--- tags: - text-generation license: cc-by-nc-4.0 language: - ko base_model: yanolja/KoSOLAR-10.7B-v0.2 pipeline_tag: text-generation --- # **DataVortexS-10.7B-dpo-v1.3** ## **Model Details** ### **Base Model** [yanolja/KoSOLAR-10.7B-v0.2](https://huggingface.co/yanolja/KoSOLAR-10.7B-v0.2) ### **Trained On** - **OS**: Ubuntu 22.04 - **GPU**: H100 80GB 4ea - **transformers**: v4.36.2 ### **Instruction format** It follows **ChatML** format. E.g. ```python text = """\ <|im_start|>system 당신은 사람들이 정보를 찾을 수 있도록 도와주는 인공지능 비서입니다.<|im_end|> <|im_start|>user 대한민국의 수도는 어디야?<|im_end|> <|im_start|>assistant 대한민국의 수도는 서울입니다.<|im_end|> <|im_start|>user 서울 인구는 총 몇 명이야?<|im_end|> <|im_start|>assistant """ ``` ## **Model Benchmark** ### **[Ko LM Eval Harness](https://github.com/Beomi/ko-lm-evaluation-harness)** On Benchmarking ... | Task | 0-shot | 5-shot | 10-shot | 50-shot | | :--------------- | ------: | ------: | ------: | ------: | | kobest_boolq | 0.0 | 0.0 | 0.0 | 0.0 | | kobest_copa | 0.0 | 0.0 | 0.0 | 0.0 | | kobest_hellaswag | 0.0 | 0.0 | 0.0 | 0.0 | | kobest_sentineg | 0.0 | 0.0 | 0.0 | 0.0 | | **Average** | **0.0** | **0.0** | **0.0** | **0.0** | ### **[Ko-LLM-Leaderboard](https://huggingface.co/spaces/upstage/open-ko-llm-leaderboard)** On Benchmarking ... | Average | Ko-ARC | Ko-HellaSwag | Ko-MMLU | Ko-TruthfulQA | Ko-CommonGen V2 | | ------: | -----: | -----------: | ------: | ------------: | --------------: | | 0 | 0 | 0 | 0 | 0 | 0 | ## **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-v1.3") tokenizer = AutoTokenizer.from_pretrained("Edentns/DataVortexS-10.7B-dpo-v1.3") 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](https://creativecommons.org/licenses/by-nc/4.0/). which allows others to share and adapt the model for non-commercial purposes.