573					<dim>1</dim>
574					<dim>384</dim>
575				</port>
576			</input>
577			<output>
578				<port id="2" precision="FP32">
579					<dim>-1</dim>
580					<dim>-1</dim>
581					<dim>384</dim>
582				</port>
583			</output>
584		</layer>
585		<layer id="43" name="__module.bert.embeddings.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
586			<data element_type="f32" shape="" offset="12050696" size="4" />
587			<output>
588				<port id="0" precision="FP32" />
589			</output>
590		</layer>
591		<layer id="44" name="__module.bert.embeddings.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
592			<data element_type="f32" shape="" offset="12050700" size="4" />
593			<output>
594				<port id="0" precision="FP32" />
595			</output>
596		</layer>
597		<layer id="45" name="__module.bert.embeddings.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
598			<data element_type="f32" shape="" offset="12050696" size="4" />
599			<output>
600				<port id="0" precision="FP32" />
601			</output>
602		</layer>
603		<layer id="46" name="__module.bert.embeddings.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
604			<data element_type="f32" shape="" offset="12050700" size="4" />
605			<output>
606				<port id="0" precision="FP32" />
607			</output>
608		</layer>
609		<layer id="47" name="__module.bert.embeddings.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
610			<data levels="256" auto_broadcast="numpy" />
611			<input>
612				<port id="0" precision="FP32">
613					<dim>-1</dim>
614					<dim>-1</dim>
615					<dim>384</dim>
616				</port>
617				<port id="1" precision="FP32" />
618				<port id="2" precision="FP32" />
619				<port id="3" precision="FP32" />
620				<port id="4" precision="FP32" />
621			</input>
622			<output>
623				<port id="5" precision="FP32">
624					<dim>-1</dim>
625					<dim>-1</dim>
626					<dim>384</dim>
627				</port>
628			</output>
629		</layer>
630		<layer id="48" name="Constant_299938" type="Const" version="opset1">
631			<data element_type="i8" shape="384, 384" offset="12050704" size="147456" />
632			<output>
633				<port id="0" precision="I8">
634					<dim>384</dim>
635					<dim>384</dim>
636				</port>
637			</output>
638		</layer>
639		<layer id="49" name="Convert_299939" type="Convert" version="opset1">
640			<data destination_type="f32" />
641			<input>
642				<port id="0" precision="I8">
643					<dim>384</dim>
644					<dim>384</dim>
645				</port>
646			</input>
647			<output>
648				<port id="1" precision="FP32">
649					<dim>384</dim>
650					<dim>384</dim>
651				</port>
652			</output>
653		</layer>
654		<layer id="50" name="Constant_299940" type="Const" version="opset1">
655			<data element_type="f32" shape="384, 1" offset="12198160" size="1536" />
656			<output>
657				<port id="0" precision="FP32">
658					<dim>384</dim>
659					<dim>1</dim>
660				</port>
661			</output>
662		</layer>
663		<layer id="51" name="__module.bert.encoder.layer.0.attention.self.query/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
664			<data auto_broadcast="numpy" />
665			<input>
666				<port id="0" precision="FP32">
667					<dim>384</dim>
668					<dim>384</dim>
669				</port>
670				<port id="1" precision="FP32">
671					<dim>384</dim>
672					<dim>1</dim>
673				</port>
674			</input>
675			<output>
676				<port id="2" precision="FP32">
677					<dim>384</dim>
678					<dim>384</dim>
679				</port>
680			</output>
681		</layer>
682		<layer id="52" name="__module.bert.encoder.layer.0.attention.self.query/aten::linear/MatMul" type="MatMul" version="opset1">
683			<data transpose_a="false" transpose_b="true" />
684			<input>
685				<port id="0" precision="FP32">
686					<dim>-1</dim>
687					<dim>-1</dim>
688					<dim>384</dim>
689				</port>
690				<port id="1" precision="FP32">
691					<dim>384</dim>
692					<dim>384</dim>
693				</port>
694			</input>
695			<output>
696				<port id="2" precision="FP32">
697					<dim>-1</dim>
698					<dim>-1</dim>
699					<dim>384</dim>
700				</port>
701			</output>
702		</layer>
