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Model: Markr-AI/Gukbap-Qwen2.5-7B
Source: Original Platform

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README.md

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+---
+library_name: transformers
+tags: []
+---
+
+# HumanF-MarkrAI/Gukbap-Qwen2.5-7B🍚
+
+## Model Details🍚
+
+### Model Description
+- **Developed by:** HumanF-MarkrAI
+- **Model type:** Ko-Qwen2.5-7B
+- **Language(s):** Korean
+- **Context Length:** 8192
+- **License:** cc-by-nc-4.0
+- **Finetuned from model:** [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct).  
+  
+
+### Model Sources
+When training, we used `A100 40GB GPU`x4.
+  
+
+### Implications🍚
+**Achieving Top-Level Korean Language Performance Surpassing GPT-4 Using Only Open-Source LLMs🔥**
+
+Recently, numerous state-of-the-art (SOTA) models **have leveraged data generated by private models (e.g., ChatGPT, GPT-4) for LLM training,** as seen in projects like `OpenOrca`, `Ultrafeedback`, and `OpenHermes`. 
+However, this approach **may violate these private models' terms of service (ToS).** 
+For instance, OpenAI's license explicitly states: **"⚠️Use Limitation: Creating services that compete with OpenAI.⚠️"** 
+This implies that using data generated by private models to create unrestricted, open LLMs is challenging.
+
+In this context, our model is significant in that **it has been trained solely on a proprietary dataset generated through open-source models.**** Furthermore, it achieved an impressive score of **🔥8.39🔥** in the korean logickor evaluation, **the SOTA for korean based LLM under <7B parameters.**
+
+The **Gukbap-Series LLM🍚** was developed using the data processing and supervised fine-tuning (SFT) methods proposed by **LIMA** and **WizardLM.** This demonstrates **⭐the potential to create unrestricted, general-purpose LLMs using datasets generated solely with open-source LLMs.⭐**
+<details>
+
+  <summary> 한국어버전 </summary>
+  
+**오픈소스 LLM만으로 데이터를 생성하여 GPT-4를 넘어 한국어 최고 레벨을 달성🔥**
+
+오늘날 수많은 여러 SOTA 모델들은 **private model (ChatGPT, GPT4 등)을 활용하여 생성한 데이터를 통해 LLM 훈련**을 진행하고 있습니다. (OpenOrca, Ultrafeedback, OpenHermes 등)
+하지만, 이는 **private model의 이용 약관에 위배**될 수도 있습니다. 대표적으로 OpenAI의 license에는 다음과 같은 말이 명시되어 있습니다: **"⚠️사용 제한: OpenAI의 경쟁하기 위한 서비스를 만드는 것.⚠️"** 즉, private model을 통해 만든 데이터로는 제약이 없는 자유로운 LLM을 만들기는 힘듭니다.
+  
+이러한 관점에서 우리 모델은 **오직 오픈소스을 통해 생성힌 자체 데이터셋로 학습했다는 것**에 큰 의의가 있습니다. 또한 한국어 logickor 자체 평가에서 **🔥8.39🔥**이라는 고득점을 달성하였고, 이는 **7B 이하 한국어 모델 중 SOTA**입니다.
+  
+**Gukbap-Series LLM🍚**은 **LIMA**와 **WizardLM**에서 제안한 데이터 가공 및 SFT 훈련 방법을 통해 제작되었으며, **⭐오픈소스 LLM만으로 데이터셋을 만들어서 제약이 없는 자체 general LLM을 만들 수 있다는 가능성⭐**을 보여줍니다.
+</details>
+
+
+### Training Method (SFT)
+The following papers contain the foundational methodologies for the dataset and training methods we are currently proceeding.
+
+- [LIMA](https://arxiv.org/abs/2305.11206).
+- [WizardLM](https://arxiv.org/abs/2304.12244).
+- [Near Dedup](https://arxiv.org/abs/2304.12244).
+
+
+### SFT Datasets (Private)
+When we made the `Open-Source based dataset`, we use `microsoft/WizardLM-2-8x22B` through [DeepInfra](https://deepinfra.com/).  
+Our datasets are made by `Evolving system`, which is propsed by [WizardLM](https://wizardlm.github.io/WizardLM2/).
