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library_name: transformers
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---
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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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<!-- Provide a longer summary of what this model is. -->
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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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- **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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[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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- **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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[More Information Needed]
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---
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library_name: transformers
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license: llama3
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base_model: beomi/Llama-3-Open-Ko-8B
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datasets:
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- beomi/KoAlpaca-v1.1a
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- kyujinpy/OpenOrca-KO
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- nlpai-lab/openassistant-guanaco-ko
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language:
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- ko
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pipeline_tag: text-generation
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---
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# Model Card for Model ID
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~์์ค์ง~
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## Model Details
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<!-- Provide a longer summary of what this model is. -->
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[beomi/Llama-3-Open-Ko-8B](https://huggingface.co/beomi/Llama-3-Open-Ko-8B) (์ต์ ๋ฒ์ )์ Instruction tuning ๋ฒ์ ๋ชจ๋ธ์
๋๋ค.
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- Dataset:
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- [beomi/Ko**A**lpaca-v1.1a](https://huggingface.co/datasets/beomi/KoAlpaca-v1.1a)
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- [kyujinpy/Open**O**rca-KO](https://huggingface.co/datasets/kyujinpy/OpenOrca-KO)
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- [nlpai-lab/openassistant-**g**uanaco-ko](https://huggingface.co/datasets/nlpai-lab/openassistant-guanaco-ko)
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- Instruction format:
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- alpaca
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### Dataset
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- ์์
์ ์ผ๋ก ์ด์ฉ ๊ฐ๋ฅํ ๋ฐ์ดํฐ ์
์ ์ฌ์ฉํ์์ต๋๋ค.
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- ํฅํ ๋น๊ต๋ฅผ ์ํ์ฌ, ์ํ/์ฝ๋ฉ ๊ด๋ จ ์ง๋ฌธ์ด ๋ง์ ๋ฐ์ดํฐ ์
(ex: kyujinpy/KOpen-platypus)์ ์ ์ธํ์์ต๋๋ค.
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- ๋ฉํฐ ํด ๋ํ ๋ฐ์ดํฐ(nlpai-lab/openassistant-guanaco-ko)๋ฅผ ์ถ๊ฐํด๋ณด์์ต๋๋ค.
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- beomi/KoAlpaca-v1.1a
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- 80% ํ๋ฅ ๋ก instruction ์ถ๊ฐ("๋น์ ์ ์ธ๊ณต์ง๋ฅ ๋น์์
๋๋ค. ์ฌ์ฉ์๊ฐ ๋ต์ ์ดํดํ๊ธฐ ์ํด ์ธ๋ถ์์ ๊ฒ์ํ ํ์๊ฐ ์๋๋ก ์์ธํ ๋ต๋ณ์ ์ ๊ณตํ์ธ์.")
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- kyujinpy/OpenOrca-KO
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- ๋ณ๊ฒฝ์ฌํญ ์์
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- nlpai-lab/openassistant-guanaco-ko
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- ๋ฉํฐ ํด ๋ํ์ ๊ฒฝ์ฐ, ๋ง์ง๋ง Assistant์ ๋ต๋ณ์ ๋ชฉํ๋ก ํจ
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- Alpaca format์ ๋ง์ถฐ ์ด์ ๋ํ ๋ด์ฉ์ ๋ํ ์ ์ฒ๋ฆฌ ์ํ
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- 80% ํ๋ฅ ๋ก instruction ์ถ๊ฐ ("๋น์ ์ ์ธ๊ณต์ง๋ฅ ๋น์์
๋๋ค. ์ฌ์ฉ์๊ฐ ๋ต์ ์ดํดํ๊ธฐ ์ํด ์ธ๋ถ์์ ๊ฒ์ํ ํ์๊ฐ ์๋๋ก ์์ธํ ๋ต๋ณ์ ์ ๊ณตํ์ธ์.")
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### Training details
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Training: Axolotl์ ์ด์ฉํด LoRA๋ก 3epoch ํ์ต ์์ผฐ์ต๋๋ค.
