default_stage:
  default_modifiers:
    AWQModifier:
      config_groups:
        group_0:
          targets: [Linear]
          weights:
            num_bits: 4
            type: int
            symmetric: true
            group_size: 32
            strategy: group
            block_structure: null
            dynamic: false
            actorder: null
            scale_dtype: null
            zp_dtype: null
            observer: mse
            observer_kwargs: {}
          input_activations: null
          output_activations: null
          format: null
      targets: [Linear]
      ignore: ['re:.*embed_tokens', 're:.*linear_attn.*', 're:.*shared_expert.*', 're:.*shared_expert_gate$',
        're:.*mlp[.]gate$', 're:.*self_attn.*', 're:model[.]visual.*', 're:mtp.*', lm_head]
      bypass_divisibility_checks: false
      mappings:
      - smooth_layer: re:model.*post_attention_layernorm$
        balance_layers: ['re:model.*mlp[.]experts.*gate_proj$', 're:model.*mlp[.]experts.*up_proj$',
          're:model.*mlp[.]shared_expert[.]gate_proj$', 're:model.*mlp[.]shared_expert[.]up_proj$',
          're:model.*mlp[.]gate$', 're:model.*mlp[.]shared_expert_gate$']
        activation_hook_target: null
        balance_exponent: 1
      - smooth_layer: re:model.*mlp[.]experts.*up_proj$
        balance_layers: ['re:model.*mlp[.]experts.*down_proj$']
        activation_hook_target: null
        balance_exponent: 1
      offload_device: !!python/object/apply:torch.device [cpu]
      duo_scaling: true
      n_grid: 20