[Bugfix] Remove ModelSlim-"M4 Quantization". (#4589)

The M4 quantization method in ModelSlim adds bias to model weights that
originally do not have a linear bias. PR #4235 supported PD-MIX
quantization and M4 quantization, adding bias to `w8a8.py` and
`w8a8_dynamic.py`, and implementing adaptations in `ops/linear.py` to
prevent it from being reset to `None` by
`self.register_parameter("bias", None)`. However, this modification
introduced an issue where the bias was still being reset to `None` in
certain scenarios, causing errors during service startup. Therefore,
support for M4 quantization is temporarily being reverted in this PR.
___
- vLLM version: v0.11.2

Signed-off-by: SlightwindSec <slightwindsec@gmail.com>

vllm_ascend/quantization/w8a8_dynamic.py

@@ -60,7 +60,6 @@ class AscendW8A8DynamicLinearMethod:
         params_dict["weight_offset"] = torch.empty(output_size,
                                                    1,
                                                    dtype=params_dtype)
-        params_dict["bias"] = torch.zeros(output_size, dtype=torch.float32)
         return params_dict
 
     def get_pergroup_param(self,
@@ -98,7 +97,6 @@ class AscendW8A8DynamicLinearMethod:
         layer.weight_scale.data = layer.weight_scale.data.flatten()
         layer.weight_scale_fp32 = layer.weight_scale.data.to(torch.float32)
         layer.weight_offset.data = layer.weight_offset.data.flatten()
-        layer.bias.data = layer.bias.data.to(layer.weight_scale.data.dtype)
 
 
 class AscendW8A8DynamicFusedMoEMethod: