diff --git "a/openvino/openvino_model_qint8_quantized.xml" "b/openvino/openvino_model_qint8_quantized.xml"
new file mode 100644--- /dev/null
+++ "b/openvino/openvino_model_qint8_quantized.xml"
@@ -0,0 +1,21012 @@
+<?xml version="1.0"?>
+<net name="Model523" version="11">
+	<layers>
+		<layer id="1" 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="0" name="attention_mask" type="Parameter" version="opset1">
+			<data shape="?,?" element_type="i64" />
+			<output>
+				<port id="0" precision="I64" names="attention_mask">
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="2" name="Constant_914879" type="Const" version="opset1">
+			<data element_type="i8" shape="51416, 768" offset="0" size="39487488" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>51416</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="3" name="Convert_914880" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>51416</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>51416</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="4" name="Constant_914881" type="Const" version="opset1">
+			<data element_type="f32" shape="51416, 1" offset="39487488" size="205664" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>51416</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="5" name="__module.embeddings.word_embeddings/aten::embedding/Gather/fq_weights_0" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>51416</dim>
+					<dim>768</dim>
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+				<port id="1" precision="FP32">
+					<dim>51416</dim>
+					<dim>1</dim>
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+			<output>
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+					<dim>51416</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="6" name="__module.embeddings.word_embeddings/aten::embedding/Convert" type="Convert" version="opset1">
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+				<port id="0" precision="I64">
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+					<dim>-1</dim>
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+					<dim>-1</dim>
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+			</output>
+		</layer>
+		<layer id="7" name="__module.embeddings.word_embeddings/aten::embedding/Constant" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="39693152" size="4" />
+			<output>
+				<port id="0" precision="I32" />
+			</output>
+		</layer>
+		<layer id="8" name="__module.embeddings.word_embeddings/aten::embedding/Gather" type="Gather" version="opset8">
+			<data batch_dims="0" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>51416</dim>
+					<dim>768</dim>
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+				<port id="1" precision="I32">
+					<dim>-1</dim>
+					<dim>-1</dim>
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+				<port id="2" precision="I32" />
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+			<output>
+				<port id="3" precision="FP32" names="101,inputs_embeds">
+					<dim>-1</dim>
+					<dim>-1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="9" name="Constant_914883" type="Const" version="opset1">
+			<data element_type="i8" shape="10, 768" offset="39693156" size="7680" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>10</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="10" name="Convert_914884" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>10</dim>
+					<dim>768</dim>
+				</port>
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+			<output>
+				<port id="1" precision="FP32">
+					<dim>10</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="11" name="Constant_914885" type="Const" version="opset1">
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+			<output>
+				<port id="0" precision="FP32">
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+					<dim>1</dim>
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+		<layer id="12" name="__module.embeddings.token_type_embeddings/aten::embedding/Gather/fq_weights_0" type="Multiply" version="opset1">
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+				<port id="0" precision="FP32">
+					<dim>10</dim>
+					<dim>768</dim>
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+					<dim>768</dim>
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+		<layer id="13" name="aten::slice/Slice" type="Const" version="opset1">
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+					<dim>1</dim>
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+		<layer id="14" name="aten::slice/Reshape" type="Const" version="opset1">
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+					<dim>1</dim>
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+			</output>
+		</layer>
+		<layer id="15" name="ShapeOf_467287" type="ShapeOf" version="opset3">
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+					<dim>-1</dim>
+					<dim>-1</dim>
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+					<dim>2</dim>
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+			</output>
+		</layer>
+		<layer id="16" name="Constant_467418" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="39709092" size="8" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="17" name="Constant_467289" type="Const" version="opset1">
+			<data element_type="i64" shape="" offset="39709084" size="8" />
+			<output>
+				<port id="0" precision="I64" />
+			</output>
+		</layer>
+		<layer id="18" name="Gather_467290" type="Gather" version="opset8">
+			<data batch_dims="0" />
+			<input>
+				<port id="0" precision="I64">
+					<dim>2</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>1</dim>
+				</port>
+				<port id="2" precision="I64" />
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+			<output>
+				<port id="3" precision="I64" names="13,15,16,17,36,38">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="19" name="aten::slice/Reshape_2" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="39709092" size="8" />
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+				<port id="0" precision="I64">
+					<dim>1</dim>
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+			</output>
+		</layer>
+		<layer id="20" name="aten::slice/Reshape_3" type="Const" version="opset1">
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+			<output>
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+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="21" name="aten::slice/Slice_1" type="Slice" version="opset8">
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+				<port id="4" precision="I64">
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+					<dim>-1</dim>
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+		</layer>
+		<layer id="22" name="aten::expand/Broadcast" type="Broadcast" version="opset3">
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+			<output>
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+		<layer id="28" name="Convert_914888" type="Convert" version="opset1">
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+		<conversion_parameters>
+			<framework value="pytorch" />
+			<is_python_object value="True" />
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+			<friendly_names_were_updated value="True" />
+			<quantization>
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+				<fast_bias_correction value="True" />
+				<ignored_scope>
+					<types value="['GroupNormalization']" />
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+				<model_type value="transformer" />
+				<preset value="mixed" />
+				<subset_size value="300" />
+				<target_device value="ANY" />
+			</quantization>
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+		</optimum>
+	</rt_info>
+</net>