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  library_name: transformers
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  tags: []
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- # Model Card for Model ID
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- <!-- Provide a quick summary of what the model is/does. -->
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- ## Model Details
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- ### Model Description
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- <!-- Provide a longer summary of what this model is. -->
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- This is the model card of a πŸ€— transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- - **Developed by:** [More Information Needed]
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- - **Funded by [optional]:** [More Information Needed]
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- - **Shared by [optional]:** [More Information Needed]
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- - **Model type:** [More Information Needed]
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- - **Language(s) (NLP):** [More Information Needed]
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- - **License:** [More Information Needed]
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- - **Finetuned from model [optional]:** [More Information Needed]
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- ### Model Sources [optional]
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- <!-- Provide the basic links for the model. -->
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- - **Repository:** [More Information Needed]
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- - **Paper [optional]:** [More Information Needed]
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- - **Demo [optional]:** [More Information Needed]
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- ## Uses
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- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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- ### Direct Use
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- <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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- [More Information Needed]
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- ### Downstream Use [optional]
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- <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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- [More Information Needed]
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- ### Out-of-Scope Use
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- <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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- [More Information Needed]
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- ## Bias, Risks, and Limitations
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- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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- [More Information Needed]
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- ### Recommendations
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- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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- ## How to Get Started with the Model
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- Use the code below to get started with the model.
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- [More Information Needed]
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- ## Training Details
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- ### Training Data
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- <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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- [More Information Needed]
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- ### Training Procedure
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- <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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- #### Preprocessing [optional]
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- [More Information Needed]
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- #### Training Hyperparameters
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- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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- #### Speeds, Sizes, Times [optional]
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- <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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- ## Evaluation
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- <!-- This section describes the evaluation protocols and provides the results. -->
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- ### Testing Data, Factors & Metrics
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- #### Testing Data
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- <!-- This should link to a Dataset Card if possible. -->
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- #### Factors
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- <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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- [More Information Needed]
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- #### Metrics
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- <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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- ### Results
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- #### Summary
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- ## Model Examination [optional]
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- <!-- Relevant interpretability work for the model goes here -->
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- [More Information Needed]
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- ## Environmental Impact
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- <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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- Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- - **Hardware Type:** [More Information Needed]
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- - **Hours used:** [More Information Needed]
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- - **Cloud Provider:** [More Information Needed]
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- - **Compute Region:** [More Information Needed]
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- - **Carbon Emitted:** [More Information Needed]
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- ## Technical Specifications [optional]
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- ### Model Architecture and Objective
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- #### Hardware
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- #### Software
 
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- ## Citation [optional]
 
 
 
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- <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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- **BibTeX:**
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- **APA:**
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- ## Glossary [optional]
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- <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
 
 
 
 
 
 
 
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- ## More Information [optional]
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- ## Model Card Authors [optional]
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- ## Model Card Contact
 
