commit c8f1adb2ee523f61f721094c643ef44a5632e17c
Author: ModelHub XC <noreply@modelhub.org.cn>
Date:   Sun Sep 6 08:28:16 2026 +0800

    初始化项目，由ModelHub XC社区提供模型
    
    Model: steven0226/llama-3.2-3b-taiwan-chat-clean
    Source: Original Platform

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diff --git a/LICENSE.txt b/LICENSE.txt
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diff --git a/NOTICE b/NOTICE
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+Llama 3.2 is licensed under the Llama 3.2 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved.
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diff --git a/README.md b/README.md
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+---
+license: llama3.2
+license_name: llama3.2
+license_link: https://www.llama.com/llama3_2/license/
+language:
+- zh
+- en
+base_model: unsloth/Llama-3.2-3B-Instruct
+datasets:
+- yentinglin/TaiwanChat
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+- llama-3.2
+- unsloth
+- qlora
+- lora
+- taiwan
+- traditional-chinese
+- zh-tw
+- sft
+---
+
+# Llama-3.2-3B Taiwan Chat
+
+**Built with Llama**
+
+以 QLoRA(Unsloth)在 TaiwanChat 子集上微調 Llama-3.2-3B-Instruct 後,**合併為完整 fp16 權重**的版本,下載即用,目標是更自然的繁體中文與台灣在地語感。
+
+*(English)* Llama-3.2-3B-Instruct fine-tuned with QLoRA (Unsloth) on a subset of yentinglin/TaiwanChat to improve Traditional-Chinese (Taiwan) fluency and localization. Loss was computed on assistant responses only. Research / non-commercial use only (the dataset is CC BY-NC 4.0).
+
+## 訓練設定
+
+| 項目 | 值 |
+|---|---|
+| Base model | `unsloth/Llama-3.2-3B-Instruct`(meta-llama/Llama-3.2-3B-Instruct 之權重相同鏡像) |
+| 資料集 | [yentinglin/TaiwanChat](https://huggingface.co/datasets/yentinglin/TaiwanChat):取樣 15000 筆 → 過濾超過 2048 tokens 後剩 14633 筆 |
+| 資料源(id) | gpt4, n/a, sharegpt |
+| 方法 | QLoRA:4-bit NF4 載入 + LoRA(r=16、alpha=16、dropout=0;q/k/v/o/gate/up/down 七個投影層) |
+| max_seq_length | 2048 |
+| Learning rate | 0.0002(linear decay、warmup ratio 0.03) |
+| 訓練量 | 1 epoch(有效 batch size 8) |
+| Optimizer | adamw_8bit(weight decay 0.001) |
+| Loss 遮罩 | 只對 assistant 回覆計 loss(unsloth `train_on_responses_only`) |
+| GPU / 時間 | NVIDIA A100-SXM4-40GB / 約 36.8 分鐘 |
+| 最終 train loss | 1.2069 |
+| Seed | 3407 |
+| 訓練日期 | 2026-07-10 |
+
+![training loss](loss_curve.png)
+
+## 使用方式
+
+這是**合併後的完整 fp16 模型**(~6.5 GB),可直接用 transformers 載入:
+
+```python
+from transformers import pipeline
+