+In training, we used 1849 training dataset, and 200 validation dataset.
+  
+- **Wizard-Korea-Datasets:** [MarkrAI/Markr_WizardLM_train_ver4](https://huggingface.co/datasets/MarkrAI/Markr_WizardLM_train_ver4).   
+- **Wizard-Korea-Valid:** [WizardLM_Evol_valid](https://huggingface.co/datasets/MarkrAI/WizardLM_Evol_valid).  
+> Validation loss (epoch 15; Learning rate: 1e-5): 0.9075
+  
+
+### Benchmark Score (Zero-shot)
+
+We internally evaluated [LogicKor](https://github.com/instructkr/LogicKor). 
+We utilized [**gpt-4-1106-preview**](https://platform.openai.com/docs/models/gpt-4-turbo-and-gpt-4) in internal evaluation.  
+It is same manner as `Logickor-v2 eval model`.
+> (GPT-4o occasionally makes errors when grading. For example, it sometimes assigns a score of 0 for English responses to questions that were supposed to be answered in English.)
+
+| Model | 추론 | 수학 | 글쓰기 | 코딩 | 이해 | 문법 | **싱글턴** | **멀티턴** | **Overall** |
+|:---------:|:-----:|:------:|:-----:|:-----:|:----:|:-----:|:-----:|:-----:|:----:|
+| [OpenAI/gpt-4o-2024-05-13](https://lk.instruct.kr/832k1b3wb3x00e4?file=default_xwfHncVI2v.jsonl) | 9.50 | 8.71 | 9.42 | 9.21 | 9.71 | 9.42 | 9.42 | 9.23 | 9.33 |
+| [Anthropic/clauide-3-5-sonnet-20240620](https://lk.instruct.kr/rf8n4j9h6vg1bq7?file=1_shot_R6talIb9Cq.jsonl) | 8.64 | 8.42 | 9.85 | 9.78 | 9.92 | 9.21 | 9.26 | 9.35 | 9.30 |
+| [google/gemini-1.5-pro-001](https://lk.instruct.kr/d54q3zaydbamaos?file=default_zE0CfbdTR3.jsonl) | 9.07 | 8.57 | 9.57 | 9.78 | 9.57 | 9.21 | 9.40 | 9.19 | 9.23 |
+|----|----|----|----|----|----|----|----|----|----|
+| **Gukbap-Qwen2.5-7B🍚** | **8.57** | **8.93** | **9.50** | 9.07 | **9.21** | 5.07 | 8.71 | 8.07 | **8.39** |
+| [Gukbap-Qwen2-7B🍚](https://huggingface.co/HumanF-MarkrAI/Gukbap-Qwen2-7B) | 5.71 | 6.43 | 8.07 | **9.14** | 7.29 | 3.57 | 7.02 | 6.38 | 6.70 |
+| [mirlab/AkaLlama-llama3-70b-v0.1](https://lk.instruct.kr/p9nzhh5ct0strpo?file=default_1ya4ZKRlUm.jsonl) | 5.14 | 5.35 | 4.14 | 9.00 | 7.85 | **7.50** | 5.97 | 7.02 | 6.50 |
+| [Qwen/Qwen2-7B-Instruct](https://lk.instruct.kr/gx4p1k3jojt977d?file=default_guHriJEiaj.jsonl) | 6.07 | 4.71 | 7.21 | 7.00 | 8.00 | 4.85 | 6.61 | 6.00 | 6.30 |
+| [yanolja/EEVE-Korean-Instruct-10.8B-v1.0](https://lk.instruct.kr/tnn389my7sa36a7?file=default_bXVomDLocN.jsonl) | 6.00 | 3.64 | 6.64 | 5.64 | 8.42 | 5.85 | 6.61 | 5.45 | 6.01 |
+  
+If you want to check model's output, please see our [⭐answer⭐](https://huggingface.co/HumanF-MarkrAI/Gukbap-Qwen2.5-7B/blob/main/Gukbap-Qwen2.5-7B.jsonl) file!!
+  
+
+### Benchmark Code
+Our code based on maywell's [Logickor code](https://github.com/instructkr/LogicKor).
+We followed maywell's evaluation method such as `judge_template`, `prompt`, etc.
+
+
+### Chat Prompt
+```yaml
+<|im_start|>user
+Hello! My favorite food is Gukbap🍚!<|im_end|>
+<|im_start|>assistant
+(model answer)
+```
+  
+### Gukbap-Series models🍚🍚
+- [Gukbap-Mistral-7B🍚](https://huggingface.co/HumanF-MarkrAI/Gukbap-Mistral-7B)
+- [Gukbap-Qwen-7B🍚](https://huggingface.co/HumanF-MarkrAI/Gukbap-Qwen2-7B)
+- [Gukbap-Gemma-9B🍚](https://huggingface.co/HumanF-MarkrAI/Gukbap-Gemma2-9B)
+
+
+### BibTeX
+```
+@article{HumanF-MarkrAI,
+  title={Gukbap-Qwen2.5-7B},
+  author={MarkrAI},
+  year={2024},
+  url={https://huggingface.co/HumanF-MarkrAI}
+}
+```

