mirror of
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44 lines
1.8 KiB
Python
44 lines
1.8 KiB
Python
"""
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# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
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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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"""
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from paddleformers.transformers import PretrainedModel
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from fastdeploy.model_executor.models.deepseek_v3 import DeepSeekV3PretrainedModel
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from fastdeploy.model_executor.models.ernie4_5_moe import Ernie4_5_PretrainedModel
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from fastdeploy.model_executor.models.ernie4_5_mtp import Ernie4_5_MTPPretrainedModel
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from fastdeploy.model_executor.models.ernie4_5_vl.ernie4_5_vl_moe import (
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Ernie4_5_VLPretrainedModel,
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)
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from fastdeploy.model_executor.models.qwen2 import Qwen2PretrainedModel
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from fastdeploy.model_executor.models.qwen3 import Qwen3PretrainedModel
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from fastdeploy.model_executor.models.qwen3moe import Qwen3MoePretrainedModel
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MODEL_CLASSES = {
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"Ernie4_5_MoeForCausalLM": Ernie4_5_PretrainedModel,
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"Ernie4_5_MTPForCausalLM": Ernie4_5_MTPPretrainedModel,
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"Qwen2ForCausalLM": Qwen2PretrainedModel,
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"Qwen3ForCausalLM": Qwen3PretrainedModel,
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"Qwen3MoeForCausalLM": Qwen3MoePretrainedModel,
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"Ernie4_5_ForCausalLM": Ernie4_5_PretrainedModel,
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"DeepseekV3ForCausalLM": DeepSeekV3PretrainedModel,
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"Ernie4_5_VLMoeForConditionalGeneration": Ernie4_5_VLPretrainedModel,
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}
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def get_pretrain_cls(architectures: str) -> PretrainedModel:
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"""get_pretrain_cls"""
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return MODEL_CLASSES[architectures]
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