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@@ -12,7 +12,7 @@ This model is trained through the approach described in [DMRetriever: A Family o
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  The associated GitHub repository is available [here](https://github.com/KaiYin97/DMRETRIEVER).
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  This model has 596M parameters.
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- ## Model Overview
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  **DMRetriever-596M** has the following features:
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@@ -24,7 +24,7 @@ This model has 596M parameters.
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  For more details, including model training, benchmark evaluation, and inference performance, please refer to our [paper](https://www.arxiv.org/abs/2510.15087), [GitHub](https://github.com/KaiYin97/DMRETRIEVER).
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- ## DMRetriever series model list
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  | **Model** | **Description** | **Backbone** | **Backbone Type** | **Hidden Size** | **#Layers** |
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  |:--|:--|:--|:--|:--:|:--:|
@@ -42,7 +42,7 @@ For more details, including model training, benchmark evaluation, and inference
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  | [DMRetriever-7.6B-PT](https://huggingface.co/DMIR01/DMRetriever-7.6B-PT) | Pre-trained version of 7.6B | Qwen3-8B | Decoder-only | 4096 | 36 |
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- ## Usage
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  Using HuggingFace Transformers:
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@@ -55,7 +55,7 @@ from bidirectional_qwen3 import Qwen3BiModel # custom bidirectional backbone
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  MODEL_ID = "DMIR01/DMRetriever-596M"
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- # Device & dtype (GPU -> fp16; CPU -> fp32)
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  device = "cuda" if torch.cuda.is_available() else "cpu"
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  dtype = torch.float16 if device == "cuda" else torch.float32
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@@ -154,13 +154,16 @@ for i, q in enumerate(queries_raw):
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  ```
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- ## Notice
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- (1) The backbone is bidirectional Qwen3 instead of Qwen3, so please ensure bidirectional_qwen3 (we provided it in the released model checkpoint folder) is in the model folder.
 
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- (2) Ensure the transformers>4.51.0 to avoid KeyError: 'qwen3'.
 
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- ## Citation
 
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  If you find this repository helpful, please kindly consider citing the corresponding paper. Thanks!
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  ```
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  @article{yin2025dmretriever,
 
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  The associated GitHub repository is available [here](https://github.com/KaiYin97/DMRETRIEVER).
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  This model has 596M parameters.
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+ ## 🧠 Model Overview
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  **DMRetriever-596M** has the following features:
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  For more details, including model training, benchmark evaluation, and inference performance, please refer to our [paper](https://www.arxiv.org/abs/2510.15087), [GitHub](https://github.com/KaiYin97/DMRETRIEVER).
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+ ## 📦 DMRetriever Series Model List
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  | **Model** | **Description** | **Backbone** | **Backbone Type** | **Hidden Size** | **#Layers** |
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  |:--|:--|:--|:--|:--:|:--:|
 
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  | [DMRetriever-7.6B-PT](https://huggingface.co/DMIR01/DMRetriever-7.6B-PT) | Pre-trained version of 7.6B | Qwen3-8B | Decoder-only | 4096 | 36 |
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+ ## 🚀 Usage
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  Using HuggingFace Transformers:
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  MODEL_ID = "DMIR01/DMRetriever-596M"
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+ # Device & dtype
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  device = "cuda" if torch.cuda.is_available() else "cpu"
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  dtype = torch.float16 if device == "cuda" else torch.float32
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  ```
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+ ## ⚠️ Notice
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+ 1. The **backbone** used in DMRetriever is **Bidirectional Qwen3**, not the standard Qwen3.
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+ Please ensure that the `bidirectional_qwen3` module (included in the released model checkpoint folder) is correctly placed inside your model directory.
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+ 2. Make sure that your **transformers** library version is **≥ 4.51.0** to avoid the error:
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+ `KeyError: 'qwen3'`.
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+
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+ ## 🧾 Citation
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  If you find this repository helpful, please kindly consider citing the corresponding paper. Thanks!
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  ```
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  @article{yin2025dmretriever,