diff --git "a/vae_decoder/vae_decoder_t1.xml" "b/vae_decoder/vae_decoder_t1.xml"
new file mode 100644--- /dev/null
+++ "b/vae_decoder/vae_decoder_t1.xml"
@@ -0,0 +1,15691 @@
+<?xml version="1.0"?>
+<net name="Model1004" version="11">
+	<layers>
+		<layer id="0" name="z" type="Parameter" version="opset1">
+			<data shape="?,?,?,?,?" element_type="f32" />
+			<output>
+				<port id="0" precision="FP32" names="45,input.1,z">
+					<dim>-1</dim>
+					<dim>-1</dim>
+					<dim>-1</dim>
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1" name="self.vae.post_quant_conv.weight" type="Const" version="opset1">
+			<data element_type="u8" shape="16, 16, 1, 1, 1" offset="0" size="256" />
+			<output>
+				<port id="0" precision="U8">
+					<dim>16</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="2" name="Convert_3037428" type="Convert" version="opset1">
+			<data destination_type="f16" />
+			<input>
+				<port id="0" precision="U8">
+					<dim>16</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP16">
+					<dim>16</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="3" name="self.vae.post_quant_conv.weight/zero_point" type="Const" version="opset1">
+			<data element_type="u8" shape="16, 1, 1, 1, 1" offset="256" size="16" />
+			<output>
+				<port id="0" precision="U8">
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="4" name="Convert_3037431" type="Convert" version="opset1">
+			<data destination_type="f16" />
+			<input>
+				<port id="0" precision="U8">
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP16">
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="5" name="self.vae.post_quant_conv.weight/zero_point/subtract" type="Subtract" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP16">
+					<dim>16</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+				<port id="1" precision="FP16">
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP16">
+					<dim>16</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="6" name="self.vae.post_quant_conv.weight/scale" type="Const" version="opset1">
+			<data element_type="f16" shape="16, 1, 1, 1, 1" offset="272" size="32" />
+			<output>
+				<port id="0" precision="FP16">
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="7" name="self.vae.post_quant_conv.weight/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP16">
+					<dim>16</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+				<port id="1" precision="FP16">
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP16">
+					<dim>16</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="8" name="self.vae.post_quant_conv.weight/fq_weights_1/convert" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="FP16">
+					<dim>16</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>16</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="9" name="__module.vae.post_quant_conv/aten::_convolution/Convolution" type="Convolution" version="opset1">
+			<data strides="1, 1, 1" dilations="1, 1, 1" pads_begin="0, 0, 0" pads_end="0, 0, 0" auto_pad="explicit" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>-1</dim>
+					<dim>-1</dim>
+					<dim>-1</dim>
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>16</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>-1</dim>
+					<dim>16</dim>
+					<dim>-1</dim>
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="10" name="__module.vae.post_quant_conv/aten::_convolution/Reshape" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 16, 1, 1, 1" offset="304" size="64" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="11" name="__module.vae.post_quant_conv/aten::_convolution/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>-1</dim>
+					<dim>16</dim>
+					<dim>-1</dim>
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="11,16,50,x.1">
+					<dim>-1</dim>
+					<dim>16</dim>
+					<dim>-1</dim>
+					<dim>-1</dim>
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="12" name="Constant_2827971" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="368" size="8" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="13" name="Constant_2827973" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="376" size="8" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="14" name="Constant_2827975" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="376" size="8" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="15" name="Constant_2827969" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="384" size="8" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="16" name="aten::slice/Slice_2" type="Slice" version="opset8">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>-1</dim>
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+				<port id="1" precision="I64">
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+				<port id="2" precision="I64">
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+				<port id="3" precision="I64">
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+				</port>
+				<port id="4" precision="I64">
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+				</port>
+			</input>
+			<output>
+				<port id="5" precision="FP32" names="21,26,31,x.3">
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+				</port>
+			</output>
+		</layer>
+		<layer id="17" name="self.vae.decoder.conv_in.weight" type="Const" version="opset1">
+			<data element_type="u8" shape="384, 16, 3, 3, 3" offset="392" size="165888" />
+			<output>
+				<port id="0" precision="U8">
+					<dim>384</dim>
+					<dim>16</dim>
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+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="18" name="Convert_3021488" type="Convert" version="opset1">
+			<data destination_type="f16" />
+			<input>
+				<port id="0" precision="U8">
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+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP16">
+					<dim>384</dim>
+					<dim>16</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="19" name="self.vae.decoder.conv_in.weight/zero_point" type="Const" version="opset1">
+			<data element_type="u8" shape="384, 1, 1, 1, 1" offset="166280" size="384" />
