diff --git "a/openvino_model.xml.xml" "b/openvino_model.xml.xml"
new file mode 100644--- /dev/null
+++ "b/openvino_model.xml.xml"
@@ -0,0 +1,7363 @@
+<?xml version="1.0"?>
+<net name="Model0" version="11">
+	<layers>
+		<layer id="2" name="input_ids" type="Parameter" version="opset1">
+			<data shape="?,?" element_type="i64" />
+			<output>
+				<port id="0" precision="I64" names="input_ids">
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1" name="attention_mask" type="Parameter" version="opset1">
+			<data shape="?,?" element_type="i64" />
+			<output>
+				<port id="0" precision="I64" names="39,attention_mask">
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="0" name="token_type_ids" type="Parameter" version="opset1">
+			<data shape="?,?" element_type="i64" />
+			<output>
+				<port id="0" precision="I64" names="token_type_ids">
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="3" name="self.bert.embeddings.word_embeddings.weight_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="61056, 384" offset="0" size="46891008" />
+			<output>
+				<port id="0" precision="FP16" names="self.bert.embeddings.word_embeddings.weight">
+					<dim>61056</dim>
+					<dim>384</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="4" name="self.bert.embeddings.word_embeddings.weight" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>61056</dim>
+					<dim>384</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>61056</dim>
+					<dim>384</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="5" name="__module.bert.embeddings.word_embeddings/aten::embedding/Convert" type="Convert" version="opset1">
+			<data destination_type="i32" />
+			<input>
+				<port id="0" precision="I64">
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="I32">
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="6" name="__module.bert.embeddings.word_embeddings/aten::embedding/Constant" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="46891008" size="4" />
+			<output>
+				<port id="0" precision="I32" />
+			</output>
+		</layer>
+		<layer id="7" name="__module.bert.embeddings.word_embeddings/aten::embedding/Gather" type="Gather" version="opset8">
+			<data batch_dims="0" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>61056</dim>
+					<dim>384</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+				<port id="2" precision="I32" />
+			</input>
+			<output>
+				<port id="3" precision="FP32" names="51,inputs_embeds">
+					<dim>-1</dim>
+					<dim>-1</dim>
+					<dim>384</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="8" name="self.bert.embeddings.token_type_embeddings.weight_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="2, 384" offset="46891012" size="1536" />
+			<output>
+				<port id="0" precision="FP16" names="self.bert.embeddings.token_type_embeddings.weight">
+					<dim>2</dim>
+					<dim>384</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="9" name="self.bert.embeddings.token_type_embeddings.weight" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>2</dim>
+					<dim>384</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>2</dim>
+					<dim>384</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="10" name="__module.bert.embeddings.token_type_embeddings/aten::embedding/Convert" type="Convert" version="opset1">
+			<data destination_type="i32" />
+			<input>
+				<port id="0" precision="I64">
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="I32">
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="11" name="__module.bert.embeddings.token_type_embeddings/aten::embedding/Constant" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="46891008" size="4" />
+			<output>
+				<port id="0" precision="I32" />
+			</output>
+		</layer>
+		<layer id="12" name="__module.bert.embeddings.token_type_embeddings/aten::embedding/Gather" type="Gather" version="opset8">
+			<data batch_dims="0" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>2</dim>
+					<dim>384</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+				<port id="2" precision="I32" />
+			</input>
+			<output>
+				<port id="3" precision="FP32" names="53,token_type_embeddings.1">
+					<dim>-1</dim>
+					<dim>-1</dim>
+					<dim>384</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="13" name="__module.bert.embeddings/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>-1</dim>
+					<dim>-1</dim>
+					<dim>384</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>-1</dim>
+					<dim>-1</dim>
+					<dim>384</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="54,input.1">
+					<dim>-1</dim>
+					<dim>-1</dim>
+					<dim>384</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="14" name="__module.bert.embeddings.LayerNorm/aten::layer_norm/Multiply" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="46892548" size="4" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="15" name="__module.bert.embeddings.LayerNorm/aten::layer_norm/MVN" type="MVN" version="opset6">
+			<data eps="9.999999960041972e-13" normalize_variance="true" eps_mode="INSIDE_SQRT" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>-1</dim>
+					<dim>-1</dim>
+					<dim>384</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>-1</dim>
+					<dim>-1</dim>
+					<dim>384</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="16" name="Constant_4723_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 1, 384" offset="46892552" size="768" />
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>384</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="17" name="Constant_4723" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>384</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>384</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="18" name="__module.bert.embeddings.LayerNorm/aten::layer_norm/Multiply_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>-1</dim>
+					<dim>-1</dim>
+					<dim>384</dim>
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+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>384</dim>
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+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>-1</dim>
+					<dim>-1</dim>
+					<dim>384</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="19" name="Constant_4724_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 1, 384" offset="46893320" size="768" />
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>384</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="20" name="Constant_4724" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>384</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>384</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="21" name="__module.bert.embeddings.LayerNorm/aten::layer_norm/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>-1</dim>