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  library_name: transformers
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  tags: []
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  ---
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+ ---
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+ {}
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+ ---
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+ <p align="center">
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+ <img src="./kormo.png" "style="width: 100%; max-width: 1100px;">
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+ </p>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ # 🦾 KORMo-10B
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+ **KORMo-10B**λŠ” ν•œκ΅­μ–΄μ™€ μ˜μ–΄λ₯Ό λͺ¨λ‘ λ‹€λ£¨λŠ” **10.8B νŒŒλΌλ―Έν„° Fully Open LLM**μž…λ‹ˆλ‹€!
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+ λͺ¨λΈ, ν•™μŠ΅ μ½”λ“œ, ν•™μŠ΅ λ°μ΄ν„°κΉŒμ§€ **λͺ¨λ‘ μ™„μ „ 곡개(Full Stack Open)** λ˜μ–΄ μžˆμ–΄ λˆ„οΏ½οΏ½λ‚˜ μž¬ν˜„ 및 ν™•μž₯이 κ°€λŠ₯ν•©λ‹ˆλ‹€!
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+ - 🧠 **λͺ¨λΈ 크기**: 10.8B νŒŒλΌλ―Έν„°
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+ - πŸ—£οΈ **μ–Έμ–΄**: ν•œκ΅­μ–΄ / μ˜μ–΄
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+ - πŸͺ„ **ν•™μŠ΅ 데이터**: ν•©μ„± 데이터 + 곡개 데이터 μ‘°ν•©
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+ - πŸ§ͺ **λΌμ΄μ„ μŠ€**: Apache 2.0 (상업적 μ‚¬μš© κ°€λŠ₯)
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+ ---
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+ ## πŸ”— Links
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+ - πŸ€— **Hugging Face**: [πŸ‘‰ λͺ¨λΈ λ‹€μš΄λ‘œλ“œ]([https://](https://huggingface.co/KORMo-Team))
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+ - πŸ’» **GitHub Repository**: [πŸ‘‰ ν•™μŠ΅ 및 μΆ”λ‘  μ½”λ“œ](https:/)
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+ ---
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+ ## πŸ†• μ—…λ°μ΄νŠΈ μ†Œμ‹
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+ - πŸš€ **2025.10**: KORMo v1.0 정식 릴리슀!
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+ ---
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+ ## λͺ¨λΈ μ•„ν‚€ν…μ²˜
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+ | ν•­λͺ© | λ‚΄μš© |
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+ |:----|:----|
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+ | Architecture | Transformer Decoder |
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+ | Parameters | 10.8B |
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+ | Context Length | 128K |
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+ | Languages | Korean, English |
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+ | License | Apache 2.0 |
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+ ---
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+ ## πŸ“ˆ 벀치마크 μ„±λŠ₯
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+
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+ ### πŸ“Š μ •λŸ‰ 평가 (Quantitative Evaluation)
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+ | Benchmark | **KORMo-10B** | smolLM3-3B | olmo2-7B | olmo2-13B | kanana1.5-8B | qwen3-8B | llama3.1-8B | gemma3-4B | gemma3-12B |
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+ |:-----------|---------------:|-----------:|---------:|---------:|------------:|--------:|-----------:|---------:|----------:|
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+ | **πŸ‡ΊπŸ‡Έ English Benchmarks** |||||||||||
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+ | arc_challenge | 58.96 | 55.55 | 59.13 | 61.01 | 56.48 | 63.82 | 54.61 | 53.58 | 63.82 |
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+ | arc_easy | 85.48 | 83.21 | 85.06 | 86.57 | 82.74 | 87.50 | 84.01 | 82.83 | 87.37 |
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+ | boolq | 83.46 | 82.17 | 84.50 | 86.48 | 84.53 | 87.71 | 81.87 | 80.70 | 86.61 |
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+ | copa | 93.00 | 91.00 | 92.00 | 93.00 | 88.00 | 92.00 | 93.00 | 89.00 | 95.00 |
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+ | gpqa_main | 30.13 | 26.79 | 26.34 | 29.24 | 29.24 | 30.13 | 23.44 | 30.13 | 35.71 |
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+ | hellaswag | 60.25 | 56.78 | 61.52 | 65.02 | 59.93 | 59.54 | 60.96 | 57.56 | 63.67 |
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+ | mmlu | 67.96 | 61.37 | 62.81 | 66.85 | 63.73 | 76.95 | 65.03 | 59.60 | 73.58 |
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+ | mmlu_global | 63.44 | 57.52 | 59.88 | 63.99 | 60.21 | 75.05 | 61.30 | 57.23 | 70.23 |
