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jinyouzhiCSWYF3634076vasquDarkLight1337
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Porting ERNIE 4.5 and ERNIE 4.5 MoE model support (#1779)
Enable ERNIE 4.5 series text generation models including Dense and MoE. This PR contains: - cherry-pick vllm-project#20220 - bugfix vllm-project#21735 (name mistake) then validate on - [ERNIE-4.5-0.3B-PT](https://huggingface.co/baidu/ERNIE-4.5-0.3B-PT) - [ERNIE-4.5-21B-A3B-PT](https://huggingface.co/baidu/ERNIE-4.5-21B-A3B-PT) @Wei-Lin-Intel --------- Signed-off-by: wangyafeng <[email protected]> Signed-off-by: vasqu <[email protected]> Signed-off-by: DarkLight1337 <[email protected]> Co-authored-by: CSWYF3634076 <[email protected]> Co-authored-by: Anton Vlasjuk <[email protected]> Co-authored-by: DarkLight1337 <[email protected]>
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‎docs/models/supported_models.md

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| `DeepseekForCausalLM` | DeepSeek | `deepseek-ai/deepseek-llm-67b-base`, `deepseek-ai/deepseek-llm-7b-chat` etc. | | ✅︎ |
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| `DeepseekV2ForCausalLM` | DeepSeek-V2 | `deepseek-ai/DeepSeek-V2`, `deepseek-ai/DeepSeek-V2-Chat` etc. | | ✅︎ |
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| `DeepseekV3ForCausalLM` | DeepSeek-V3 | `deepseek-ai/DeepSeek-V3-Base`, `deepseek-ai/DeepSeek-V3` etc. | | ✅︎ |
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| `Ernie4_5ForCausalLM` | Ernie4.5 | `baidu/ERNIE-4.5-0.3B-PT`,etc. | | ✅︎ | ✅︎ |
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| `Ernie4_5_MoeForCausalLM` | Ernie4.5MoE | `baidu/ERNIE-4.5-21B-A3B-PT`, `baidu/ERNIE-4.5-300B-A47B-PT`, etc. | | ✅︎ | ✅︎ |
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| `ExaoneForCausalLM` | EXAONE-3 | `LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct`, etc. | ✅︎ | ✅︎ |
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| `FalconForCausalLM` | Falcon | `tiiuae/falcon-7b`, `tiiuae/falcon-40b`, `tiiuae/falcon-rw-7b`, etc. | | ✅︎ |
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| `FalconMambaForCausalLM` | FalconMamba | `tiiuae/falcon-mamba-7b`, `tiiuae/falcon-mamba-7b-instruct`, etc. | | ✅︎ |
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| `XverseForCausalLM` | XVERSE | `xverse/XVERSE-7B-Chat`, `xverse/XVERSE-13B-Chat`, `xverse/XVERSE-65B-Chat`, etc. | ✅︎ | ✅︎ |
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| `MiniMaxText01ForCausalLM` | MiniMax-Text | `MiniMaxAI/MiniMax-Text-01`, etc. | | |
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| `Zamba2ForCausalLM` | Zamba2 | `Zyphra/Zamba2-7B-instruct`, `Zyphra/Zamba2-2.7B-instruct`, `Zyphra/Zamba2-1.2B-instruct`, etc. | | |
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!!! note
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Currently, the ROCm version of vLLM supports Mistral and Mixtral only for context lengths up to 4096.
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| `SmolVLMForConditionalGeneration` | SmolVLM2 | T + I | `SmolVLM2-2.2B-Instruct` | ✅︎ | | ✅︎ |
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| `TarsierForConditionalGeneration` | Tarsier | T + I<sup>E+</sup> | `omni-search/Tarsier-7b`,`omni-search/Tarsier-34b` | | ✅︎ | ✅︎ |
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<sup>^</sup> You need to set the architecture name via `--hf-overrides` to match the one in vLLM.
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&nbsp;&nbsp;&nbsp;&nbsp;• For example, to use DeepSeek-VL2 series models:
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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;`--hf-overrides '{"architectures": ["DeepseekVLV2ForCausalLM"]}'`
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<sup>E</sup> Pre-computed embeddings can be inputted for this modality.
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<sup>^</sup> You need to set the architecture name via `--hf-overrides` to match the one in vLLM.
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&nbsp;&nbsp;&nbsp;&nbsp;• For example, to use DeepSeek-VL2 series models:
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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;`--hf-overrides '{"architectures": ["DeepseekVLV2ForCausalLM"]}'`
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<sup>E</sup> Pre-computed embeddings can be inputted for this modality.
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<sup>+</sup> Multiple items can be inputted per text prompt for this modality.
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!!! warning

‎tests/models/registry.py

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trust_remote_code=True),
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"DeepseekV3ForCausalLM": _HfExamplesInfo("deepseek-ai/DeepSeek-V3", # noqa: E501
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trust_remote_code=True),
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"Ernie4_5ForCausalLM": _HfExamplesInfo("baidu/ERNIE-4.5-0.3B-PT",
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min_transformers_version="4.54"),
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"Ernie4_5_MoeForCausalLM": _HfExamplesInfo("baidu/ERNIE-4.5-21B-A3B-PT",
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trust_remote_code=True),
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"ExaoneForCausalLM": _HfExamplesInfo("LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct"), # noqa: E501
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"Fairseq2LlamaForCausalLM": _HfExamplesInfo("mgleize/fairseq2-dummy-Llama-3.2-1B"), # noqa: E501
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"FalconForCausalLM": _HfExamplesInfo("tiiuae/falcon-7b"),

‎vllm/model_executor/models/ernie45.py

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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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# Copyright 2025 The Baidu team.
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# Copyright 2023 The vLLM team.
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# Copyright 2022 EleutherAI and the HuggingFace Inc. team. All rights reserved.
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#
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# This code is based on EleutherAI's GPT-NeoX library and the GPT-NeoX
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# and OPT implementations in this library. It has been modified from its
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# original forms to accommodate minor architectural differences compared
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# to GPT-NeoX and OPT used by the Meta AI team that trained the model.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Inference-only Erine model compatible with HuggingFace 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 .utils import PPMissingLayer
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class Ernie4_5ForCausalLM(LlamaForCausalLM):
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def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):
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super().__init__(vllm_config=vllm_config, prefix=prefix)
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# Hack Llama model to fit HF format Ernie4.5 dense implementation
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# Attention difference between Ernie and Llama:
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# 1. 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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