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+}

special_tokens_map.json

@@ -0,0 +1,31 @@
+{
+  "additional_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|>"
+  ],
+  "eos_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

@@ -0,0 +1,211 @@
+{
+  "add_bos_token": false,
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151645": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151646": {
+      "content": "<|object_ref_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151647": {
+      "content": "<|object_ref_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151648": {
+      "content": "<|box_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151649": {
+      "content": "<|box_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151650": {
+      "content": "<|quad_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151651": {
+      "content": "<|quad_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151652": {
+      "content": "<|vision_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151653": {
+      "content": "<|vision_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151654": {
+      "content": "<|vision_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151655": {
+      "content": "<|image_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151656": {
+      "content": "<|video_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151657": {
+      "content": "<tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151658": {
+      "content": "</tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151659": {
+      "content": "<|fim_prefix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151660": {
+      "content": "<|fim_middle|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151661": {
+      "content": "<|fim_suffix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151662": {
+      "content": "<|fim_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151663": {
+      "content": "<|repo_name|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151664": {
+      "content": "<|file_sep|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "additional_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|>"
+  ],
+  "bos_token": null,
+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0]['role'] == 'system' %}\n        {{- messages[0]['content'] }}\n    {%- else %}\n        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\n    {%- endif %}\n    {{- \"\\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>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\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\" }}\n{%- else %}\n    {%- if messages[0]['role'] == 'system' %}\n        {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n    {%- else %}\n        {{- '<|im_start|>system\\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n        {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role }}\n        {%- if message.content %}\n            {{- '\\n' + message.content }}\n        {%- endif %}\n        {%- for tool_call in message.tool_calls %}\n            {%- if tool_call.function is defined %}\n                {%- set tool_call = tool_call.function %}\n            {%- endif %}\n            {{- '\\n<tool_call>\\n{\"name\": \"' }}\n            {{- tool_call.name }}\n            {{- '\", \"arguments\": ' }}\n            {{- tool_call.arguments | tojson }}\n            {{- '}\\n</tool_call>' }}\n        {%- endfor %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- message.content }}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "max_length": 8192,
+  "model_max_length": 131072,
+  "pad_token": "<|im_end|>",
+  "split_special_tokens": false,
+  "stride": 0,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": null
+}