Edit model card

Mandoo is a LM assistant supporting English, Chinese and Korean.

Example

from transformers import pipeline

pipe = pipeline("text-generation", model="heegyu/mandoo-9b-2407", device_map="auto", torch_dtype="auto")

messages = [
    {"role": "user", "content": "I want to start saving some money by growing my own food. Can I do this during the winter with an indoor garden?"},
]
pipe(messages, max_new_tokens=128, do_sample=True)

Benchmark Result

Every generation of this model was sampled with temperature=0.7, top_p=0.9, top_k=50

Korean

Model ์‹ฑ๊ธ€ํ„ด
gemma-2-9b-it 7.45
mandoo-9b-2407-sft 6.50

I used sampling with temperature=0.7, max_new_tokens=2048 for generation.

# mandoo-9b-2407-sft
์นดํ…Œ๊ณ ๋ฆฌ: ์ถ”๋ก (Reasoning), ์‹ฑ๊ธ€ ์ ์ˆ˜ ํ‰๊ท : 6.86, ๋ฉ€ํ‹ฐ ์ ์ˆ˜ ํ‰๊ท : 3.86
์นดํ…Œ๊ณ ๋ฆฌ: ์ˆ˜ํ•™(Math), ์‹ฑ๊ธ€ ์ ์ˆ˜ ํ‰๊ท : 5.14, ๋ฉ€ํ‹ฐ ์ ์ˆ˜ ํ‰๊ท : 3.71
์นดํ…Œ๊ณ ๋ฆฌ: ๊ธ€์“ฐ๊ธฐ(Writing), ์‹ฑ๊ธ€ ์ ์ˆ˜ ํ‰๊ท : 7.29, ๋ฉ€ํ‹ฐ ์ ์ˆ˜ ํ‰๊ท : 7.00
์นดํ…Œ๊ณ ๋ฆฌ: ์ฝ”๋”ฉ(Coding), ์‹ฑ๊ธ€ ์ ์ˆ˜ ํ‰๊ท : 8.29, ๋ฉ€ํ‹ฐ ์ ์ˆ˜ ํ‰๊ท : 8.14
์นดํ…Œ๊ณ ๋ฆฌ: ์ดํ•ด(Understanding), ์‹ฑ๊ธ€ ์ ์ˆ˜ ํ‰๊ท : 9.29, ๋ฉ€ํ‹ฐ ์ ์ˆ˜ ํ‰๊ท : 8.57
์นดํ…Œ๊ณ ๋ฆฌ: ๋ฌธ๋ฒ•(Grammar), ์‹ฑ๊ธ€ ์ ์ˆ˜ ํ‰๊ท : 6.43, ๋ฉ€ํ‹ฐ ์ ์ˆ˜ ํ‰๊ท : 3.43
์ „์ฒด ์‹ฑ๊ธ€ ์ ์ˆ˜ ํ‰๊ท : 7.21
์ „์ฒด ๋ฉ€ํ‹ฐ ์ ์ˆ˜ ํ‰๊ท : 5.79
์ „์ฒด ์ ์ˆ˜: 6.50

# gemma-2-9b-it
์นดํ…Œ๊ณ ๋ฆฌ: ์ถ”๋ก (Reasoning), ์‹ฑ๊ธ€ ์ ์ˆ˜ ํ‰๊ท : 9.43, ๋ฉ€ํ‹ฐ ์ ์ˆ˜ ํ‰๊ท : 6.71
์นดํ…Œ๊ณ ๋ฆฌ: ์ˆ˜ํ•™(Math), ์‹ฑ๊ธ€ ์ ์ˆ˜ ํ‰๊ท : 6.14, ๋ฉ€ํ‹ฐ ์ ์ˆ˜ ํ‰๊ท : 8.57
์นดํ…Œ๊ณ ๋ฆฌ: ๊ธ€์“ฐ๊ธฐ(Writing), ์‹ฑ๊ธ€ ์ ์ˆ˜ ํ‰๊ท : 8.71, ๋ฉ€ํ‹ฐ ์ ์ˆ˜ ํ‰๊ท : 8.86
์นดํ…Œ๊ณ ๋ฆฌ: ์ฝ”๋”ฉ(Coding), ์‹ฑ๊ธ€ ์ ์ˆ˜ ํ‰๊ท : 7.43, ๋ฉ€ํ‹ฐ ์ ์ˆ˜ ํ‰๊ท : 6.86
์นดํ…Œ๊ณ ๋ฆฌ: ์ดํ•ด(Understanding), ์‹ฑ๊ธ€ ์ ์ˆ˜ ํ‰๊ท : 8.29, ๋ฉ€ํ‹ฐ ์ ์ˆ˜ ํ‰๊ท : 8.29
์นดํ…Œ๊ณ ๋ฆฌ: ๋ฌธ๋ฒ•(Grammar), ์‹ฑ๊ธ€ ์ ์ˆ˜ ํ‰๊ท : 6.29, ๋ฉ€ํ‹ฐ ์ ์ˆ˜ ํ‰๊ท : 3.86
์ „์ฒด ์‹ฑ๊ธ€ ์ ์ˆ˜ ํ‰๊ท : 7.71
์ „์ฒด ๋ฉ€ํ‹ฐ ์ ์ˆ˜ ํ‰๊ท : 7.19
์ „์ฒด ์ ์ˆ˜: 7.45

English

AlpacaEval

                            length_controlled_winrate  win_rate  standard_error  n_total  avg_length
gpt-4o-2024-05-13                               57.46     51.33            1.47      805        1873
gpt-4-turbo-2024-04-09                          55.02     46.12            1.47      805        1802
gpt4_1106_preview                               50.00     50.00            0.00      805        2049
claude-3-opus-20240229                          40.51     29.11            1.39      805        1388
claude-3-sonnet-20240229                        34.87     25.56            1.34      805        1420
Meta-Llama-3-70B-Instruct                       34.42     33.18            1.39      805        1919
gemini-pro                                      24.38     18.18            1.16      805        1456
Mixtral-8x7B-Instruct-v0.1                      23.69     18.26            1.19      805        1465
Meta-Llama-3-8B-Instruct                        22.92     22.57            1.26      805        1899
**heegyu/mandoo-9b-2407-sft**  <---             19.82     18.18            1.13      805        1847
Mistral-7B-Instruct-v0.2                        17.11     14.72            1.08      805        1676
alpaca-7b                                        5.88      2.59            0.49      805         396

IFEval

Model ์‹ฑ๊ธ€ํ„ด
gemma-2-9b-it 76.95
mandoo-9b-2407-sft 59.19
Strict Accuracy Scores: Avg 0.59191279139
prompt-level: 0.5471349353049908                  
instruction-level: 0.6366906474820144 

Loose Accuracy Scores:
prompt-level: 0.589648798521257                   
instruction-level: 0.6774580335731415
Downloads last month
17
Safetensors
Model size
9.24B params
Tensor type
BF16
ยท
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Datasets used to train heegyu/mandoo-9b-2407-sft