+pipe = pipeline("text-generation", model="steven0226/llama-3.2-3b-taiwan-chat-clean", torch_dtype="auto", device_map="auto")
+out = pipe([{"role": "user", "content": "請推薦台南的夜市小吃"}], max_new_tokens=256)
+print(out[0]["generated_text"][-1]["content"])
+```
+
+也可用 vLLM / Unsloth 載入。只想要輕量 adapter → [steven0226/llama-3.2-3b-taiwan-chat-clean-lora](https://huggingface.co/steven0226/llama-3.2-3b-taiwan-chat-clean-lora)。
+
+## 微調前後對照
+
+同樣 5 個台灣情境問題、greedy decoding(可重現),差異完全來自微調:
+
+<details>
+<summary>請用台灣人習慣的說法介紹珍珠奶茶:它的由來、基本做法,以及為什麼能代表台灣的手搖飲文化。</summary>
+
+**微調前(base):**
+
+珍珠奶茶（也稱為「珍珠」或「奶茶」），是一種非常受歡迎的台灣手搖飲，尤其是在年輕人中非常流行。
+
+**由來**
+
+珍珠奶茶的起源可以追溯到20世紀60年代，當時在台北的街頭小吃店和咖啡館中，開始出現一種特殊的奶茶。這種奶茶使用了高質量的牛奶、糖和珍珠（即是糖化的水晶）等成分，通過手搖混合機製造出一種濃稠且有趣的飲料。
+
+**基本做法**
+
+珍珠奶茶的基本做法如下：
+
+1. 使用高質量的牛奶和糖進行混合。
+2. 加入一些珍珠（糖化的水晶）。
+3. 使用手搖混合機搖拌所有成分，直到得到均勻的色彩和口感。
+4. 將熱水加入混合物中，讓它充滿溫度並擴散。
+5. 最後，將珍珠奶茶放入杯子中，並可添加
+
+**微調後(fine-tuned):**
+
+珍珠奶茶是台灣最受歡迎的飲品之一，尤其是在台灣的街頭和市場上。這個名詞來自於奶茶中含有的珍珠，這些珍珠在熱水中煮沸後會形成小泡子。
+
+珍珠奶茶的由來可以追溯到20世紀初期，當時台灣的街頭和市場上流行著一種叫做「牛奶」或「奶茶」的飲品。這個飲品通常由牛奶、糖和熱水混合而成，並且常常配有珍珠。
+
+珍珠奶茶的基本做法也很簡單。首先，將牛奶、糖和熱水混合在一起。然後，將這個混合物放入一個大型杯子中。最後，將珍珠加入到混合物中並攪拌。
+
+珍珠奶茶能代表台灣的手搖飲文化，因為它是一種傳統的飲品，經過了幾十年的發展。它還具有獨特的風味和口感，使得它成為台灣人喜愛的飲品之一。
+
+</details>
+
+<details>
+<summary>我是剛來台灣的交換學生,想辦手機門號。請比較預付卡和月租方案的差別,以及辦理時要準備哪些證件。</summary>
+
+**微調前(base):**
+
+Congratulations on your arrival in Taiwan! 
+
+當你想辦手機門號時，預付卡和月租方案都是兩個常見的選擇。下面是一個簡單的比較：
+
+**預付卡（Prepaid Card）**
+
+* 优點：可以自行充值，無需每月繳費；可控制使用量。
+* 缺點：需要先充值一定額，否則無法使用；可能有額外的充值費用。
+
+**月租方案（Postpaid Plan）**
+
+* 优點：不需要先充值，毎月繳費；無需額外的充值費用。
+* 缺點：每月繳費，可能會有額外的費用，如數據流量、通話等。
+
+在 Taiwanese 手機業界中，預付卡和月租方案都很流行，但月租方案更為普遍。以下是兩…
+
+**微調後(fine-tuned):**
+
+當然，我很樂意幫助你！在台灣，預付卡和月租方案都是常用的手機服務方式。你可以選擇其中一個或兩個進行手機服務。
+
+預付卡是一種預付費用，通常每月或每年支付一次。這種方式通常適用於短期使用者，如交換學生，因為他們可能不需要長時間的手機服務。預付卡通常提供較少功能的服務，但價格相對較低。
+
+另一方面，月租方案是一種按月付款方式，通常每月支付一定金額。這種方式通常適用於長期使用者，因為它提供更多功能和服務。月租方案通常比預付卡更昂貴，但提供更多功能和服務。
+
+在台灣，預付卡和月租方案都有不同的公司提供，因此你可以根據自己的需求和預算選擇最適合你的服務方式。
+
+為了辦理手機服務，你需要準備以下證件：
+
+…
+
+</details>
+
+<details>
+<summary>請推薦台南有名的夜市,並列出五樣必吃的小吃,每樣用一兩句話介紹。</summary>
+
+**微調前(base):**
+
+台南有許多著名的夜市，以下是一些常見的夜市和五樣必吃小吃：
+
+1. **台南夜市**（台南市區）
+ * 這是台南最知名的夜市之一，提供各種 Taiwanese 飲食、服飾等商品。
+2. **安平夜市**（台南市區）
+ * 這個夜市以其豐富的夜市環境和豐富的美食而聞名，特別是其豐富的 Street Food。
+3. **新化夜市**（新化區）
+ * 這個夜市以其豐富的美食和豐富的購物環境而聞名，特別是其豐富的 Street Food 和手工製品。
+
+以下是五樣必吃的小吃：
+
+1. **麻辣鍋**（台南夜市或安平夜市）
+ * 這是一種非常受歡迎的 Taiwanese 飲食，使用麻辣粉末和肉類調理成…
+
+**微調後(fine-tuned):**
+
+台南最受歡迎的夜市是台南夜市，該夜市位於台南市中區，擁有豐富的文化和歷史。
+
+以下是台南夜市的五樣必吃小吃：
+
+1. 鯨魚麵：這是一種由鯨魚、麵粉和蔬菜製成的美味麵食。它以其獨特的風味和口感而聞名。
+2. 烤雞：烤雞是一種由雞肉烤熟後削皮的美味小吃。它通常與薑、辣椒和醋一起配上，為人們帶來快樂和愉悅。
+3. 蘿蔔餡：蘿蔔餡是一種由蘿蔔、麵粉和蔬菜製成的美味餡食。它以其獨特的風味和口感而聞名。
+4. 烤豬肉：烤豬肉是一種由豬肉烤熟後削皮的美味小吃。它通常與薑、辣�
+
+</details>
+
+<details>
+<summary>「土豆」這個詞在台灣和中國大陸分別指什麼?請再舉三組兩岸說法不同的日常用語,整理成表格。</summary>
+
+**微調前(base):**
+
+「土豆」的意思在台灣是指一種小型的、白色的、扁平的豆類，通常用來做菜或食物。然而，在中國大陸，「土豆」則是指一種長而高大的、白色的、圓形的豆類。
+
+以下是兩岸不同日常用語的表格：
+
+| 語言 | 日常用語 |
+| --- | --- |
+| 台灣 | 土豆 |
+| 中國大陸 | 土豆 |
+
+另外，以下是一些兩岸不同的日常用語：
+
+| 語言 | 日常用語 |
+| --- | --- |
+| 台灣 | 錦路石 (指一種常見的花色) |
+| 中國大陸 | 醉酒 (指一種常見的花色) |
+| 台灣 | 錦路石 |
+| 中國大陸 | 醉酒 |
+| 台灣 | 錦路石 (指一種常見的花色) |
+| 中國大陸…
+
+**微調後(fine-tuned):**
+
+| 語言 | 土豆的意思 |
+| --- | --- |
+| 中文 | 土豆是中國大陸的一種蔬菜，通常用來做飯或烤食物。它是一種白色的、圓形的植物，根部長而細。它被認為有營養價值，並且在許多地區都很受歡迎。 |
+| 台灣 | 在台灣，土豆也是一種蔬菜，但它通常用來做飯或烤食物。它是一種白色的、圓形的植物，根部長而細。它被認為有營養價值，並且在許多地區都很受歡迎。 |
+| 英文 | 在英語中，土豆通常指的是一種白色的、圓形的植物，根部長而細。它是一種蔬菜，可以用來做飯或烤食物。它被認為有營養價值，並且在許多地區都很受歡迎。 |
+
+總結來說，土豆在台灣和中國大陸分別指的是一種蔬菜，用於做飯或烤食物…
+
+</details>
+
+<details>
+<summary>請解釋台灣的「垃圾不落地」政策,以及為什麼垃圾車會播放音樂?</summary>
+
+**微調前(base):**
+
+台灣的「垃圾不落地」政策是由於政府對環境保護和衛生管理的重視。這個政策要求垃圾收集、處理和廢棄地點都要遵守規定，確保垃圾不被遺棄在公共空間中。
+
+關於垃圾車播放音樂的原因，我們可以從以下幾點來看：
+
+1. **警告和引導**：垃圾車上的音樂可能是用來警告人們不要擋路或擋車，讓人們能夠順暢通過。
+2. **安全性**：音樂也可能是用來增加垃圾車的安全性，例如避免人們誤將垃圾車當作一種交通工具。
+3. **環境保護**：音樂也可能是用來促進環境保護，例如鼓勵人們減少垃圾產量和更好地分類垃圾。
+
+總之，垃圾車播放音樂的目的是為了提高安全性、環境保護和衛生管理，讓我們能夠更好
+
+**微調後(fine-tuned):**
+
+台灣的「垃圾不落地」政策是一個旨在減少垃圾排放並促進環境保護的計劃。該計劃要求所有垃圾都要被收集和處理，包括家庭、商業和公共區域中的垃圾。
+
+垃圾車通常會播放音樂，以便它們能夠更有效地運行。這是因為垃圾車需要在特定的時間內運行，以確保所有垃圾都能被收集。通過播放音樂，垃圾車可以更好地管理其運行時間，並確保所有垃圾都能被收集。
+
+</details>
+
+## 限制
+
+- 事實型內容(電信資費、店家、時刻)可能過時或幻覺,請勿當作查詢工具。
+- 訓練資料含翻譯/合成語料,偶爾仍會滲出簡體中文或英文片段。
+- 未做額外安全對齊,安全行為同 base model。
+
+## 授權與合規
+
+- 模型權重依 [Llama 3.2 Community License](https://www.llama.com/llama3_2/license/) 發佈(repo 內附 LICENSE.txt 與 NOTICE),使用須遵守 [Acceptable Use Policy](https://www.llama.com/llama3_2/use-policy)。
+- 訓練資料 TaiwanChat 為 [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/):**本模型僅供研究/非商業用途**。
+
+## 引用
+
+```bibtex
+@misc{lin2023taiwanllm,
+  title={Taiwan LLM: Bridging the Linguistic Divide with a Culturally Aligned Language Model},
+  author={Yen-Ting Lin and Yun-Nung Chen},
+  year={2023},
+  eprint={2311.17487},
+  archivePrefix={arXiv}
+}
+```
+
+訓練使用 [Unsloth](https://github.com/unslothai/unsloth)。訓練程式碼:[github.com/tun0000/llama32-taiwanchat-qlora](https://github.com/tun0000/llama32-taiwanchat-qlora)
diff --git a/chat_template.jinja b/chat_template.jinja
