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Model: sxiong/DeepControl-Qwen2.5-3B
Source: Original Platform

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README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: Qwen/Qwen2.5-3B-Instruct
+tags:
+  - qwen2.5
+  - deepcontrol
+  - search-augmented
+  - reinforcement-learning
+  - text-generation
+language:
+  - en
+pipeline_tag: text-generation
+---
+
+# DeepControl-Qwen2.5-3B
+
+Deep search agent checkpoint from Qwen2.5-3B-Instruct under *[Adaptive Information Control for Search-Augmented LLM Reasoning](https://arxiv.org/abs/2602.01672)* (EMNLP 2026).
+
+## Quick start
+
+See our repo [DeepControl](https://github.com/xiongsiheng/DeepControl) for more details.
+
+Recommended Configuration:
+
+| Setting | Value |
+|---|---:|
+| Inference dtype | BF16 |
+| Context length | 8,192 |
+| Generation temperature | 0 |
+| Maximum new tokens per action | 512 |
+| Maximum agent turns | 8 |
+| Retrieval top-k | 5 |
+| Retrieval corpus | Wikipedia 2018 (`wiki18`) |
+
+For example, the model server can be started with:
+
+```bash
+vllm serve sxiong/DeepControl-Qwen2.5-3B \
+  --dtype bfloat16 \
+  --max-model-len 8192
+```
+
+Loading the model alone does not provide retrieval. It requires the DeepControl system prompt, action parser, and `wiki18` corpus.
+
+## Citation
+
+```bibtex
+@article{xiong2026adaptive,
+  title={Adaptive Information Control for Search-Augmented LLM Reasoning},
+  author={Xiong, Siheng and Gungordu, Oguzhan and Kerce, James C and Fekri, Faramarz},
+  journal={arXiv preprint arXiv:2602.01672},
+  year={2026}
+}
+```

chat_template.jinja

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+{%- if messages[0]['role'] == 'system' %}{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}{%- set loop_messages = messages[1:] %}{%- else %}{{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}{%- set loop_messages = messages %}{%- endif %}{%- for message in loop_messages %}{%- if message['role'] == 'assistant' %}{{- '<|im_start|>assistant\n' }}{% generation %}{{ message['content'] + '<|im_end|>\n' }}{% endgeneration %}{%- else %}{{- '<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>\n' }}{%- endif %}{%- endfor %}{%- if add_generation_prompt %}{{- '<|im_start|>assistant\n' }}{%- endif %}

config.json

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+{
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0,
+  "bos_token_id": null,
+  "dtype": "bfloat16",
+  "eos_token_id": 151645,
+  "hidden_act": "silu",
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 11008,
+  "layer_types": [
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+    "full_attention",
+    "full_attention",
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+    "full_attention",
+    "full_attention",
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+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
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+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 32768,
+  "max_window_layers": 70,
+  "model_type": "qwen2",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 36,
+  "num_key_value_heads": 2,
+  "pad_token_id": 151643,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 1000000,
+    "rope_type": "default"
+  },
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "transformers_version": "5.12.1",
+  "use_cache": false,
+  "use_sliding_window": false,
+  "vocab_size": 151936,
+  "rope_theta": 1000000
+}

generation_config.json

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+  "pad_token_id": 151643,
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+  "temperature": 0.7,
+  "top_k": 20,
+  "top_p": 0.8,
+  "transformers_version": "5.12.1"
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