+			<output>
+				<port id="0" precision="U8">
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+					<dim>1</dim>
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+				</port>
+			</output>
+		</layer>
+		<layer id="20" name="Convert_3021491" type="Convert" version="opset1">
+			<data destination_type="f16" />
+			<input>
+				<port id="0" precision="U8">
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+			<output>
+				<port id="1" precision="FP16">
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+				</port>
+			</output>
+		</layer>
+		<layer id="21" name="self.vae.decoder.conv_in.weight/zero_point/subtract" type="Subtract" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP16">
+					<dim>384</dim>
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+				</port>
+				<port id="1" precision="FP16">
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+					<dim>1</dim>
+					<dim>1</dim>
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+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP16">
+					<dim>384</dim>
+					<dim>16</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="22" name="self.vae.decoder.conv_in.weight/scale" type="Const" version="opset1">
+			<data element_type="f16" shape="384, 1, 1, 1, 1" offset="166664" size="768" />
+			<output>
+				<port id="0" precision="FP16">
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+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="23" name="self.vae.decoder.conv_in.weight/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP16">
+					<dim>384</dim>
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+				<port id="1" precision="FP16">
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+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP16">
+					<dim>384</dim>
+					<dim>16</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="24" name="self.vae.decoder.conv_in.weight/fq_weights_1/convert" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="FP16">
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+			<output>
+				<port id="1" precision="FP32">
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+					<dim>3</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="25" name="__module.vae.decoder.conv_in/aten::_convolution/Convolution" type="Convolution" version="opset1">
+			<data strides="1, 1, 1" dilations="1, 1, 1" pads_begin="2, 1, 1" pads_end="0, 1, 1" auto_pad="explicit" />
+			<input>
+				<port id="0" precision="FP32">
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+				<port id="1" precision="FP32">
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+					<dim>3</dim>
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+			<output>
+				<port id="2" precision="FP32">
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+			</output>
+		</layer>
+		<layer id="26" name="__module.vae.decoder.conv_in/aten::_convolution/Reshape" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 384, 1, 1, 1" offset="167432" size="1536" />
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+			</output>
+		</layer>
+		<layer id="27" name="__module.vae.decoder.conv_in/aten::_convolution/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
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+			<output>
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+			</output>
+		</layer>
+		<layer id="28" name="Concat_2828166" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="376" size="8" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="29" name="__module.vae.decoder.mid_block.resnets.0.norm1/aten::linalg_vector_norm/ReduceL2" type="ReduceL2" version="opset4">
+			<data keep_dims="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>-1</dim>
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+				<port id="1" precision="I64">
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+			<output>
+				<port id="2" precision="FP32" names="107">
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+		</layer>
+		<layer id="30" name="Constant_2850025" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 1, 1, 1" offset="168968" size="4" />
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+			</output>
+		</layer>
+		<layer id="31" name="__module.vae.decoder.mid_block.resnets.0.norm1/aten::clamp_min/Maximum" type="Maximum" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
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+			</output>
+		</layer>
+		<layer id="32" name="__module.vae.decoder.mid_block.resnets.0.norm1/aten::div/Divide" type="Divide" version="opset1">
+			<data auto_broadcast="numpy" m_pythondiv="true" />
+			<input>
+				<port id="0" precision="FP32">
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+		<info name="OpenVINO Runtime" value="2026.3.0-22451-8a17657b995-releases/2026/3" />
+		<Runtime_version value="2026.3.0-22451-8a17657b995-releases/2026/3" />
+		<conversion_parameters>
+			<framework value="pytorch" />
+			<is_python_object value="True" />
+		</conversion_parameters>
+		<nncf>
+			<friendly_names_were_updated value="True" />
+			<version value="3.3.0" />
+			<weight_compression>
+				<advanced_parameters value="{'statistics_path': None, 'lora_adapter_rank': 256, 'group_size_fallback_mode': 'error', 'min_adjusted_group_size': 32, 'awq_params': {'subset_size': 32, 'percent_to_apply': 0.002, 'alpha_min': 0.0, 'alpha_max': 1.0, 'steps': 100, 'prefer_data_aware_scaling': True}, '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}, 'backend_params': {}, 'codebook': None, 'adaptive_codebook_params': {'value_type': 'f8e4m3', 'across_blocks': False, 'num_elements': 16}}" />
+				<all_layers value="False" />
+				<awq value="False" />
+				<backup_mode value="int8_asym" />
+				<compression_format value="dequantize" />
+				<gptq value="False" />
+				<group_size value="64" />
+				<ignored_scope value="[]" />
+				<lora_correction value="False" />
+				<mode value="int4_asym" />
+				<ratio value="1.0" />
+				<scale_estimation value="False" />
+				<sensitivity_metric value="weight_quantization_error" />
+			</weight_compression>
+		</nncf>
+	</rt_info>
+</net>