703		<layer id="53" name="Constant_90303" type="Const" version="opset1">
704			<data element_type="f32" shape="1, 1, 384" offset="12199696" size="1536" />
705			<output>
706				<port id="0" precision="FP32">
707					<dim>1</dim>
708					<dim>1</dim>
709					<dim>384</dim>
710				</port>
711			</output>
712		</layer>
713		<layer id="54" name="__module.bert.encoder.layer.0.attention.self.query/aten::linear/Add" type="Add" version="opset1">
714			<data auto_broadcast="numpy" />
715			<input>
716				<port id="0" precision="FP32">
717					<dim>-1</dim>
718					<dim>-1</dim>
719					<dim>384</dim>
720				</port>
721				<port id="1" precision="FP32">
722					<dim>1</dim>
723					<dim>1</dim>
724					<dim>384</dim>
725				</port>
726			</input>
727			<output>
728				<port id="2" precision="FP32" names="96,x.1">
729					<dim>-1</dim>
730					<dim>-1</dim>
731					<dim>384</dim>
732				</port>
733			</output>
734		</layer>
735		<layer id="55" name="__module.bert.encoder.layer.0.attention.self.query/aten::linear/Add/fq_output_0/input_low" type="Const" version="opset1">
736			<data element_type="f32" shape="" offset="12201232" size="4" />
737			<output>
738				<port id="0" precision="FP32" />
739			</output>
740		</layer>
741		<layer id="56" name="__module.bert.encoder.layer.0.attention.self.query/aten::linear/Add/fq_output_0/input_high" type="Const" version="opset1">
742			<data element_type="f32" shape="" offset="12201236" size="4" />
743			<output>
744				<port id="0" precision="FP32" />
745			</output>
746		</layer>
747		<layer id="57" name="__module.bert.encoder.layer.0.attention.self.query/aten::linear/Add/fq_output_0/output_low" type="Const" version="opset1">
748			<data element_type="f32" shape="" offset="12201232" size="4" />
749			<output>
750				<port id="0" precision="FP32" />
751			</output>
752		</layer>
753		<layer id="58" name="__module.bert.encoder.layer.0.attention.self.query/aten::linear/Add/fq_output_0/output_high" type="Const" version="opset1">
754			<data element_type="f32" shape="" offset="12201236" size="4" />
755			<output>
756				<port id="0" precision="FP32" />
757			</output>
758		</layer>
759		<layer id="59" name="__module.bert.encoder.layer.0.attention.self.query/aten::linear/Add/fq_output_0" type="FakeQuantize" version="opset1">
760			<data levels="256" auto_broadcast="numpy" />
761			<input>
762				<port id="0" precision="FP32">
763					<dim>-1</dim>
764					<dim>-1</dim>
765					<dim>384</dim>
766				</port>
767				<port id="1" precision="FP32" />
768				<port id="2" precision="FP32" />
769				<port id="3" precision="FP32" />
770				<port id="4" precision="FP32" />
771			</input>
772			<output>
773				<port id="5" precision="FP32">
774					<dim>-1</dim>
775					<dim>-1</dim>
776					<dim>384</dim>
777				</port>
778			</output>
779		</layer>
780		<layer id="60" name="__module.bert.encoder.layer.0.attention.self/prim::ListConstruct/Concat" type="Const" version="opset1">
781			<data element_type="i64" shape="4" offset="12201240" size="32" />
782			<output>
783				<port id="0" precision="I64">
784					<dim>4</dim>
785				</port>
786			</output>
787		</layer>
788		<layer id="61" name="__module.bert.encoder.layer.0.attention.self/aten::view/Reshape" type="Reshape" version="opset1">
789			<data special_zero="true" />
790			<input>
791				<port id="0" precision="FP32">
792					<dim>-1</dim>
793					<dim>-1</dim>
794					<dim>384</dim>
795				</port>
796				<port id="1" precision="I64">
797					<dim>4</dim>
798				</port>
799			</input>
800			<output>
801				<port id="2" precision="FP32" names="100,x.3">
802					<dim>-1</dim>
803					<dim>-1</dim>
804					<dim>12</dim>
805					<dim>32</dim>
806				</port>
807			</output>
808		</layer>
809		<layer id="62" name="Constant_84452" type="Const" version="opset1">
810			<data element_type="i64" shape="4" offset="12201272" size="32" />
811			<output>
812				<port id="0" precision="I64" names="101">
813					<dim>4</dim>
814				</port>
815			</output>
816		</layer>