new file mode 100644
index 0000000..d144a9d
--- /dev/null
+++ b/chat_template.jinja
@@ -0,0 +1,139 @@
+{{- bos_token }}
+{%- if custom_tools is defined %}
+    {%- set tools = custom_tools %}
+{%- endif %}
+{%- if not tools_in_user_message is defined %}
+    {%- set tools_in_user_message = true %}
+{%- endif %}
+{%- if not date_string is defined %}
+    {%- set date_string = "26 July 2024" %}
+{%- endif %}
+{%- if not tools is defined %}
+    {%- set tools = none %}
+{%- endif %}
+
+{#- This block extracts the system message, so we can slot it into the right place. #}
+{%- if messages[0]['role'] == 'system' %}
+    {%- set system_message = messages[0]['content'] %}
+    {%- set messages = messages[1:] %}
+{%- else %}
+    {%- set system_message = "" %}
+{%- endif %}
+
+{#- System message + builtin tools #}
+{{- "<|start_header_id|>system<|end_header_id|>
+
+" }}
+{%- if builtin_tools is defined or tools is not none %}
+    {{- "Environment: ipython
+" }}
+{%- endif %}
+{%- if builtin_tools is defined %}
+    {{- "Tools: " + builtin_tools | reject('equalto', 'code_interpreter') | join(", ") + "
+
+"}}
+{%- endif %}
+{{- "Cutting Knowledge Date: December 2023
+" }}
+{{- "Today Date: " + date_string + "
+
+" }}
+{%- if tools is not none and not tools_in_user_message %}
+    {{- "You have access to the following functions. To call a function, please respond with JSON for a function call." }}
+    {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
+    {{- "Do not use variables.
+
+" }}
+    {%- for t in tools %}
+        {{- t | tojson(indent=4) }}
+        {{- "
+
+" }}
+    {%- endfor %}
+{%- endif %}
+{{- system_message }}
+{{- "<|eot_id|>" }}
+
+{#- Custom tools are passed in a user message with some extra guidance #}
+{%- if tools_in_user_message and not tools is none %}
+    {#- Extract the first user message so we can plug it in here #}
+    {%- if messages | length != 0 %}
+        {%- set first_user_message = messages[0]['content'] %}
+        {%- set messages = messages[1:] %}
+    {%- else %}
+        {{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
+{%- endif %}
+    {{- '<|start_header_id|>user<|end_header_id|>
+
+' -}}
+    {{- "Given the following functions, please respond with a JSON for a function call " }}
+    {{- "with its proper arguments that best answers the given prompt.
+
+" }}
+    {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
+    {{- "Do not use variables.
