fix: Always initialize bias to zero for ColumnParallelLinear.

[gesanqiu]

This PR should fix the problem of #1411.

In #1181, @zhuohan123 refactor the codes of ColumnParallelLinear, and removed the self.bias.zero_() statement, which result in some unknow behaviors in the model init phase. vLLM will do a forward inprofile_num_available_blocks, and hidden_state will include nan value when executing the second DecodeLayer forwarding.
To be more precise, some wired phenomenon happened to the self.bias of ColumnParallelLinear:

1. self.bias will include some large value from the second attention layer if we just init the whole model;
   
   These larger value will result in some nan value in the attn_output.

2. If I add a breakpoint at this statement:

        self.qkv_proj = ColumnParallelLinear(
            hidden_size,
            3 * self.total_num_heads * self.head_dim,
            bias=True,
            gather_output=False,
        )

step into its construct function, run the __init__() step by step, self.bias seems to be a zero tensor, but still bring in some accuracy error when forwarding, qkv, _ = self.qkv_proj(hidden_states) is different to the result in vLLM==0.2.0.

I'm no a expert of Pytorch, and can't explain why these wired phenomenon happened. But this PR could fix the bug.