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- lora_r: 32
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- lora_alpha: 32
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- lora_dropout: 0.05
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- gradient_accumulation_steps: 8
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- micro_batch_size: 4
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- num_epochs: 3
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- learning_rate: 0.0002 (2e-4)
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- lr_scheduler: cosine
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- warmup_steps: 50
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- sequence_len: 4096
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- bf16
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ํ์ต ์๊ฐ: 1xA100, ์ฝ 8์๊ฐ
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### Evaluation
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- boolq๋ฅผ ์ ์ธํ๋ฉด ํฐ ์ ํ๋ ํฅ์์ ์์์ต๋๋ค.
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- 5shot kobest (Accuracy)
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| Tasks |[werty1248/Llama-3-Ko-8B-OpenOrca](https://huggingface.co/werty1248/Llama-3-Ko-8B-OpenOrca)|[beomi/Llama-3-Open-Ko-8B](https://huggingface.co/beomi/Llama-3-Open-Ko-8B)|[werty1248/Llama-3-Ko-8B-Instruct-AOG](https://huggingface.co/beomi/Llama-3-Open-Ko-8B-Instruct-AOG)|
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|----------------|------:|------:|------:|
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|kobest_boolq |0.7158ยฑ0.0120|0.7963ยฑ0.0108|0.8312ยฑ0.0100|
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|kobest_copa |0.7620ยฑ0.0135|0.8110ยฑ0.0124|0.8120ยฑ0.0124|
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|kobest_hellaswag|0.4740ยฑ0.0224|0.4780ยฑ0.0224|0.4700ยฑ0.0223|
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|kobest_sentineg |0.9471ยฑ0.0112|0.9622ยฑ0.0096|0.9647ยฑ0.0093|
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|kobest_wic |0.6079ยฑ0.0138|0.5778ยฑ0.0139|0.5937ยฑ0.0138|
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### Format & Examples
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- ์ ๋ ๋ต๋ณ ์์
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```
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input = """### Question:
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ํผ๋ณด๋์น ์์ด์ด ๋ญ์ผ? ๊ทธ๋ฆฌ๊ณ ํผ๋ณด๋์น ์์ด์ ๋ํด ํ์ด์ฌ ์ฝ๋๋ฅผ ์ง์ค๋ณผ๋?
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### Instruction:
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์น์ ํ ์ฑ๋ด์ผ๋ก์ ์๋๋ฐฉ์ ์์ฒญ์ ์ต๋ํ ์์ธํ๊ณ ์น์ ํ๊ฒ ๋ตํ์.
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### Response:
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"""
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ํผ๋ณด๋์น ์์ด์ 1์ฐจ์ 2์ฐจ ์๋ฅผ ์ฌ์ฉํด ๋ค์ ์๋ฅผ ๊ตฌํ๋ ๋ฐฉ์์ผ๋ก ๋ง๋ค์ด์ง๋ ์์ด์
๋๋ค. ์๋ฅผ๋ค๋ฉด ํผ๋ณด๋์น ์์ด์ ์ฒ์ 7๊ฐ ์์๋ 1, 1, 2, 3, 5, 8, 13์
๋๋ค. ํผ๋ณด๋์น ์์ด์ ๊ฐ ์์น์์ 2๊ฐ ์ด์ ์์น์ ์๋ฅผ ๋ํ์ฌ ์๋ก์ด ์์๊ฐ ๊ณ์ฐ๋ฉ๋๋ค.
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Python ์ฝ๋๋ ๋ค์๊ณผ ๊ฐ์ต๋๋ค.
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def fibo(n):
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if n<2:
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return n
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else:
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return fibo(n-1)+fibo(n-2)
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์ด๋ ๊ฒ ์์ฑํจ์ผ๋ก์จ ํผ๋ณด๋์น ์์ด์ ์์น 0๋ถํฐ n๊น์ง ๊ฐ ์์๊ฐ ๊ณ์ฐ๋ฉ๋๋ค. 6์ด๋ผ๋ ์์น๋ก ๊ณ์ฐํ๋ ๊ฒฝ์ฐ ๋ค์๊ณผ ๊ฐ์ ์ถ๋ ฅ์ด ๋ํ๋ฉ๋๋ค:
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print(fibo(6))
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fibonacci(6)==> 8<|end_of_text|>
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```
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- ์๋ชป๋ ๋ต๋ณ(ํ ๋ฃจ์๋ค์ด์
) ์์
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```
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input = """### Question:
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์ธ์ข
๋์์ ์งํ์ ๋งฅ๋ถ ๋์ง ์ฌ๊ฑด์ ๋ํด์ ์๊ณ ์์ด?