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+				<port id="1" precision="FP32">
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+					<dim>1</dim>
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+			</input>
+			<output>
+				<port id="2" precision="FP32" names="58,input.3">
+					<dim>-1</dim>
+					<dim>-1</dim>
+					<dim>384</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="22" name="self.bert.encoder.model.layer.0.attention.self.query.weight_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="384, 384" offset="46894088" size="294912" />
+			<output>
+				<port id="0" precision="FP16" names="self.bert.encoder.model.layer.0.attention.self.query.weight">
+					<dim>384</dim>
+					<dim>384</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="23" name="self.bert.encoder.model.layer.0.attention.self.query.weight" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>384</dim>
+					<dim>384</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>384</dim>
+					<dim>384</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="24" name="__module.bert.encoder.model.layer.0.attention.self.query/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
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+				<port id="1" precision="FP32">
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+					<dim>384</dim>
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+			</input>
+			<output>
+				<port id="2" precision="FP32">
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+					<dim>-1</dim>
+					<dim>384</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="25" name="Constant_4725_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 1, 384" offset="47189000" size="768" />
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>384</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="26" name="Constant_4725" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
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+			<input>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>384</dim>
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+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>384</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="27" name="__module.bert.encoder.model.layer.0.attention.self.query/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>-1</dim>
+					<dim>-1</dim>
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+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>384</dim>
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+			</input>
+			<output>
+				<port id="2" precision="FP32" names="104,x.9">
+					<dim>-1</dim>
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+					<dim>384</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="28" name="__module.bert.encoder.model.layer.0.attention.self/prim::ListConstruct/Concat" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="47189768" size="32" />
+			<rt_info>
+				<attribute name="precise" version="0" />
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+				<port id="0" precision="I64">
+					<dim>4</dim>
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+		</layer>
+		<layer id="29" name="__module.bert.encoder.model.layer.0.attention.self/aten::view/Reshape" type="Reshape" version="opset1">
+			<data special_zero="true" />
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+				<port id="0" precision="FP32">
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+					<dim>32</dim>
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+		</layer>
+		<layer id="30" name="Constant_302" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="47189800" size="32" />
+			<output>
+				<port id="0" precision="I64" names="127">
+					<dim>4</dim>
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+			</output>
+		</layer>
+		<layer id="31" name="__module.bert.encoder.model.layer.0.attention.self/aten::permute/Transpose" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
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+					<dim>32</dim>
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+				<port id="1" precision="I64">
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+				<port id="2" precision="FP32" names="128,query_layer.1">
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+					<dim>12</dim>
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+		<layer id="32" name="self.bert.encoder.model.layer.0.attention.self.key.weight_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="384, 384" offset="47189832" size="294912" />
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+				<port id="0" precision="FP16" names="self.bert.encoder.model.layer.0.attention.self.key.weight">
+					<dim>384</dim>
+					<dim>384</dim>
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+			</output>
+		</layer>
+		<layer id="33" name="self.bert.encoder.model.layer.0.attention.self.key.weight" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
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+				<port id="0" precision="FP16">
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+					<dim>384</dim>
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+			<output>
+				<port id="1" precision="FP32">
+					<dim>384</dim>
+					<dim>384</dim>
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+			</output>
+		</layer>
+		<layer id="34" name="__module.bert.encoder.model.layer.0.attention.self.key/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
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+		<layer id="35" name="Constant_4726_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 1, 384" offset="47484744" size="768" />
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+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>384</dim>
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+		</layer>
+		<layer id="36" name="Constant_4726" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
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+				<port id="0" precision="FP16">
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+		<layer id="37" name="__module.bert.encoder.model.layer.0.attention.self.key/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
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+			<data element_type="i64" shape="4" offset="47189768" size="32" />
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+</net>