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+ | mmlu_pro | 40.18 | 34.94 | 27.29 | 32.50 | 34.93 | 56.58 | 36.23 | 27.79 | 37.07 |
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+ | mmlu_redux | 69.00 | 62.95 | 63.53 | 68.37 | 65.88 | 78.19 | 65.86 | 60.86 | 75.25 |
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+ | openbookqa | 39.00 | 36.40 | 39.00 | 39.60 | 36.80 | 39.20 | 39.00 | 37.00 | 40.20 |
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+ | piqa | 81.12 | 78.45 | 80.79 | 82.64 | 80.30 | 79.05 | 80.90 | 79.49 | 82.59 |
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+ | social_iqa | 52.81 | 50.72 | 55.89 | 57.57 | 57.01 | 56.96 | 53.12 | 51.84 | 56.45 |
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+ | winogrande | 74.03 | 73.32 | 77.03 | 81.69 | 73.32 | 77.03 | 77.74 | 72.93 | 80.51 |
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+ | **English Avg.** | **64.20** | 60.80 | 62.48 | 65.32 | 62.36 | 68.55 | 62.65 | 60.04 | 67.72 |
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+ | **πŸ‡°πŸ‡· Korean Benchmarks** |||||||||||
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+ | click | 55.29 | 46.97 | 37.79 | 41.80 | 62.76 | 60.70 | 49.22 | 49.62 | 62.21 |
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+ | csatqa | 38.00 | 26.67 | 19.33 | 24.67 | 44.67 | 52.00 | 28.67 | 28.67 | 31.33 |
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+ | haerae | 68.29 | 55.82 | 31.62 | 37.58 | 80.75 | 67.19 | 53.25 | 60.68 | 74.34 |
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+ | k2_eval | 84.89 | 75.23 | 49.54 | 63.43 | 84.72 | 84.72 | 76.62 | 76.39 | 85.42 |
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+ | kobest | 75.05 | 69.13 | 57.27 | 59.02 | 81.93 | 80.05 | 70.55 | 69.33 | 77.70 |
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+ | kobalt | 22.86 | 15.86 | 11.43 | 13.14 | 26.29 | 26.57 | 17.43 | 15.57 | 23.86 |
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+ | kmmlu | 46.48 | 38.52 | 33.05 | 31.24 | 48.86 | 56.93 | 40.75 | 39.84 | 51.60 |
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+ | mmlu_global (ko) | 55.16 | 44.15 | 34.00 | 36.95 | 52.65 | 61.95 | 46.34 | 46.33 | 59.68 |
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+ | kr_clinical_qa | 77.32 | 53.97 | 48.33 | 46.22 | 65.84 | 80.00 | 63.54 | 60.00 | 77.22 |
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+ | **Korean Avg.** | **58.15** | 47.37 | 35.82 | 39.34 | 60.94 | 63.35 | 49.60 | 49.60 | 60.37 |
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+ ## πŸ“ μ •μ„± 평가 (LLM-as-a-Judge)
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+ | Benchmark | KORMo-10B | smolLM3-3B | olmo2-7B | olmo2-13B | kanana1.5-8B | qwen3-8B | llama3.1-8B | exaone3.5-8B* | gemma3-12B |
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+ |:----------|---------:|----------:|---------:|---------:|------------:|--------:|------------:|-------------:|-----------:|
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+ | MT-Bench (EN) | 8.32 | 7.15 | 7.32 | 7.64 | 8.45 | 8.70 | 6.32 | 8.15 | 8.70 |
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+ | KO-MT-Bench (KO) | 8.54 | - | - | - | 8.02 | 8.16 | 4.27 | 8.13 | 8.51 |
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+ | LogicKor (KO) | 8.96 | - | - | - | 8.94 | 8.63 | 6.45 | 9.20 | 8.46 |
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+ | **Average** | **8.61** | - | - | - | **8.47** | **8.50** | **5.68** | **8.49** | **8.56** |
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+ ---
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+ ## πŸ“ 인용 (Citation)
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+ ```bibtex
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+ @misc{kormo2025,
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+ title = {KORMo-10B: Fully Open Bilingual Korean-English Large Language Model Trained on Synthetic Data},
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+ author = {KORMo Research Team},
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+ year = {2025},
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+ url = {https://huggingface.co/kormo-lm},
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+ }
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+ ```
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+ ---
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+ ## Contact
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+ - μž„κ²½νƒœ(KyungTae Lim), Professor at Seoultech. `[email protected]`
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+ ## Contributor