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library_name: transformers
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##
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### Model Description
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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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- **Demo [optional]:** [More Information Needed]
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[
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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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[More Information Needed]
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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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[More Information Needed]
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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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[More Information Needed]
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### Results
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[More Information Needed]
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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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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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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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[More Information Needed]
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**APA:**
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[More Information Needed]
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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 Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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---
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library_name: transformers
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license: apache-2.0
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language:
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- ko
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# GPT-4o Level with Ko-R1-1.5B
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## Model Overview
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Ko-R1-Preview is a Korean implementation of [R1](https://huggingface.co/deepseek-ai/DeepSeek-R1).
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Similar to R1, it adapts a two-step problem-solving process (<think> and <solution>). Drawing inspiration from [Ko et al., 2025](https://www.arxiv.org/abs/2501.02448) the thinking is done in English for performance, and the solution is generated in Korean for readability.
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## Performance
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The model’s performance is evaluated on subsets of the HRM8K benchmark ([Ko et al., 2025](https://www.arxiv.org/abs/2501.02448)).
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The evaluation files are also available here.
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## Inference Settings
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Parameters used during evaluation:
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```
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params = SamplingParams(temperature=0.0, min_tokens=32, max_tokens=8192, repetition_penalty=1.1)
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```
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## Sample Output
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Here is a sample output.
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```
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Q: $2^8=4^x$일 때, $x$의 값은 얼마입니까?
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Response by ko-r1-preview-1.5B:
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<think>
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Okay, so I need to solve the equation 2^8 = 4^x and find the value of x. Let me think about how to approach this step by step.
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First, I remember that when dealing with exponential equations, it's often helpful to express both sides of the equation with the same base if possible.
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That way, I can set the exponents equal to each other because if a^b = c^d, then b must equal d if a and c are the same.
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So, let's see if I can rewrite 4 as a power of 2. Since 4 is 2 squared, right? Because 2 times 2 is 4. So, 4 is 2^2.
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So substituting that into the original equation, we have:\n\n2^8 = (2^2)^x
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Now, using the exponentiation rule (a^m)^n = a^(m*n), which means multiplying the exponents. Applying that here, the right side becomes 2^(2*x).
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So now the equation is:\n\n2^8 = 2^(2x)
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Since the bases are the same (both are powers of 2), their exponents must be equal for the equality to hold.
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Therefore, I can set the exponents equal to each other:\n\n8 = 2x\n\nTo solve for x, I just divide both sides by 2:
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x = 8 / 2
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x = 4
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Wait, let me check that again. If x is 4, then 4^4 would be 256, and 2^8 is also 256. Yeah, that works out.
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But maybe there's another way to verify?
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Alternatively, I could take logarithms on both sides.
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Let's try that method to confirm. Taking the natural log or common log of both sides.
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Let's use natural logs for this example.\n\nTaking ln of both sides:
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ln(2^8) = ln(4^x)
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Using the logarithm property that ln(a^b) = b*ln(a):
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8*ln(2) = x*ln(4)\n\nThen solving for x:
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x = (8*ln(2)) / ln(4)
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But since 4 is 2^2, ln(4) is ln(2^2) = 2*ln(2). Substituting back in:
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x = (8*ln(2)) / (2*ln(2)) = 8/2 = 4
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Same result. So that confirms it. Both methods give x = 4.
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[skipped...]
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</think>
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<solution>
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\\(2^8 = 4^x\\)을 풀기 위해, 우리는 양쪽을 같은 밑으로 표현합니다. \\(4\\)를 \\(2^2\\)로 다시 씁니다:
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\\[
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2^8 = (2^2)^x
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\\]
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지수 법칙 \\((a^m)^n = a^{mn}\\)을 사용하여 오른쪽을 단순화하면:
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\\[\n2^8 = 2^{2x}\n\\]
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밑이 같으므로 지수는 같아야 합니다:
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\\[\n8 = 2x\n\\]\n\n\\(x\\)를 구하면:
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\\[\nx = \\frac{8}{2} = 4\n\\]
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검증:\n- \\(4^4 = 256\\)이고 \\(2^8 = 256\\)이므로 해가 맞음을 확인할 수 있습니다.
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로그를 사용한 검증도 결과를 확인합니다.\n\n따라서, \\(x\\)의 값은 \\(\\boxed{4}\\)입니다.
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</solution>
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```
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## Citation
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```
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@article{ko2025understand,
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title={Understand, Solve and Translate: Bridging the Multilingual Mathematical Reasoning Gap},
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author={Ko, Hyunwoo and Son, Guijin and Choi, Dasol},
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journal={arXiv preprint arXiv:2501.02448},
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year={2025}
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}
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```
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