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Edentns/DataVortexS-10.7B-dpo-v1.10

sourceHugging Facecc-by-nc-4.0updated 3y agoView on Hugging Face

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Model Card

DataVortexS-10.7B-dpo-v1.10

Our Team

Research & Engineering	Product Management
Kwangseok Yang	Seunghyun Choi
Jeongwon Choi	Hyoseok Choi

Model Details

Base Model

beomi/OPEN-SOLAR-KO-10.7B

Trained On

—OS: Ubuntu 22.04
—GPU: H100 80GB 4ea
—transformers: v4.36.2

Instruction format

It follows Alpaca (Chat) format.

E.g.

python

text = """\
### System:
당신은 사람들이 정보를 찾을 수 있도록 도와주는 인공지능 비서입니다.

### User:
대한민국의 수도는 어디야?

### Assistant:
대한민국의 수도는 서울입니다.

### User:
서울 인구는 총 몇 명이야?
"""

Model Benchmark

[Ko LM Eval Harness](https://github.com/Beomi/ko-lm-evaluation-harness)

Task	0-shot	5-shot	10-shot	50-shot
kobest_boolq	0.874261	0.897165	0.904985	0.907857
kobest_copa	0.807479	0.845701	0.860809	0.8719
kobest_hellaswag	0.504865	0.502074	0.50717	0.51609
kobest_sentineg	0.409404	0.967251	0.992443	0.982367
Average	0.649002	0.803048	0.816352	0.819553

[Ko-LLM-Leaderboard](https://huggingface.co/spaces/upstage/open-ko-llm-leaderboard)

Average	Ko-ARC	Ko-HellaSwag	Ko-MMLU	Ko-TruthfulQA	Ko-CommonGen V2
56.32	54.27	63.16	49.95	55.08	59.15

Implementation Code

This model contains the chat_template instruction format. You can use the code below.

python

from transformers import AutoModelForCausalLM, AutoTokenizer

device = "cuda" # the device to load the model onto

model = AutoModelForCausalLM.from_pretrained("Edentns/DataVortexS-10.7B-dpo-v1.10")
tokenizer = AutoTokenizer.from_pretrained("Edentns/DataVortexS-10.7B-dpo-v1.10")

messages = [
    {"role": "system", "content": "당신은 사람들이 정보를 찾을 수 있도록 도와주는 인공지능 비서입니다."},
    {"role": "user", "content": "대한민국의 수도는 어디야?"},
    {"role": "assistant", "content": "대한민국의 수도는 서울입니다."},
    {"role": "user", "content": "서울 인구는 총 몇 명이야?"}
]

encodeds = tokenizer.apply_chat_template(messages, return_tensors="pt")

model_inputs = encodeds.to(device)
model.to(device)

generated_ids = model.generate(model_inputs, max_new_tokens=1000, do_sample=True)
decoded = tokenizer.batch_decode(generated_ids)
print(decoded[0])

License

This model is licensed under the cc-by-nc-4.0. which allows others to share and adapt the model for non-commercial purposes.