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README kr update #804

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May 2, 2024
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README kr update #804

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64 changes: 59 additions & 5 deletions readme/README_ko.md
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Original file line number Diff line number Diff line change
Expand Up @@ -88,10 +88,25 @@ cd data && ./download.sh alpaca && cd -
./scripts/run_finetune.sh \
--model_name_or_path gpt2 \
--dataset_path data/alpaca/train_conversation \
--conversation_template chatml \
--output_model_path output_models/finetuned_gpt2
```

> [!TIP]
> 대화 데이터셋에 대화 템플릿을 지정하려면 `--conversation_template` 매개변수를 추가할 수 있습니다.
>
> <details><summary>예시: Llama-3-8B에 대화 데이터셋 템플릿 지정</summary>
>
>```bash
>cd data && ./download.sh alpaca && cd -
>
>./scripts/run_finetune.sh \
> --model_name_or_path meta-llama/Meta-Llama-3-8B \
> --dataset_path data/alpaca/train_conversation \
> --conversation_template llama3 \
> --output_model_path output_models/finetuned_llama3_8b
>```
> </details>

### Fine-Tuning (LISA)
[LISA](https://arxiv.org/abs/2403.17919) 는 **메모리 효율적인(memory-efficient)** 파인 튜닝 알고리즘이며, 메모리와 무작위로 해동하는 레이어 수 사이의 균형을 가능하게 합니다. 아래 스크립트는 현재 **단일 GPU** 에서만 테스트되었습니다. 최신 업데이트에 주목해 주세요! :smile:
```sh
Expand All @@ -100,24 +115,63 @@ cd data && ./download.sh alpaca && cd -
./scripts/run_finetune_with_lisa.sh \
--model_name_or_path meta-llama/Llama-2-7b-hf \
--dataset_path data/alpaca/train_conversation \
--conversation_template llama2 \
--output_model_path output_models/finetuned_llama \
--output_model_path output_models/finetuned_llama2_7b \
--lisa_activated_layers 1 \
--lisa_interval_steps 20
```

> [!TIP]
> <details><summary>예시: Llama-2-7B 대화 데이터셋 템플릿 지정</summary>
>
>```bash
>cd data && ./download.sh alpaca && cd -
>
>./scripts/run_finetune_with_lisa.sh \
> --model_name_or_path meta-llama/Llama-2-7b-hf \
> --dataset_path data/alpaca/train_conversation \
> --conversation_template llama2 \
> --output_model_path output_models/finetuned_llama2_7b_lisa \
> --lisa_activated_layers 1 \
> --lisa_interval_steps 20
>```
></details>

### Fine-Tuning (LoRA)
LoRA는 전체 매개변수 미세 조정보다 더 효율적인 매개변수 효율적인 미세 조정 알고리즘입니다.
```sh
cd data && ./download.sh alpaca && cd -

# Saves lora only
./scripts/run_finetune_with_lora.sh \
--model_name_or_path facebook/galactica-1.3b \
--dataset_path data/alpaca/train \
--dataset_path data/alpaca/train_conversation \
--output_lora_path output_models/finetuned_galactica_lora
```

> [!TIP]
> <details><summary>예시: Llama-2-7B 대화 데이터셋 템플릿 지정</summary>
>
>```bash
>cd data && ./download.sh alpaca && cd -
>
>./scripts/run_finetune_with_lora.sh \
> --model_name_or_path meta-llama/Llama-2-7b-hf \
> --dataset_path data/alpaca/train_conversation \
> --conversation_template llama2 \
> --output_model_path output_models/finetuned_llama2_7b_lora \
>```
> </details>
>
> <details><summary>LoRA 가중치 병합</summary>
>
>아래 명령어를 사용하여 LoRA 가중치를 원본 모델과 병합할 수 있습니다:
>```sh
>./scripts/run_merge_lora.sh \
> --model_name_or_path Qwen/Qwen1.5-1.8B \
> --lora_model_path output_models/lora \
> --output_model_path output_models/lora_merged \
>```
></details>

### Inference
미세 조정이 완료된 후에는 다음 명령을 사용하여 모델과 대화할 수 있습니다.
```sh
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