817		<layer id="63" name="__module.bert.encoder.layer.0.attention.self/aten::permute/Transpose" type="Transpose" version="opset1">
818			<input>
819				<port id="0" precision="FP32">
820					<dim>-1</dim>
821					<dim>-1</dim>
822					<dim>12</dim>
823					<dim>32</dim>
824				</port>
825				<port id="1" precision="I64">
826					<dim>4</dim>
827				</port>
828			</input>
829			<output>
830				<port id="2" precision="FP32" names="102">
831					<dim>-1</dim>
832					<dim>12</dim>
833					<dim>-1</dim>
834					<dim>32</dim>
835				</port>
836			</output>
837		</layer>
838		<layer id="64" name="Constant_299942" type="Const" version="opset1">
839			<data element_type="i8" shape="384, 384" offset="12201304" size="147456" />
840			<output>
841				<port id="0" precision="I8">
842					<dim>384</dim>
843					<dim>384</dim>
844				</port>
845			</output>
846		</layer>
847		<layer id="65" name="Convert_299943" type="Convert" version="opset1">
848			<data destination_type="f32" />
849			<input>
850				<port id="0" precision="I8">
851					<dim>384</dim>
852					<dim>384</dim>
853				</port>
854			</input>
855			<output>
856				<port id="1" precision="FP32">
857					<dim>384</dim>
858					<dim>384</dim>
859				</port>
860			</output>
861		</layer>
862		<layer id="66" name="Constant_299944" type="Const" version="opset1">
863			<data element_type="f32" shape="384, 1" offset="12348760" size="1536" />
864			<output>
865				<port id="0" precision="FP32">
866					<dim>384</dim>
867					<dim>1</dim>
868				</port>
869			</output>
870		</layer>
871		<layer id="67" name="__module.bert.encoder.layer.0.attention.self.key/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
872			<data auto_broadcast="numpy" />
873			<input>
874				<port id="0" precision="FP32">
875					<dim>384</dim>
876					<dim>384</dim>
877				</port>
878				<port id="1" precision="FP32">
879					<dim>384</dim>
880					<dim>1</dim>
881				</port>
882			</input>
883			<output>
884				<port id="2" precision="FP32">
885					<dim>384</dim>
886					<dim>384</dim>
887				</port>
888			</output>
889		</layer>
890		<layer id="68" name="__module.bert.encoder.layer.0.attention.self.key/aten::linear/MatMul" type="MatMul" version="opset1">
891			<data transpose_a="false" transpose_b="true" />
892			<input>
893				<port id="0" precision="FP32">
894					<dim>-1</dim>
895					<dim>-1</dim>
896					<dim>384</dim>
897				</port>
898				<port id="1" precision="FP32">
899					<dim>384</dim>
900					<dim>384</dim>
901				</port>
902			</input>
903			<output>
904				<port id="2" precision="FP32">
905					<dim>-1</dim>
906					<dim>-1</dim>
907					<dim>384</dim>
908				</port>
909			</output>
910		</layer>
911		<layer id="69" name="Constant_90304" type="Const" version="opset1">
912			<data element_type="f32" shape="1, 1, 384" offset="12350296" size="1536" />
913			<output>
914				<port id="0" precision="FP32">
915					<dim>1</dim>
916					<dim>1</dim>
917					<dim>384</dim>
918				</port>
919			</output>
920		</layer>
921		<layer id="70" name="__module.bert.encoder.layer.0.attention.self.key/aten::linear/Add" type="Add" version="opset1">
922			<data auto_broadcast="numpy" />
923			<input>
924				<port id="0" precision="FP32">
925					<dim>-1</dim>
926					<dim>-1</dim>
927					<dim>384</dim>
928				</port>
929				<port id="1" precision="FP32">
930					<dim>1</dim>
931					<dim>1</dim>
932					<dim>384</dim>
933				</port>
934			</input>
935			<output>
936				<port id="2" precision="FP32" names="105,x.5">
937					<dim>-1</dim>
938					<dim>-1</dim>
939					<dim>384</dim>
940				</port>
941			</output>
942		</layer>
943		<layer id="71" name="__module.bert.encoder.layer.0.attention.self.key/aten::linear/Add/fq_output_0/input_low" type="Const" version="opset1">
944			<data element_type="f32" shape="" offset="12351832" size="4" />
945			<output>
946				<port id="0" precision="FP32" />
947			</output>
948		</layer>
949		<layer id="72" name="__module.bert.encoder.layer.0.attention.self.key/aten::linear/Add/fq_output_0/input_high" type="Const" version="opset1">
