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Model: yifan02/qwen3-0.6b-tool-distill
Source: Original Platform

.gitattributes

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README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen3-0.6B
+language:
+- zh
+tags:
+- tool-calling
+- function-calling
+- knowledge-distillation
+- qwen3
+- edge
+pipeline_tag: text-generation
+---
+
+# Qwen3-0.6B · 端侧工具调用蒸馏版
+
+把 **Qwen3-8B** 教师模型的**工具调用（tool/function calling）+ 思维链**能力，通过**序列级知识蒸馏 + 全量 SFT** 蒸馏进 **Qwen3-0.6B** 学生模型，面向 **CPU / 端侧本地部署**。场景为端侧智能音频设备控制（7 个自定义工具）。
+
+📦 完整代码 / 数据 / 评测 / 复现：**https://github.com/dengdengf/qwen3-tool-distill**
+
+## 结果（自建执行式评测集，227 条，防污染）
+
+| 指标 | 训练前 base(0.6B) | **本模型(蒸馏后)** | 教师(8B) |
+|---|---|---|---|
+| 工具调用精确匹配（名+参） | 59.0% | **94.3%** | 97.8% |
+| 工具选择准确率 | 79.4% | **94.9%** | 98.3% |
+| 参数 schema 合规率 | 96.6% | **99.4%** | 100% |
+| 越界请求·正确拒调用 | 98.1% | **100%** | 100% |
+
+- 训练带来 **+35.2pt**（59.0→94.3），达教师 **96.4%** 水平；相较教师**体积压缩 13.7×**（16.4GB→1.19GB）。
+
+## 用法
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "yifan02/qwen3-0.6b-tool-distill"
+tok = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id, dtype="bfloat16").cuda()
+
+tools = [{"type": "function", "function": {
+    "name": "set_volume",
+    "description": "设置指定音频设备的音量大小(0-100)。",
+    "parameters": {"type": "object", "properties": {
+        "device": {"type": "string", "enum": ["living_room","bedroom","kitchen","study","all"]},
+        "level":  {"type": "integer", "minimum": 0, "maximum": 100}},
+        "required": ["device","level"]}}}]  # 完整 7 个工具见 GitHub 仓库
+
+msgs = [{"role":"system","content":"你是一个智能音频助手，负责控制家里的音频设备。"},
+        {"role":"user","content":"把客厅音量调到40"}]
+text = tok.apply_chat_template(msgs, tools=tools, add_generation_prompt=True, tokenize=False)
+out = model.generate(**tok(text, return_tensors="pt").to("cuda"), max_new_tokens=512)
+print(tok.decode(out[0], skip_special_tokens=True))
+# -> <think>...</think> <tool_call>{"name":"set_volume","arguments":{"device":"living_room","level":40}}</tool_call>
+```
+
+## 训练细节
+
+序列级知识蒸馏（教师生成「思维链+工具调用」轨迹，拒绝采样保留 95.7%）+ 全量 SFT；bf16、有效 batch 32、lr 1e-5、3 epoch、max_len 2048、按 eval_loss 选最优 checkpoint。单张 RTX 4090。
+
+## 局限
+
+评测数据为程序化合成、分布规整；测试集 n=227；多工具（一句两调用）仍落后教师 ~17pt（0.6B 容量上限）。详见 GitHub 仓库。

chat_template.jinja

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+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0].role == 'system' %}
+        {{- messages[0].content + '\n\n' }}
+    {%- endif %}
+    {{- "# 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' }}
+    {%- endif %}
+{%- endif %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for message in messages[::-1] %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
+        {%- set ns.multi_step_tool = false %}
+        {%- set ns.last_query_index = index %}
+    {%- endif %}
+{%- endfor %}
+{%- for message in messages %}
+    {%- if message.content is string %}
+        {%- set content = message.content %}
+    {%- else %}
+        {%- set content = '' %}
+    {%- endif %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is string %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in content %}
+                {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
+                {%- set content = content.split('</think>')[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- if loop.index0 > ns.last_query_index %}
+            {%- if loop.last or (not loop.last and reasoning_content) %}
+                {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
+            {%- else %}
+                {{- '<|im_start|>' + message.role + '\n' + content }}
+            {%- endif %}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- if message.tool_calls %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if (loop.first and content) or (not loop.first) %}
+                    {{- '\n' }}
+                {%- endif %}
+                {%- if tool_call.function %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {{- '<tool_call>\n{"name": "' }}
+                {{- tool_call.name }}
+                {{- '", "arguments": ' }}
+                {%- if tool_call.arguments is string %}
+                    {{- tool_call.arguments }}
+                {%- else %}
+                    {{- tool_call.arguments | tojson }}
+                {%- endif %}
+                {{- '}\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- 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' }}
+    {%- if enable_thinking is defined and enable_thinking is false %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- endif %}
+{%- endif %}

config.json

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+{
+  "architectures": [
+    "Qwen3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "dtype": "bfloat16",
+  "eos_token_id": 151645,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "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": 40960,
+  "max_window_layers": 28,
+  "model_type": "qwen3",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 8,
+  "pad_token_id": null,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 1000000,
+    "rope_type": "default"
+  },
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "transformers_version": "5.13.1",
+  "use_cache": false,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}

generation_config.json

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+{
+  "bos_token_id": 151643,
+  "do_sample": true,
+  "eos_token_id": [
+    151645,
+    151643
+  ],
+  "pad_token_id": 151643,
+  "temperature": 0.6,
+  "top_k": 20,
+  "top_p": 0.95,
+  "transformers_version": "5.13.1"
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a0a86fa55ebf728fbeb069379b3e8fd5707e1ae7f791c20ac5e9824736418789
+size 1192135096

tokenizer.json

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+oid sha256:be75606093db2094d7cd20f3c2f385c212750648bd6ea4fb2bf507a6a4c55506
+size 11422650

tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "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,
+  "local_files_only": false,
+  "model_max_length": 131072,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}