--- tags: - text-generation license: cc-by-nc-sa-4.0 language: - ko base_model: megastudy/M-SOLAR-10.7B-v1.3 pipeline_tag: text-generation --- # **DataVortexS-10.7B-dpo-v1.2** ## Our Team | Research & Engineering | Product Management | | :--------------------: | :----------------: | | Kwangseok Yang | Seunghyun Choi | | Jeongwon Choi | Hyoseok Choi | ## **Model Details** ### **Base Model** [megastudy/M-SOLAR-10.7B-v1.3](https://huggingface.co/megastudy/M-SOLAR-10.7B-v1.3) ### **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 | 0.86665 | 0.932254 | 0.940132 | 0.941561 | | kobest_copa | 0.723415 | 0.780594 | 0.778814 | 0.79982 | | kobest_hellaswag | 0.471639 | 0.466883 | 0.472548 | 0.488648 | | kobest_sentineg | 0.78514 | 0.964734 | 0.972281 | 0.972289 | | **Average** | **0.711711** | **0.786116** | **0.790944** | **0.80058** | ### **[Ko-LLM-Leaderboard](https://huggingface.co/spaces/upstage/open-ko-llm-leaderboard)** | Average | Ko-ARC | Ko-HellaSwag | Ko-MMLU | Ko-TruthfulQA | Ko-CommonGen V2 | | ------: | -----: | -----------: | ------: | ------------: | --------------: | | 56.53 | 52.73 | 64.83 | 52.99 | 58.36 | 53.72 | ## **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-v1.2") tokenizer = AutoTokenizer.from_pretrained("Edentns/DataVortexS-10.7B-dpo-v1.2") 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** The model is licensed under the [cc-by-nc-sa-4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) license, which allows others to copy, modify, and share the work non-commercially, as long as they give appropriate credit and distribute any derivative works under the same license.