--- tags: - text-generation license: cc-by-nc-sa-4.0 language: - ko base_model: yanolja/KoSOLAR-10.7B-v0.1 pipeline_tag: text-generation datasets: - nlpai-lab/kullm-v2 --- # **DataVortexS-10.7B-v0.1** DataVortex ## **Model Details** ### **Base Model** [yanolja/KoSOLAR-10.7B-v0.1](https://huggingface.co/yanolja/KoSOLAR-10.7B-v0.1) ### **Trained On** - **OS**: Ubuntu 20.04 - **GPU**: H100 80GB 1ea - **transformers**: v4.36.2 ### **Dataset** - [nlpai-lab/kullm-v2](https://huggingface.co/datasets/nlpai-lab/kullm-v2) - 152k rows ### **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-LLM-Leaderboard** On Benchmarking ... | Model | Average | Ko-ARC | Ko-HellaSwag | Ko-MMLU | Ko-TruthfulQA | Ko-CommonGen V2 | | ------------------------------------ | ------- | ------ | ------------ | ------- | ------------- | --------------- | | Edentns/DataVortexM-7B-Instruct-v0.1 | 39.81 | 34.13 | 42.35 | 38.73 | 45.46 | 38.37 | | **Edentns/DataVortexS-10.7B-v0.1** | **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-v0.1") tokenizer = AutoTokenizer.from_pretrained("Edentns/DataVortexS-10.7B-v0.1") 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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