950			<data element_type="f32" shape="" offset="12351836" size="4" />
951			<output>
952				<port id="0" precision="FP32" />
953			</output>
954		</layer>
955		<layer id="73" name="__module.bert.encoder.layer.0.attention.self.key/aten::linear/Add/fq_output_0/output_low" type="Const" version="opset1">
956			<data element_type="f32" shape="" offset="12351832" size="4" />
957			<output>
958				<port id="0" precision="FP32" />
959			</output>
960		</layer>
961		<layer id="74" name="__module.bert.encoder.layer.0.attention.self.key/aten::linear/Add/fq_output_0/output_high" type="Const" version="opset1">
962			<data element_type="f32" shape="" offset="12351836" size="4" />
963			<output>
964				<port id="0" precision="FP32" />
965			</output>
966		</layer>
967		<layer id="75" name="__module.bert.encoder.layer.0.attention.self.key/aten::linear/Add/fq_output_0" type="FakeQuantize" version="opset1">
968			<data levels="256" auto_broadcast="numpy" />
969			<input>
970				<port id="0" precision="FP32">
971					<dim>-1</dim>
972					<dim>-1</dim>
973					<dim>384</dim>
974				</port>
975				<port id="1" precision="FP32" />
976				<port id="2" precision="FP32" />
977				<port id="3" precision="FP32" />
978				<port id="4" precision="FP32" />
979			</input>
980			<output>
981				<port id="5" precision="FP32">
982					<dim>-1</dim>
983					<dim>-1</dim>
984					<dim>384</dim>
985				</port>
986			</output>
987		</layer>
988		<layer id="76" name="__module.bert.encoder.layer.0.attention.self/prim::ListConstruct/Concat_1" type="Const" version="opset1">
989			<data element_type="i64" shape="4" offset="12201240" size="32" />
990			<output>
991				<port id="0" precision="I64">
992					<dim>4</dim>
993				</port>
994			</output>
995		</layer>
996		<layer id="77" name="__module.bert.encoder.layer.0.attention.self/aten::view/Reshape_1" type="Reshape" version="opset1">
997			<data special_zero="true" />
998			<input>
999				<port id="0" precision="FP32">
1000					<dim>-1</dim>
1001					<dim>-1</dim>
1002					<dim>384</dim>
1003				</port>
1004				<port id="1" precision="I64">
1005					<dim>4</dim>
1006				</port>
1007			</input>
1008			<output>
1009				<port id="2" precision="FP32" names="109,x.7">
1010					<dim>-1</dim>
1011					<dim>-1</dim>
1012					<dim>12</dim>
1013					<dim>32</dim>
1014				</port>
1015			</output>
1016		</layer>
1017		<layer id="78" name="Constant_84477" type="Const" version="opset1">
1018			<data element_type="i64" shape="4" offset="12201272" size="32" />
1019			<output>
1020				<port id="0" precision="I64" names="110">
1021					<dim>4</dim>
1022				</port>
1023			</output>
1024		</layer>
1025		<layer id="79" name="__module.bert.encoder.layer.0.attention.self/aten::permute/Transpose_1" type="Transpose" version="opset1">
1026			<input>
1027				<port id="0" precision="FP32">
1028					<dim>-1</dim>
1029					<dim>-1</dim>
1030					<dim>12</dim>
1031					<dim>32</dim>
1032				</port>
1033				<port id="1" precision="I64">
1034					<dim>4</dim>
1035				</port>
1036			</input>
1037			<output>
1038				<port id="2" precision="FP32" names="111">
1039					<dim>-1</dim>
1040					<dim>12</dim>
1041					<dim>-1</dim>
1042					<dim>32</dim>
1043				</port>
1044			</output>
1045		</layer>
1046		<layer id="80" name="Constant_299946" type="Const" version="opset1">
1047			<data element_type="i8" shape="384, 384" offset="12351840" size="147456" />
1048			<output>
1049				<port id="0" precision="I8">
1050					<dim>384</dim>
1051					<dim>384</dim>
1052				</port>
1053			</output>
1054		</layer>
1055		<layer id="81" name="Convert_299947" type="Convert" version="opset1">
1056			<data destination_type="f32" />
1057			<input>
1058				<port id="0" precision="I8">
1059					<dim>384</dim>
1060					<dim>384</dim>
1061				</port>
1062			</input>
1063			<output>
1064				<port id="1" precision="FP32">
1065					<dim>384</dim>
1066					<dim>384</dim>
1067				</port>
1068			</output>
1069		</layer>
1070		<layer id="82" name="Constant_299948" type="Const" version="opset1">
