diff --git "a/openvino_model.xml" "b/openvino_model.xml"
new file mode 100644--- /dev/null
+++ "b/openvino_model.xml"
@@ -0,0 +1,140627 @@
+<?xml version="1.0"?>
+<net name="Model0" version="11">
+	<layers>
+		<layer id="3" 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="2" 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="1" name="position_ids" type="Parameter" version="opset1">
+			<data shape="?,?" element_type="i64" />
+			<output>
+				<port id="0" precision="I64" names="position_ids">
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="0" name="beam_idx" type="Parameter" version="opset1">
+			<data shape="?" element_type="i32" />
+			<output>
+				<port id="0" precision="I32" names="beam_idx">
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="4" name="Constant_395356" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="0" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="5" name="ShapeOf_395342" type="ShapeOf" version="opset3">
+			<data output_type="i64" />
+			<input>
+				<port id="0" precision="I64">
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="I64">
+					<dim>2</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="6" name="Constant_395344" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="0" size="4" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="7" name="Constant_395346" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="0" size="4" />
+			<output>
+				<port id="0" precision="I32" />
+			</output>
+		</layer>
+		<layer id="8" name="Gather_395347" type="Gather" version="opset8">
+			<data batch_dims="0" />
+			<input>
+				<port id="0" precision="I64">
+					<dim>2</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+				</port>
+				<port id="2" precision="I32" />
+			</input>
+			<output>
+				<port id="3" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="9" name="Constant_395349" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="4" size="8" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="10" name="Constant_395351" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="12" size="8" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="11" name="Constant_395353" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="20" size="8" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="12" name="Concat_395354" type="Concat" version="opset1">
+			<data axis="0" />
+			<input>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>1</dim>
+				</port>
+				<port id="2" precision="I64">
+					<dim>1</dim>
+				</port>
+				<port id="3" precision="I64">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="4" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="13" name="Broadcast_395357" type="Broadcast" version="opset3">
+			<data mode="numpy" />
+			<input>
+				<port id="0" precision="FP32" />
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>-1</dim>
+					<dim>2</dim>
+					<dim>0</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="14" name="ReadValue_387265" type="ReadValue" version="opset6">
+			<data variable_id="past_key_values.9.valuepresent.9.value" variable_type="f32" variable_shape="?,2,?,128" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>-1</dim>
+					<dim>2</dim>
+					<dim>0</dim>
+					<dim>128</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="past_key_values.9.value">
+					<dim>-1</dim>
+					<dim>2</dim>
+					<dim>-1</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="15" name="Constant_378890" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="0" size="4" />
+			<output>
+				<port id="0" precision="I32" />
+			</output>
+		</layer>
+		<layer id="16" name="Gather_378891" type="Gather" version="opset8">
+			<data batch_dims="0" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>-1</dim>
+					<dim>2</dim>
+					<dim>-1</dim>
+					<dim>128</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>-1</dim>
+				</port>
+				<port id="2" precision="I32" />
+			</input>
+			<output>
+				<port id="3" precision="FP32">
+					<dim>-1</dim>
+					<dim>2</dim>
+					<dim>-1</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="17" name="Constant_334404" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 2048" offset="28" size="8192" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>2048</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="18" name="self.model.embed_tokens.weight" type="Const" version="opset1">
+			<data element_type="u8" shape="151936, 2048" offset="8220" size="311164928" />
+			<output>
+				<port id="0" precision="U8">
+					<dim>151936</dim>
+					<dim>2048</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="19" name="Convert_436050" type="Convert" version="opset1">
+			<data destination_type="f16" />
+			<input>
+				<port id="0" precision="U8">
+					<dim>151936</dim>
+					<dim>2048</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP16">
+					<dim>151936</dim>
+					<dim>2048</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="20" name="self.model.embed_tokens.weight/zero_point" type="Const" version="opset1">
+			<data element_type="u8" shape="151936, 1" offset="311173148" size="151936" />
+			<output>
+				<port id="0" precision="U8">
+					<dim>151936</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="21" name="Convert_436053" type="Convert" version="opset1">
+			<data destination_type="f16" />
+			<input>
+				<port id="0" precision="U8">
+					<dim>151936</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP16">
+					<dim>151936</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="22" name="self.model.embed_tokens.weight/zero_point/subtract" type="Subtract" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP16">
+					<dim>151936</dim>
+					<dim>2048</dim>
+				</port>
+				<port id="1" precision="FP16">
+					<dim>151936</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP16">
+					<dim>151936</dim>
+					<dim>2048</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="23" name="self.model.embed_tokens.weight/scale" type="Const" version="opset1">
