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gemma-3-4B-T1-it/README_EN.md
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Model: twinkle-ai/gemma-3-4B-T1-it
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2026-07-08 09:14:09 +08:00

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license, language, base_model, library_name, tags, datasets, model-index, metrics
license language base_model library_name tags datasets model-index metrics
gemma
en
zh
google/gemma-3-4b-pt
transformers
Taiwan
R.O.C
zhtw
SLM
Gemma-3
gemma3
lianghsun/tw-reasoning-instruct
lianghsun/tw-contract-review-chat
minyichen/tw-instruct-R1-200k
minyichen/tw_mm_R1
minyichen/LongPaper_multitask_zh_tw_R1
nvidia/Nemotron-Instruction-Following-Chat-v1
name results
gemma-3-4B-T1-it
task dataset metrics
type name
question-answering Single Choice Question
type name config split revision
ikala/tmmluplus tmmlu+ all test c0e8ae955997300d5dbf0e382bf0ba5115f85e8c
name type value
single choice accuracy 47.44
task dataset metrics
type name
question-answering Single Choice Question
type name config split revision
cais/mmlu mmlu all test c30699e
name type value
single choice accuracy 59.13
task dataset metrics
type name
question-answering Single Choice Question
type name config split revision
lianghsun/tw-legal-benchmark-v1 tw-legal-benchmark-v1 all test 66c3a5f
name type value
single choice accuracy 44.18
accuracy

Model Card for gemma-3-4B-T1-it

Gemma3-4B-T1-it_1000_x_500_px

gemma-3-4B-T1-it is a Traditional Chinese instruction-tuned model specifically designed for the context of Taiwan (Republic of China). Built upon the google/gemma-3-4b-pt architecture, this model deeply integrates Taiwan's humanities, social context, and local terminology. It is capable of flexibly handling diverse tasks such as legal provision interpretation, academic material compilation, and daily situational dialogue.

Furthermore, this model has been strengthened in Function Calling structure understanding and output stability, providing a solid foundation for building AI Agents or tool-oriented applications. The model itself does not presuppose specific task workflows, making it suitable for integration with application-layer tool definitions and control logic to progressively develop Agent systems that meet practical needs.

⚠️ Key Specification: This model is a Single Modality version (text-only).

Model Details

Following the widespread resonance of the Formosa-1 Series in the Traditional Chinese open-source community, Twinkle AI continues to dedicate itself to solving the pain points of "insufficient model localization" and "cultural context gaps." gemma-3-4B-T1-Instruct is the team's brand-new attempt based on the Google Gemma 3 architecture. Unlike models that merely perform language translation, the T1 Series places greater emphasis on "Taiwan's local humanities and social depth." We understand that language is a carrier of culture; a good Traditional Chinese model should not only know how to write Traditional Chinese characters but also understand Taiwan's historical context, social norms, and legal system.

Key Features

  • Cultural Alignment (Deep Localization & Humanities/Social Context):

    • Enhanced training on data specific to Taiwan's Humanities & Social Sciences.
    • Corrected common biases in Large Language Models regarding Taiwanese terminology (e.g., legal terms, government agency titles, place names, and descriptions of historical events), ensuring generated content aligns with the cognitive habits of Taiwanese readers.
  • Agent Base: Enhanced Function Calling Capabilities:

    • During the training phase, we specifically reinforced the Function Calling format, equipping the model with excellent structural understanding and tool invocation potential.
    • The model can accurately identify when to call external tools (APIs), precisely extract parameters, and generate final responses based on tool results. Users can further reinforce and integrate the model with domain data, tool definitions, and workflow designs according to their application scenarios (such as RAG, internal enterprise systems, automated processes, professional decision support, etc.).
  • Multi-domain Expertise:

    • Legal Practice: Understands the structure of Taiwan's legal provisions and can assist in basic provision interpretation and legal document support (Note: For assistance only; not formal legal advice).
    • Education Support: Suitable for compiling teaching materials, exam question analyses, and syllabuses that align with Taiwan's curriculum style.
    • Life Applications: Possesses high Instruction Following capabilities, providing precise and natural Traditional Chinese responses for creative writing, daily chat, or information organization.

Model Description

Model Sources

Evaluation

Results

The table below uses the 🌟 Twinkle Eval benchmark framework.

