--- tags: - text-generation license: cc-by-nc-sa-4.0 language: - ko base_model: hyeogi/SOLAR-10.7B-dpo-v0.1 pipeline_tag: text-generation datasets: - beomi/KoAlpaca-v1.1a - Edentns/Worktronics-FAQ --- # **DataVortexS-10.7B-v0.2** DataVortex ## Our Team | Research & Engineering | Product Management | | :--------------------: | :----------------: | | Kwangseok Yang | Seunghyun Choi | | Jeongwon Choi | Hyoseok Choi | ## **Model Details** ### **Base Model** [hyeogi/SOLAR-10.7B-dpo-v0.1](https://huggingface.co/hyeogi/SOLAR-10.7B-dpo-v0.1) ### **Trained On** - **OS**: Ubuntu 20.04 - **GPU**: H100 80GB 1ea - **transformers**: v4.36.2 ### **Dataset** - [beomi/KoAlpaca-v1.1a](https://huggingface.co/datasets/beomi/KoAlpaca-v1.1a) - Edentns/Worktronics-FAQ - private ### **Instruction format** It follows **Alpaca** format. E.g. ```python text = """\ 당신은 사람들이 정보를 찾을 수 있도록 도와주는 인공지능 비서입니다. ### Instruction: 대한민국의 수도는 어디야? ### Response: 대한민국의 수도는 서울입니다. ### Instruction: 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 | 0.501449 | 0.668845 | 0.652565 | 0.655491 | | kobest_copa | 0.635474 | 0.685637 | 0.708601 | 0.725683 | | kobest_hellaswag | 0.417966 | 0.442942 | 0.428077 | 0.425199 | | kobest_sentineg | 0.681941 | 0.880517 | 0.921754 | 0.939528 | | **Average** | **0.5592075** | **0.66948525** | **0.67774925** | **0.68647525** | ### **[Ko-LLM-Leaderboard](https://huggingface.co/spaces/upstage/open-ko-llm-leaderboard)** | Average | Ko-ARC | Ko-HellaSwag | Ko-MMLU | Ko-TruthfulQA | Ko-CommonGen V2 | | ------: | -----: | -----------: | ------: | ------------: | --------------: | | 43.6 | 38.74 | 50.74 | 38.98 | 44.7 | 44.86 | ## **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-v0.2") tokenizer = AutoTokenizer.from_pretrained("Edentns/DataVortexS-10.7B-v0.2") 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.
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