+			<data element_type="f16" shape="151936, 1" offset="311325084" size="303872" />
+			<output>
+				<port id="0" precision="FP16">
+					<dim>151936</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="24" name="self.model.embed_tokens.weight/fq_weights_0" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP16">
+					<dim>151936</dim>
+					<dim>2048</dim>
+				</port>
+				<port id="1" precision="FP16">
+					<dim>151936</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP16">
+					<dim>151936</dim>
+					<dim>2048</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="25" name="__module.model.embed_tokens/prim::PythonOp/Convert" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>151936</dim>
+					<dim>2048</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>151936</dim>
+					<dim>2048</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="26" name="__module.model.embed_tokens/prim::PythonOp/Convert_1" 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="27" name="__module.model.embed_tokens/prim::PythonOp/Constant" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="0" size="4" />
+			<output>
+				<port id="0" precision="I32" />
+			</output>
+		</layer>
+		<layer id="28" name="__module.model.embed_tokens/prim::PythonOp/Gather" type="Gather" version="opset8">
+			<data batch_dims="0" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>151936</dim>
+					<dim>2048</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="338,391,402,hidden_states.1,inputs_embeds">
+					<dim>-1</dim>
+					<dim>-1</dim>
+					<dim>2048</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="29" name="Constant_334313" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 2048" offset="311628956" size="8192" />
+			<output>
+				<port id="0" precision="FP32">
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+					<dim>1</dim>
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+			</output>
+		</layer>
+		<layer id="30" name="Constant_334312" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 1" offset="311637148" size="4" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="31" name="Constant_334310" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 1" offset="311637152" size="4" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="32" name="__module.model.layers.0.input_layernorm/aten::pow/Power" type="Power" 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>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="392">
+					<dim>-1</dim>
+					<dim>-1</dim>
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+				</port>
+			</output>
+		</layer>
+		<layer id="33" name="Constant_388" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="311637156" size="8" />
+			<output>
+				<port id="0" precision="I64" names="393">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="34" name="__module.model.layers.0.input_layernorm/aten::mean/ReduceMean" type="ReduceMean" version="opset1">
+			<data keep_dims="true" />
+			<input>
+				<port id="0" precision="FP32">
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+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="394,variance.1">
+					<dim>-1</dim>
+					<dim>-1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="35" name="Constant_334311" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 1" offset="311637164" size="4" />
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+			</output>
+		</layer>
+		<layer id="36" name="__module.model.layers.0.input_layernorm/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
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+				<port id="2" precision="FP32" names="395">
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+			</output>
+		</layer>
+		<layer id="37" name="__module.model.layers.0.input_layernorm/aten::rsqrt/Sqrt" type="Sqrt" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
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+			</output>
+		</layer>
+		<layer id="38" name="__module.model.layers.0.input_layernorm/aten::rsqrt/Divide" type="Divide" version="opset1">
+			<data auto_broadcast="numpy" m_pythondiv="true" />
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+				<port id="0" precision="FP32">
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+		</layer>
+		<layer id="39" name="__module.model.layers.0.input_layernorm/aten::mul/Multiply" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
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+		<layer id="40" name="__module.model.layers.0.input_layernorm/aten::mul/Multiply_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
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+		<layer id="43" name="self.model.layers.0.self_attn.q_proj.weight/scale" type="Const" version="opset1">
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+			<framework value="pytorch" />
+			<is_python_object value="True" />
+		</conversion_parameters>
+		<nncf>
+			<friendly_names_were_updated value="True" />
+			<weight_compression>
+				<advanced_parameters value="{'awq_params': {'subset_size': 32, 'percent_to_apply': 0.002, 'alpha_min': 0.0, 'alpha_max': 1.0, 'steps': 100}, 'scale_estimation_params': {'subset_size': 64, 'initial_steps': 5, 'scale_steps': 5, 'weight_penalty': -1.0}, 'gptq_params': {'damp_percent': 0.1, 'block_size': 128, 'subset_size': 128}, 'lora_correction_params': {'adapter_rank': 8, 'num_iterations': 3, 'apply_regularization': True, 'subset_size': 128, 'use_int8_adapters': True}}" />
+				<all_layers value="False" />
+				<awq value="False" />
+				<gptq value="False" />
+				<group_size value="64" />
+				<ignored_scope value="[]" />
+				<lora_correction value="False" />
+				<mode value="int4_sym" />
+				<ratio value="0.6" />
+				<scale_estimation value="False" />
+				<sensitivity_metric value="weight_quantization_error" />
+			</weight_compression>
+		</nncf>
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+	</rt_info>
+</net>