Model Evaluation Mode TMMLU+(%) Taiwan Legal (%) MMLU(%) Runs Option Ordering
google/gemma-3-4b-it box 35.12 (±0.018) 32.69 (±0.021) 41.03 (±0.019) 3 Random
🌟twinkle-ai/Llama-3.2-3B-F1-Instruct (ours) box 44.11 (±0.018) 35.24 (±0.012) 50.64 (±0.019) 3 Random
🌟twinkle-ai/gemma-3-4B-T1-it (ours) box 47.44 (±0.018) 44.18 (±0.022) 59.13 (±0.021) 3 Random

Function Calling Benchmark

We utilized the BFCL (Berkeley Function Calling Leaderboard) to evaluate the model's performance in Function Calling tasks.

The metrics used are as follows:

  • AST Accuracy: Compares the structural similarity between the model-generated function call and the target answer on the Abstract Syntax Tree (AST).
  • It covers four types of questions:
    • Simple Function
    • Multiple Function
    • Parallel Function
    • Parallel Multiple Function
Model Overall Accuracy AST Accuracy (S.) AST Accuracy (M.) AST Accuracy (P.) AST Accuracy (P.M.)
google/gemma-3-4b-it 61 64 88 56 36
🌟twinkle-ai/Llama-3.2-3B-F1-Instruct (ours) 91 93 95 91 87
🌟twinkle-ai/gemma-3-4B-T1-it (ours) 84.5 88 89 80 81

Model Responses

The following examples demonstrate the differences between gemma-3-4B-it (Original) and 🌟 gemma-3-4B-T1-it (Ours) in Taiwan-specific contexts.

Note: In the image, 👈 denotes gemma-3-4B-it; 👉 denotes 🌟gemma-3-4B-T1-it.

Geographical Knowledge

地理位置1

Taiwanese Slang

很盤

Localized Translation

Translations generated by foreign models almost exclusively use Mainland Chinese terminology.

翻譯1

The Pride of Taiwan

周子瑜

Taiwanese Memes

超派鐵拳

🔧 Tool Calling

This model is trained using the Hermes format and supports Parallel calling. Below is a complete example workflow. The Tool calling template is already integrated into the chat_template.

1 Start vLLM Backend

vllm serve twinkle-ai/gemma-3-4B-T1-it \
  --port 8000 \
  --enable-auto-tool-choice \
  --tool-call-parser hermes

2 Define Tools (Functions)

def get_weather(location: str, unit: str):
    return f"{location}的氣溫是{unit}26度晴朗無風"

def search(query: str):
    return "川普終於宣布對等關稅政策,針對 18 個經濟體課徵一半的對等關稅,並從 4/5 起對所有進口產品徵收10%的基準關稅!美國將針對被認定為不當貿易行為(不公平貿易) 的國家,於 4/9 起課徵報復型對等關稅 (Discounted Reciprocal Tariff),例如:日本將被課徵 24% 的關稅,歐盟則為 20%,以取代普遍性的 10% 關稅。\n針對中國則開啟新一波 34% 關稅,並疊加於先前已實施的關稅上,這將使中國進口商品的基本關稅稅率達到 54%,而且這尚未包含拜登總統任內或川普第一任期所施加的額外關稅。加拿大與墨西哥則不適用這套對等關稅制度,但川普認為這些國家在芬太尼危機與非法移民問題尚未完全解決,因此計畫對這兩國的大多數進口商品施加 25% 關稅。另外原本針對汽車與多數其他商品的關稅豁免將於 4/2 到期。\n台灣的部分美國擬向台灣課徵32的對等關稅雖然並未針對晶片特別課徵關稅但仍在記者會中提到台灣搶奪所有的電腦與半導體晶片最終促成台積電對美國投資計劃額外加碼 1,000 億美元的歷史性投資歐盟則課徵20的對等關稅。最後是汽車關稅將於 4/2 起對所有外國製造的汽車課徵25% 關稅。"

tools = [
    {
        "type": "function",
        "function": {
            "name": "get_weather",
            "description": "Get the current weather in a given location",
            "parameters": {
                "type": "object",
                "properties": {
                    "location": {"type": "string", "description": "國家或城市名, e.g., 'Taipei'、'Jaipei'"},
                    "unit": {"type": "string", "description": "氣溫單位,亞洲城市使用攝氏;歐美城市使用華氏", "enum": ["celsius", "fahrenheit"]}
                },
                "required": ["location", "unit"]
            }
        }
    },
    {
        "type": "function",
        "function": {
            "name": "search",
            "description": "這是一個類似 Google 的搜尋引擎,關於知識、天氣、股票、電影、小說、百科等等問題,如果你不確定答案就搜尋一下。",
            "parameters": {
                "type": "object",
                "properties": {
                    "query": {"type": "string", "description": "should be a search query, e.g., '2024 南韓 戒嚴'"}
                },
                "required": ["query"]
            }
        }
    }
]

