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Model: quangdung/Qwen2.5-7B-Math-Distill-Sens
Source: Original Platform

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
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+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+license: apache-2.0
+
+language:
+  - en
+
+base_model:
+  - deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
+  - Qwen/Qwen2.5-Math-7B
+
+tags:
+  - merge
+  - sens-merging
+  - math
+  - reasoning
+  - qwen2.5
+  - deepseek-r1
+
+pipeline_tag: text-generation
+---
+
+# Qwen2.5-Math-DeepSeekR1-Sens-7B
+
+A 7B merged model created by applying Sensitivity-aware Model Merging (Sens Merging) to:
+
+- deepseek-ai/DeepSeek-R1-Distill-Qwen-7B  
+- Qwen/Qwen2.5-Math-7B  
+
+The goal of this model is to preserve the strong mathematical reasoning ability of DeepSeek-R1-Distill while significantly reducing reasoning verbosity and output token length.
+
+---
+
+## Highlights
+
+- Average accuracy: 66.9%  
+- Average output tokens: 701  
+- Output tokens reduced by 75.2% compared to DeepSeek-R1-Distill-Qwen-7B  
+- Only 2.5 points lower average accuracy than DeepSeek-R1-Distill-Qwen-7B  
+
+This model provides an attractive trade-off between reasoning quality and inference cost.
+
+---
+
+## Base Models
+
+| Model                        | Avg Accuracy | Avg Tokens |
+|-----------------------------|-------------:|-----------:|
+| DeepSeek-R1-Distill-Qwen-7B | 69.4         | 2826       |
+| Qwen2.5-Math-7B             | 45.3         | 755        |
+| Sens Merge (λ=0.4)          | 66.9         | 701        |
+
+---
+
+## Benchmark Results
+
+| Benchmark      | Distill | Qwen2.5-Math | Sens Merge (λ=0.4) |
+|----------------|--------:|-------------:|--------------------:|
+| College Math   | 66.0    | 37.9         | 70.4               |
+| GSM8K          | 90.2    | 84.5         | 90.6               |
+| MATH           | 94.4    | 73.3         | 90.2               |
+| Minerva Math   | 41.5    | 13.6         | 36.0               |
+| OlympiadBench  | 55.0    | 17.3         | 47.2               |
+| Avg Accuracy   | 69.4    | 45.3         | 66.9               |
+| Avg Tokens     | 2826    | 755          | 701                |
+
+---
+
+## Motivation
+
+Large reasoning models such as DeepSeek-R1-Distill often produce long chains of thought, which increases inference cost.
+
+This model explores whether model merging can reduce reasoning verbosity without requiring additional training.
+
+By merging a reasoning model (DeepSeek-R1-Distill-Qwen-7B) with a compact mathematical model (Qwen2.5-Math-7B) using Sensitivity-aware Model Merging, the merged model:
+
+- Maintains competitive reasoning performance  
+- Produces significantly shorter outputs  
+- Requires no gradient-based fine-tuning  
+- Uses only a small calibration dataset  
+
+---
+
+## Comparison with DPO
+
+We additionally compared Sens Merging with a DPO-trained model:
+
+| Model                        | Avg Accuracy | Avg Tokens |
+|-----------------------------|-------------:|-----------:|
+| DeepSeek-R1-Distill-Qwen-7B | 69.4         | 2826       |
+| DPO                         | 68.55        | 2402       |
+| Sens Merge (λ=0.4)          | 66.9         | 701        |
+
+Sens Merging achieves a much larger reduction in output length while remaining competitive in accuracy.
+
+---
+
+## Usage
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model_name = "quangdung/Qwen2.5-Math-DeepSeekR1-Sens-7B"
+
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype="auto",
+    device_map="auto"
+)
+
+prompt = "Solve: If x^2 + 5x + 6 = 0, find x."
+
+messages = [{"role": "user", "content": prompt}]
+
+text = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True
+)
+
+inputs = tokenizer(text, return_tensors="pt").to(model.device)
+
+outputs = model.generate(
+    **inputs,
+    max_new_tokens=512
+)
+
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))

chat_template.jinja

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+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- messages[0]['content'] }}
+    {%- else %}
+        {{- 'Please reason step by step, and put your final answer within \\boxed{}.' }}
+    {%- endif %}
+    {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
+{%- else %}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
+    {%- else %}
+        {{- '<|im_start|>system\nPlease reason step by step, and put your final answer within \\boxed{}.<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role }}
+        {%- if message.content %}
+            {{- '\n' + message.content }}
+        {%- endif %}
+        {%- for tool_call in message.tool_calls %}
+            {%- if tool_call.function is defined %}
+                {%- set tool_call = tool_call.function %}
+            {%- endif %}
+            {{- '\n<tool_call>\n{"name": "' }}
+            {{- tool_call.name }}
+            {{- '", "arguments": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- '}\n</tool_call>' }}
+        {%- endfor %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- message.content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+{%- endif %}

config.json

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+{
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "dtype": "bfloat16",
+  "eos_token_id": 151643,
+  "hidden_act": "silu",
+  "hidden_size": 3584,
+  "initializer_range": 0.02,
+  "intermediate_size": 18944,
+  "layer_types": [
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 4096,
+  "max_window_layers": 28,
+  "model_type": "qwen2",
+  "num_attention_heads": 28,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 4,
+  "pad_token_id": null,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 10000,
+    "rope_type": "default"
+  },
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "transformers_version": "5.5.4",
+  "use_cache": true,
+  "use_mrope": false,
+  "use_sliding_window": false,
+  "vocab_size": 152064
+}

generation_config.json

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+{
+  "bos_token_id": 151643,
+  "do_sample": false,
+  "eos_token_id": 151643,
+  "max_new_tokens": 2048,
+  "transformers_version": "5.5.4"
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:e9c8685245e89d40805ff6eda9ba04fb0269d153d529961d712e41b4bad86ffa
+size 15231272152

tokenizer.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:3fd169731d2cbde95e10bf356d66d5997fd885dd8dbb6fb4684da3f23b2585d8
+size 11421892

tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|endoftext|>",
+  "errors": "replace",
+  "extra_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "is_local": true,
+  "model_max_length": 131072,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}