+
+" }}
+    {%- for t in tools %}
+        {{- t | tojson(indent=4) }}
+        {{- "
+
+" }}
+    {%- endfor %}
+    {{- first_user_message + "<|eot_id|>"}}
+{%- endif %}
+
+{%- for message in messages %}
+    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
+        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>
+
+'+ message['content'] + '<|eot_id|>' }}
+    {%- elif 'tool_calls' in message %}
+        {%- if not message.tool_calls|length == 1 %}
+            {{- raise_exception("This model only supports single tool-calls at once!") }}
+        {%- endif %}
+        {%- set tool_call = message.tool_calls[0].function %}
+        {%- if builtin_tools is defined and tool_call.name in builtin_tools %}
+            {{- '<|start_header_id|>assistant<|end_header_id|>
+
+' -}}
+            {{- "<|python_tag|>" + tool_call.name + ".call(" }}
+            {%- for arg_name, arg_val in tool_call.arguments | items %}
+                {{- arg_name + '="' + arg_val + '"' }}
+                {%- if not loop.last %}
+                    {{- ", " }}
+                {%- endif %}
+                {%- endfor %}
+            {{- ")" }}
+        {%- else  %}
+            {{- '<|start_header_id|>assistant<|end_header_id|>
+
+' -}}
+            {{- '{"name": "' + tool_call.name + '", ' }}
+            {{- '"parameters": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- "}" }}
+        {%- endif %}
+        {%- if builtin_tools is defined %}
+            {#- This means we're in ipython mode #}
+            {{- "<|eom_id|>" }}
+        {%- else %}
+            {{- "<|eot_id|>" }}
+        {%- endif %}
+    {%- elif message.role == "tool" or message.role == "ipython" %}
+        {{- "<|start_header_id|>ipython<|end_header_id|>
+
+" }}
+        {%- if message.content is mapping or message.content is iterable %}
+            {{- message.content | tojson }}
+        {%- else %}
+            {{- message.content }}
+        {%- endif %}
+        {{- "<|eot_id|>" }}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|start_header_id|>assistant<|end_header_id|>
+
+' }}
+{%- endif %}
diff --git a/config.json b/config.json
new file mode 100644
index 0000000..f66f74c
--- /dev/null
+++ b/config.json
@@ -0,0 +1,37 @@
+{
+    "architectures": [
+        "LlamaForCausalLM"
+    ],
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "bos_token_id": 128000,
+    "torch_dtype": "bfloat16",
+    "eos_token_id": 128009,
+    "head_dim": 128,
+    "hidden_act": "silu",
+    "hidden_size": 3072,
+    "initializer_range": 0.02,
+    "intermediate_size": 8192,
+    "max_position_embeddings": 131072,
+    "mlp_bias": false,
+    "model_type": "llama",
+    "num_attention_heads": 24,
+    "num_hidden_layers": 28,
+    "num_key_value_heads": 8,
+    "pad_token_id": 128004,
+    "pretraining_tp": 1,
+    "rms_norm_eps": 1e-05,
+    "rope_scaling": {
+        "factor": 32.0,
+        "high_freq_factor": 4.0,
+        "low_freq_factor": 1.0,
+        "original_max_position_embeddings": 8192,
+        "rope_type": "llama3"
+    },
+    "rope_theta": 500000.0,
+    "tie_word_embeddings": true,
+    "unsloth_fixed": true,
+    "unsloth_version": "2026.7.2",
+    "use_cache": true,
+    "vocab_size": 128256
+}
\ No newline at end of file
diff --git a/generation_config.json b/generation_config.json
new file mode 100644
index 0000000..3f8dcb6
--- /dev/null
+++ b/generation_config.json
@@ -0,0 +1,14 @@
+{
+  "bos_token_id": 128000,
+  "do_sample": true,
+  "eos_token_id": [
+    128001,
+    128008,
+    128009
+  ],
+  "max_length": 131072,
+  "pad_token_id": 128004,
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "4.56.2"
+}
diff --git a/loss_curve.png b/loss_curve.png
new file mode 100644
index 0000000..3f2d56f
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new file mode 100644
index 0000000..873ce82
--- /dev/null
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diff --git a/model-00002-of-00002.safetensors b/model-00002-of-00002.safetensors
new file mode 100644
index 0000000..191e260
--- /dev/null
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diff --git a/model.safetensors.index.json b/model.safetensors.index.json
new file mode 100644
index 0000000..d3a1f0f
--- /dev/null
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+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128231": {
+      "content": "<|reserved_special_token_223|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128232": {
+      "content": "<|reserved_special_token_224|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128233": {
+      "content": "<|reserved_special_token_225|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128234": {
+      "content": "<|reserved_special_token_226|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128235": {
+      "content": "<|reserved_special_token_227|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128236": {
+      "content": "<|reserved_special_token_228|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128237": {
+      "content": "<|reserved_special_token_229|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128238": {
+      "content": "<|reserved_special_token_230|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128239": {
+      "content": "<|reserved_special_token_231|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128240": {
+      "content": "<|reserved_special_token_232|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128241": {
+      "content": "<|reserved_special_token_233|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128242": {
+      "content": "<|reserved_special_token_234|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128243": {
