delete glmGlmForCausalLM register (#132)

Co-authored-by: hanhaowen <hanhaowen@baidu.com>

vllm_kunlun/models/__init__.py

@@ -37,10 +37,6 @@ def register_model():
         "Qwen3NextForCausalLM",
         "vllm_kunlun.models.qwen3_next:Qwen3NextForCausalLM")
 
-    ModelRegistry.register_model(
-        "GlmForCausalLM",
-        "vllm_kunlun.models.glm:GlmForCausalLM")  
-
     ModelRegistry.register_model(
         "GptOssForCausalLM",
         "vllm_kunlun.models.gpt_oss:GptOssForCausalLM")  

vllm_kunlun/models/glm.py

@@ -1,24 +0,0 @@
-# SPDX-License-Identifier: Apache-2.0
-# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
-"""Inference-only HF format GLM-4 model compatible with THUDM weights."""
-from vllm.config import VllmConfig
-# from vllm.model_executor.models.llama import LlamaForCausalLM
-from .llama import LlamaForCausalLM #noqa: F401
-
-from vllm.model_executor.models.utils import PPMissingLayer
-
-class GlmForCausalLM(LlamaForCausalLM):
-
-    def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):
-        print("glm for causalLM initialization!!!!", flush=True)
-        vllm_config.model_config.hf_config.partial_rotary_factor = 0.5
-        super().__init__(vllm_config=vllm_config, prefix=prefix)
-        # Hack Llama model to fit HF format GLM implementation
-        # Attention difference between GLM and Llama:
-        # 1. Half partial rotary_dim and no Neox style.
-        # 2. There is no bias for o_proj in attention
-        for layer in self.model.layers:
-            if not isinstance(layer, PPMissingLayer):
-                layer.self_attn.rotary_emb.is_neox_style = False
-                layer.self_attn.o_proj.bias = None
-                layer.self_attn.o_proj.skip_bias_add = True