1071			<data element_type="f32" shape="384, 1" offset="12499296" size="1536" />
1072			<output>
1073				<port id="0" precision="FP32">
1074					<dim>384</dim>
1075					<dim>1</dim>
1076				</port>
1077			</output>
1078		</layer>
1079		<layer id="83" name="__module.bert.encoder.layer.0.attention.self.value/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
1080			<data auto_broadcast="numpy" />
1081			<input>
1082				<port id="0" precision="FP32">
1083					<dim>384</dim>
1084					<dim>384</dim>
1085				</port>
1086				<port id="1" precision="FP32">
1087					<dim>384</dim>
1088					<dim>1</dim>
1089				</port>
1090			</input>
1091			<output>
1092				<port id="2" precision="FP32">
1093					<dim>384</dim>
1094					<dim>384</dim>
1095				</port>
1096			</output>
1097		</layer>
1098		<layer id="84" name="__module.bert.encoder.layer.0.attention.self.value/aten::linear/MatMul" type="MatMul" version="opset1">
1099			<data transpose_a="false" transpose_b="true" />
1100			<input>
1101				<port id="0" precision="FP32">
1102					<dim>-1</dim>
1103					<dim>-1</dim>
1104					<dim>384</dim>
1105				</port>
1106				<port id="1" precision="FP32">
1107					<dim>384</dim>
1108					<dim>384</dim>
1109				</port>
1110			</input>
1111			<output>
1112				<port id="2" precision="FP32">
1113					<dim>-1</dim>
1114					<dim>-1</dim>
1115					<dim>384</dim>
1116				</port>
1117			</output>
1118		</layer>
1119		<layer id="85" name="Constant_90305" type="Const" version="opset1">
1120			<data element_type="f32" shape="1, 1, 384" offset="12500832" size="1536" />
1121			<output>
1122				<port id="0" precision="FP32">
1123					<dim>1</dim>
1124					<dim>1</dim>
1125					<dim>384</dim>
1126				</port>
1127			</output>
1128		</layer>
1129		<layer id="86" name="__module.bert.encoder.layer.0.attention.self.value/aten::linear/Add" type="Add" version="opset1">
1130			<data auto_broadcast="numpy" />
1131			<input>
1132				<port id="0" precision="FP32">
1133					<dim>-1</dim>
1134					<dim>-1</dim>
1135					<dim>384</dim>
1136				</port>
1137				<port id="1" precision="FP32">
1138					<dim>1</dim>
1139					<dim>1</dim>
1140					<dim>384</dim>
1141				</port>
1142			</input>
1143			<output>
1144				<port id="2" precision="FP32" names="114,x.9">
1145					<dim>-1</dim>
1146					<dim>-1</dim>
1147					<dim>384</dim>
1148				</port>
1149			</output>
1150		</layer>
1151		<layer id="87" name="__module.bert.encoder.layer.0.attention.self/prim::ListConstruct/Concat_2" type="Const" version="opset1">
1152			<data element_type="i64" shape="4" offset="12201240" size="32" />
1153			<output>
1154				<port id="0" precision="I64">
1155					<dim>4</dim>
1156				</port>
1157			</output>
1158		</layer>
1159		<layer id="88" name="__module.bert.encoder.layer.0.attention.self/aten::view/Reshape_2" type="Reshape" version="opset1">
1160			<data special_zero="true" />
1161			<input>
1162				<port id="0" precision="FP32">
1163					<dim>-1</dim>
1164					<dim>-1</dim>
1165					<dim>384</dim>
1166				</port>
1167				<port id="1" precision="I64">
1168					<dim>4</dim>
1169				</port>
1170			</input>
1171			<output>
1172				<port id="2" precision="FP32" names="118,x.11">
1173					<dim>-1</dim>
1174					<dim>-1</dim>
1175					<dim>12</dim>
1176					<dim>32</dim>
1177				</port>
1178			</output>
1179		</layer>
1180		<layer id="89" name="Constant_84502" type="Const" version="opset1">
1181			<data element_type="i64" shape="4" offset="12201272" size="32" />
1182			<output>
1183				<port id="0" precision="I64" names="119">
1184					<dim>4</dim>
1185				</port>
1186			</output>
1187		</layer>
1188		<layer id="90" name="__module.bert.encoder.layer.0.attention.self/aten::permute/Transpose_2" type="Transpose" version="opset1">
1189			<input>
1190				<port id="0" precision="FP32">
1191					<dim>-1</dim>
1192					<dim>-1</dim>
1193					<dim>12</dim>
1194					<dim>32</dim>
1195				</port>
1196				<port id="1" precision="I64">
1197					<dim>4</dim>
1198				</port>
1199			</input>
1200			<output>

Showing the first 1,200 of 11290 lines. Download the file for the rest.