3 Execute Tool Calls

⚠️ Note: system_prompt is optional unless the tool requires a time reference.

response = client.chat.completions.create(
    model=client.models.list().data[0].id,
    messages=[
        {"role": "system", "content": "記住你的知識截止於 2024/12今天是 2025/4/7"},
        {"role": "user", "content": "台北氣溫如何? 另外,告訴我川普最新關稅政策"},
    ],
    max_tokens=1500,
    temperature=0.6,
    top_p=0.95,
    tools=tools,
    tool_choice="auto"
)

print(response.choices[0].message.tool_calls)

⚙️ Tool Calls List:

[ChatCompletionMessageToolCall(id='chatcmpl-tool-35e74420119349999913a10133b84bd3', function=Function(arguments='{"location": "Taipei", "unit": "celsius"}', name='get_weather'), type='function'), ChatCompletionMessageToolCall(id='chatcmpl-tool-7ffdcb98e59f4134a6171defe7f2e31b', function=Function(arguments='{"query": "Donald Trump latest tariffs policy"}', name='search'), type='function')]

4 Generate Final Answer

response = client.chat.completions.create(
    model=client.models.list().data[0].id,
    messages=[
        {"role": "system", "content": "記住你的知識截止於 2024/12今天是 2025/4/7"},
        {"role": "user", "content": "台北氣溫如何? 另外,告訴我川普最新關稅政策"},
        {
            "role": "assistant",
            "content": "",
            "tool_calls": [
                {
                    "id": response.choices[0].message.tool_calls[0].id,
                    "type": "function",
                    "function": {
                        "name": response.choices[0].message.tool_calls[0].function.name,
                        "arguments": response.choices[0].message.tool_calls[0].function.arguments
                    }
                },
                {
                    "id": response.choices[0].message.tool_calls[1].id,
                    "type": "function",
                    "function": {
                        "name": response.choices[0].message.tool_calls[1].function.name,
                        "arguments": response.choices[0].message.tool_calls[1].function.arguments
                    }
                }
            ]
        },
        {
            "role": "tool",
            "content": search(**json.loads(response.choices[0].message.tool_calls[0].function.arguments)),
            "tool_call_id": response.choices[0].message.tool_calls[0].id # tool_call_id 必須要帶,才能正確配對 工具 及 tool_call
        },
        {
            "role": "tool",
            "content": get_weather(**json.loads(response.choices[0].message.tool_calls[1].function.arguments)),
            "tool_call_id": response.choices[0].message.tool_calls[1].id # tool_call_id 必須要帶,才能正確配對 工具 及 tool_call
        }
    ],
    max_tokens=1500,
    temperature=0.6,
    top_p=0.95,
    tools=tools,
    tool_choice="auto"
)

print(response.choices[0].message.content)

📋 Final Output Content:

以下是您請求的資訊:

**臺北市氣溫**
- 目前的氣溫為 **26°C**(攝氏)
- 天候狀況:晴朗無風

**川普最新關稅政策概述**
1. **對等關稅政策**  
   - 對 18 個經濟體課徵 50% 的對等關稅  
   - 自 4 月 5 日起,所有進口產品全面徵收 10% 基本關稅  

2. **報復型對等關稅**  
   - 日本 24%、歐盟 20%  

3. **對中國的高額關稅**  
   - 增加至 54%(原有關稅 + 新增 34%  

4. **特殊案例**  
   - 加拿大與墨西哥不適用,但其他商品課徵 25%  
   - 汽車與部分商品的免稅即將到期  

5. **對台灣的影響**  
   - 美國計畫對台灣課徵 32% 關稅,但晶片暫無額外課稅  

6. **全球視角**  
   - 歐盟與日本關稅比例相對較高

Citation

@misc{twinkleai2025gemma3t1,
  title        = {gemma-3-4B-T1-it: A Traditional Chinese Instruction-Tuned Language Model for Taiwan},
  author       = {Huang, Liang Hsun and Chen, Min Yi and Lin, Wen Bin and Sung, Dave},
  year         = {2025},
  howpublished = {\url{https://huggingface.co/twinkle-ai/gemma-3-4B-T1-it}},
  note         = {Twinkle AI and APMIC. All authors contributed equally.}
}

Acknowledge

We would like to express our gratitude to APMIC for providing computing power support, enabling the successful completion of this project training. Special thanks to CNA and all partners who provided valuable assistance.

Model Card Authors

Twinkle AI

Model Card Contact

Twinkle AI