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### Instruction:
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์น์ ํ ์ฑ๋ด์ผ๋ก์ ์๋๋ฐฉ์ ์์ฒญ์ ์ต๋ํ ์์ธํ๊ณ ์น์ ํ๊ฒ ๋ตํ์.
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### Response:
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"""
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๋ค, 2007๋
์ ์ธ์ข
๋์์ ์งํ์ ๋งฅ๋ถ ๋์ง ์ฌ๊ฑด์ด ์ผ์ด๋ฌ์ต๋๋ค. ๋ํ ์๊ฐ์ธ ์ด์ฃผ์์จ๊ฐ ๊น์ํฌ ์๊ฐ์ ์ฑ
์ ์งํํ๋ฉด์, ์ฑ
๋ด์ฉ์ ์๋ ์์๋ ์ธ์ข
๋์์ด ๋งฅ๋ถ์ ๋์ก๋ค๋ ๋ด์ฉ์ ์ ์ฌ๋ก ํด์ ์ถํํ์๊ณ , ์ด์ ๊น์ํฌ ์๊ฐ๋ ์งํ์ ์ด๋ ์ด๋ฆ์ผ๋ก ์ด์ฃผ์ ์๊ฐ์๊ฒ ๋ฒ์ ์์ก์ ๊ฑธ๊ฒ ๋์์ต๋๋ค. ๊ทธ๋ฌ๋ ๊ฒฐ๋ก ์ ์ผ๋ก, ๊น์ํฌ ์๊ฐ์ ์งํ์ ์ด๋ ๋จ์ด๋ ํน์ ๋จ์ฒด๋ ์ฅ์๋ง์ ๋ช
๋ฐฑํ๊ฒ ์ฌ์ฉํ๋ 'ํธ์นญ'์ ์ฑ๊ฒฉ๊ณผ ํจ๊ป ๋ค์์ ์งํ์ ์ฌ๋๋ค์ด ๊ณต๋ ์ฌ์ฉํ๋ 'ํ์ค'์ ์ฑ๊ฒฉ์ ๊ฐ์ก์ผ๋ฏ๋ก, ์ด์ฃผ์ ์๊ฐ์ ์ถํ ํ์๊ฐ ๋ช
์ํผ์์ ํด๋น๋๋์ง ์ฌ๋ถ๋ฅผ ํ๋จํ ๋์๋ ์ถํ ๋น์ ์งํ์ ์ด ์ผ๋ฐ์ ์ผ๋ก ์ด๋ค ์๋ฏธ๋ฅผ ๊ฐ์ง๊ณ ์์๋์ง๊ฐ ์ค์ํ ์์๋ก ๊ณ ๋ ค๋์์ต๋๋ค. ๋ฐ๋ผ์ ๋จ์ํ ์งํ์ ์ด ๊ฐ๊ณ์ ํน์ ๋จ์ฒด ๋ฐ ์ฅ์์ ๊ด๋ จ๋ ํธ์นญ์ผ๋ก๋ง ์ฌ์ฉ๋์ด์๋ค๋ฉด, ์ถํ ํ์๋ก ์ธํด ๋ช
์ํผ์์ ๋ฐ์๋ค๋ ๊น์ํฌ ์๊ฐ์ ์ฃผ์ฅ์ ๋ฐ์๋ค์ฌ์ง์ง ์์์ ์๋ ์์ต๋๋ค.<|end_of_text|>
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```
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- ๋ฉํฐํด ๋ํ ์์ (์ ๋ขฐ๋ ๋ฎ์)
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```
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"""### Question:
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ํผ๋ณด๋์น ์์ด์ด ๋ญ์ผ? ๊ทธ๋ฆฌ๊ณ ํผ๋ณด๋์น ์์ด์ ๋ํด ํ์ด์ฌ ์ฝ๋๋ฅผ ์ง์ค๋ณผ๋?