+      "content": "<|reserved_special_token_235|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128244": {
+      "content": "<|reserved_special_token_236|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128245": {
+      "content": "<|reserved_special_token_237|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128246": {
+      "content": "<|reserved_special_token_238|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128247": {
+      "content": "<|reserved_special_token_239|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128248": {
+      "content": "<|reserved_special_token_240|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128249": {
+      "content": "<|reserved_special_token_241|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128250": {
+      "content": "<|reserved_special_token_242|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128251": {
+      "content": "<|reserved_special_token_243|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128252": {
+      "content": "<|reserved_special_token_244|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128253": {
+      "content": "<|reserved_special_token_245|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128254": {
+      "content": "<|reserved_special_token_246|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128255": {
+      "content": "<|reserved_special_token_247|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<|begin_of_text|>",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|eot_id|>",
+  "extra_special_tokens": {},
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 131072,
+  "pad_token": "<|finetune_right_pad_id|>",
+  "padding_side": "left",
+  "tokenizer_class": "PreTrainedTokenizerFast",
+  "unk_token": null,
+  "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n    {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n    {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n    {%- set date_string = \"26 July 2024\" %}\n{%- endif %}\n{%- if not tools is defined %}\n    {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n    {%- set system_message = messages[0]['content'] %}\n    {%- set messages = messages[1:] %}\n{%- else %}\n    {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- System message + builtin tools #}\n{{- \"<|start_header_id|>system<|end_header_id|>\n\n\" }}\n{%- if builtin_tools is defined or tools is not none %}\n    {{- \"Environment: ipython\n\" }}\n{%- endif %}\n{%- if builtin_tools is defined %}\n    {{- \"Tools: \" + builtin_tools | reject('equalto', 'code_interpreter') | join(\", \") + \"\n\n\"}}\n{%- endif %}\n{{- \"Cutting Knowledge Date: December 2023\n\" }}\n{{- \"Today Date: \" + date_string + \"\n\n\" }}\n{%- if tools is not none and not tools_in_user_message %}\n    {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n    {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n    {{- \"Do not use variables.\n\n\" }}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\n\n\" }}\n    {%- endfor %}\n{%- endif %}\n{{- system_message }}\n{{- \"<|eot_id|>\" }}\n\n{#- Custom tools are passed in a user message with some extra guidance #}\n{%- if tools_in_user_message and not tools is none %}\n    {#- Extract the first user message so we can plug it in here #}\n    {%- if messages | length != 0 %}\n        {%- set first_user_message = messages[0]['content'] %}\n        {%- set messages = messages[1:] %}\n    {%- else %}\n        {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n{%- endif %}\n    {{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}\n    {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n    {{- \"with its proper arguments that best answers the given prompt.\n\n\" }}\n    {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n    {{- \"Do not use variables.\n\n\" }}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\n\n\" }}\n    {%- endfor %}\n    {{- first_user_message + \"<|eot_id|>\"}}\n{%- endif %}\n\n{%- for message in messages %}\n    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] + '<|eot_id|>' }}\n    {%- elif 'tool_calls' in message %}\n        {%- if not message.tool_calls|length == 1 %}\n            {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n        {%- endif %}\n        {%- set tool_call = message.tool_calls[0].function %}\n        {%- if builtin_tools is defined and tool_call.name in builtin_tools %}\n            {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}\n            {{- \"<|python_tag|>\" + tool_call.name + \".call(\" }}\n            {%- for arg_name, arg_val in tool_call.arguments | items %}\n                {{- arg_name + '=\"' + arg_val + '\"' }}\n                {%- if not loop.last %}\n                    {{- \", \" }}\n                {%- endif %}\n                {%- endfor %}\n            {{- \")\" }}\n        {%- else  %}\n            {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}\n            {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n            {{- '\"parameters\": ' }}\n            {{- tool_call.arguments | tojson }}\n            {{- \"}\" }}\n        {%- endif %}\n        {%- if builtin_tools is defined %}\n            {#- This means we're in ipython mode #}\n            {{- \"<|eom_id|>\" }}\n        {%- else %}\n            {{- \"<|eot_id|>\" }}\n        {%- endif %}\n    {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n        {{- \"<|start_header_id|>ipython<|end_header_id|>\n\n\" }}\n        {%- if message.content is mapping or message.content is iterable %}\n            {{- message.content | tojson }}\n        {%- else %}\n            {{- message.content }}\n        {%- endif %}\n        {{- \"<|eot_id|>\" }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}\n{%- endif %}\n"
+}
\ No newline at end of file