pibog_models / alexa_v0.1.xml
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<?xml version="1.0"?>
<net name="torch_jit" version="11">
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<edge from-layer="46" from-port="0" to-layer="48" to-port="0" />
<edge from-layer="47" from-port="0" to-layer="48" to-port="1" />
<edge from-layer="48" from-port="2" to-layer="49" to-port="1" />
<edge from-layer="49" from-port="2" to-layer="50" to-port="0" />
<edge from-layer="50" from-port="1" to-layer="51" to-port="0" />
</edges>
<rt_info>
<nncf>
<friendly_names_were_updated value="True" />
<version value="2.18.0" />
<weight_compression>
<advanced_parameters value="{'statistics_path': None, 'lora_adapter_rank': 256, 'group_size_fallback_mode': 'ignore', 'min_adjusted_group_size': 16, '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}" />
<all_layers value="False" />
<awq value="False" />
<backup_mode value="int8_asym" />
<compression_format value="dequantize" />
<gptq value="False" />
<group_size value="-1" />
<ignored_scope value="[]" />
<lora_correction value="False" />
<mode value="int8_asym" />
<ratio value="1" />
<scale_estimation value="False" />
<sensitivity_metric value="weight_quantization_error" />
</weight_compression>
</nncf>
</rt_info>
</net>