| <?xml version="1.0"?>
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| <conversion_parameters>
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| <framework value="pytorch" />
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| <is_python_object value="True" />
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| </conversion_parameters>
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| <nncf>
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| <friendly_names_were_updated value="True" />
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| <version value="2.19.0" />
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| <weight_compression>
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| <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}" />
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| <all_layers value="False" />
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| <group_size value="-1" />
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| <ignored_scope value="[]" />
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| <lora_correction value="False" />
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| <mode value="int8_sym" />
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| <ratio value="1.0" />
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| <scale_estimation value="False" />
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| <sensitivity_metric value="weight_quantization_error" />
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| </weight_compression>
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| </nncf>
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| <optimum>
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| <nncf_version value="2.19.0" />
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| <optimum_intel_version value="1.27.0" />
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| <optimum_version value="2.1.0" />
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| <pytorch_version value="2.9.1" />
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| <transformers_version value="4.55.0" />
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| </optimum>
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| </rt_info>
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| </net>
|
|
|
