delete glmGlmForCausalLM register (#132)
Co-authored-by: hanhaowen <hanhaowen@baidu.com>
This commit is contained in:
@@ -36,10 +36,6 @@ def register_model():
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ModelRegistry.register_model(
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"Qwen3NextForCausalLM",
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"vllm_kunlun.models.qwen3_next:Qwen3NextForCausalLM")
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ModelRegistry.register_model(
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"GlmForCausalLM",
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"vllm_kunlun.models.glm:GlmForCausalLM")
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ModelRegistry.register_model(
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"GptOssForCausalLM",
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@@ -1,24 +0,0 @@
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# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""Inference-only HF format GLM-4 model compatible with THUDM weights."""
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from vllm.config import VllmConfig
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# from vllm.model_executor.models.llama import LlamaForCausalLM
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from .llama import LlamaForCausalLM #noqa: F401
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from vllm.model_executor.models.utils import PPMissingLayer
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class GlmForCausalLM(LlamaForCausalLM):
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def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):
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print("glm for causalLM initialization!!!!", flush=True)
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vllm_config.model_config.hf_config.partial_rotary_factor = 0.5
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super().__init__(vllm_config=vllm_config, prefix=prefix)
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# Hack Llama model to fit HF format GLM implementation
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# Attention difference between GLM and Llama:
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# 1. Half partial rotary_dim and no Neox style.
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# 2. There is no bias for o_proj in attention
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for layer in self.model.layers:
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if not isinstance(layer, PPMissingLayer):
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layer.self_attn.rotary_emb.is_neox_style = False
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layer.self_attn.o_proj.bias = None
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layer.self_attn.o_proj.skip_bias_add = True
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