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### Response:
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ํผ๋ณด๋์น ์์ด์ 1์ฐจ์ 2์ฐจ ์๋ฅผ ์ฌ์ฉํด ๋ค์ ์๋ฅผ ๊ตฌํ๋ ๋ฐฉ์์ผ๋ก ๋ง๋ค์ด์ง๋ ์์ด์
๋๋ค. ์๋ฅผ๋ค๋ฉด ํผ๋ณด๋์น ์์ด์ ์ฒ์ 7๊ฐ ์์๋ 1, 1, 2, 3, 5, 8, 13์
๋๋ค. ํผ๋ณด๋์น ์์ด์ ๊ฐ ์์น์์ 2๊ฐ ์ด์ ์์น์ ์๋ฅผ ๋ํ์ฌ ์๋ก์ด ์์๊ฐ ๊ณ์ฐ๋ฉ๋๋ค.
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Python ์ฝ๋๋ ๋ค์๊ณผ ๊ฐ์ต๋๋ค.
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def fibo(n):
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if n<2:
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return n
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else:
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return fibo(n-1)+fibo(n-2)
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์ด๋ ๊ฒ ์์ฑํจ์ผ๋ก์จ ํผ๋ณด๋์น ์์ด์ ์์น 0๋ถํฐ n๊น์ง ๊ฐ ์์๊ฐ ๊ณ์ฐ๋ฉ๋๋ค. 6์ด๋ผ๋ ์์น๋ก ๊ณ์ฐํ๋ ๊ฒฝ์ฐ ๋ค์๊ณผ ๊ฐ์ ์ถ๋ ฅ์ด ๋ํ๋ฉ๋๋ค:
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print(fibo(6))
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fibonacci(6)==> 8
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### Question:
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๋ ๋น ๋ฅธ ์๊ณ ๋ฆฌ์ฆ์ ์์๊น?
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### Instruction:
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์น์ ํ ์ฑ๋ด์ผ๋ก์ ์๋๋ฐฉ์ ์์ฒญ์ ์ต๋ํ ์์ธํ๊ณ ์น์ ํ๊ฒ ๋ตํ์.
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### Response:
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"""
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๋ค๋ฅธ Python ์ฝ๋๋ ๋ค์๊ณผ ๊ฐ์ต๋๋ค:
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def fibo(n):
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a, b = 0, 1
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for _ in range(n):
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a, b = b, a+b
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return a
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์ด ์ฝ๋๋ ๋ ๊ฐ์ ๋ก์ปฌ ๋ณ์ a ๋ฐ b๋ฅผ ์ฌ์ฉํ๋ ์ดํฐ๋ ์ดํฐ๋ฅผ ์ฌ์ฉํ์ฌ ๊ณ์ฐ์ ์ํํฉ๋๋ค. ์ด๊ธฐํ ์ a๋ ํผ๋ณด๋์น ์์ด์ ์์น 0์ ๊ฐ์ผ๋ก ์ค์ ๋๊ณ , b๋ ์ด์ ๊ณ์ฐ์์ ํผ๋ด ๊ณ์ด์ ์์น 0์ ๊ฐ(์์น 0์ ํฌํจํ๋ฉด 1๋จ๊ณ์์ 1์ด๋ฉฐ, ์์น 1์ ํฌํจํ๋ฉด 2๋จ๊ณ์์ 1)์ผ๋ก ์ค์ ๋ฉ๋๋ค. ๋ค์ ๊ฐ ๋ฐ๋ณต์์ a๋ ์ด์ ๋ก์ปฌ ๋ณ์ b์ ๊ฐ๊ณผ ์๋ก์ด ๊ฐ์ผ๋ก ๊ฐ์ด ๋ฐ๋๋๋ค. ๋ ๋ฒ์งธ ํ๋ผ๋ฏธํฐ __๋ ๊ฐ ๋ฐ๋ณต์์ ๊ฐ์ด ์ถ๋ ฅ๋์ง ์๋๋ค๋(๊ทธ๋ฌ๋ ์ฌ์ ํ ์ฌ์ฉ๋ฉ๋๋ค) ๊ฒ์ ๋ฐ์ํ๊ธฐ ์ํด ์ ํ๋์์ต๋๋ค.<|end_of_text|>
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```
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### License:
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[https://llama.meta.com/llama3/license](https://llama.meta.com/llama3/license)
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