Sync from v0.13

vllm/model_executor/models/glm.py

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+# 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 .utils import PPMissingLayer
+
+
+class GlmForCausalLM(LlamaForCausalLM):
+    def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):
+        hf_config = vllm_config.model_config.hf_config
+        hf_config.rope_parameters["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