59 lines
1.7 KiB
Python
59 lines
1.7 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""
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ColQwen3 configuration that extends Qwen3VLConfig with embedding projection
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fields. This allows ColQwen3 models to be loaded without trust_remote_code
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by mapping their custom model_type (colqwen3, ops_colqwen3, etc.) to a
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standard config class that vLLM understands.
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Supported model_types:
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- colqwen3 (TomoroAI/tomoro-colqwen3-embed-8b)
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- ops_colqwen3 (OpenSearch-AI/Ops-Colqwen3-4B)
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- qwen3_vl_nemotron_embed (nvidia/nemotron-colembed-vl-8b-v2)
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"""
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from transformers.models.qwen3_vl.configuration_qwen3_vl import Qwen3VLConfig
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class ColQwen3Config(Qwen3VLConfig):
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"""Configuration class for ColQwen3 models.
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Extends Qwen3VLConfig with additional fields used by ColQwen3 variants
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for the embedding projection layer.
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"""
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# Accept any ColQwen3 variant model_type
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model_type = "colqwen3"
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def __init__(
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self,
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embed_dim: int | None = None,
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dims: int | None = None,
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dim: int | None = None,
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projection_dim: int | None = None,
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colbert_dim: int | None = None,
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pooling: str | None = None,
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**kwargs,
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):
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# Store embedding projection config fields
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self.embed_dim = embed_dim
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self.dims = dims
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self.dim = dim
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self.projection_dim = projection_dim
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self.colbert_dim = colbert_dim
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self.pooling = pooling
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super().__init__(**kwargs)
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class OpsColQwen3Config(ColQwen3Config):
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"""Configuration for OpenSearch-AI ColQwen3 variants."""
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model_type = "ops_colqwen3"
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class Qwen3VLNemotronEmbedConfig(ColQwen3Config):
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"""Configuration for NVIDIA Nemotron ColEmbed variants."""
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model_type = "qwen3_vl_nemotron_embed"
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