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--- |
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tags: |
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- text-generation |
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license: cc-by-nc-sa-4.0 |
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language: |
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- ko |
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base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 |
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pipeline_tag: text-generation |
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datasets: |
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- beomi/KoAlpaca-v1.1a |
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- jojo0217/korean_rlhf_dataset |
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- kyujinpy/OpenOrca-KO |
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- nlpai-lab/kullm-v2 |
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widget: |
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- text: > |
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<|system|> |
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You are a chatbot who answers User's questions. |
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<|user|> |
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대한민국의 수도는 어디야? |
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<|assistant|> |
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--- |
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# **DataVortexTL-1.1B-v0.1** |
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<img src="./DataVortex.png" alt="DataVortex" style="height: 8em;"> |
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## Our Team |
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| Research & Engineering | Product Management | |
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| :--------------------: | :----------------: | |
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| Kwangseok Yang | Seunghyun Choi | |
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| Jeongwon Choi | Hyoseok Choi | |
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## **Model Details** |
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### **Base Model** |
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[TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co./TinyLlama/TinyLlama-1.1B-Chat-v1.0) |
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### **Trained On** |
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- **OS**: Ubuntu 20.04 |
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- **GPU**: H100 80GB 1ea |
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- **transformers**: v4.36.2 |
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### **Dataset** |
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- [beomi/KoAlpaca-v1.1a](https://huggingface.co./datasets/beomi/KoAlpaca-v1.1a) |
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- [jojo0217/korean_rlhf_dataset](https://huggingface.co./datasets/jojo0217/korean_rlhf_dataset) |
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- [kyujinpy/OpenOrca-KO](https://huggingface.co./datasets/kyujinpy/OpenOrca-KO) |
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- [nlpai-lab/kullm-v2](https://huggingface.co./datasets/nlpai-lab/kullm-v2) |
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### **Instruction format** |
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It follows **TinyLlama** format. |
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E.g. |
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```python |
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text = """\ |
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<|system|> |
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당신은 사람들이 정보를 찾을 수 있도록 도와주는 인공지능 비서입니다.</s> |
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<|user|> |
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대한민국의 수도는 어디야?</s> |
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<|assistant|> |
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대한민국의 수도는 서울입니다.</s> |
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<|user|> |
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서울 인구는 총 몇 명이야?</s> |
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""" |
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``` |
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## **Model Benchmark** |
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### **[Ko LM Eval Harness](https://github.com/Beomi/ko-lm-evaluation-harness)** |
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| Task | 0-shot | 5-shot | 10-shot | 50-shot | |
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| :--------------- | -------------: | -------------: | -------------: | -----------: | |
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| kobest_boolq | 0.334282 | 0.516446 | 0.500478 | 0.498941 | |
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| kobest_copa | 0.515061 | 0.504321 | 0.492927 | 0.50809 | |
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| kobest_hellaswag | 0.36253 | 0.357733 | 0.355873 | 0.376502 | |
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| kobest_sentineg | 0.481146 | 0.657411 | 0.687417 | 0.635703 | |
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| **Average** | **0.42325475** | **0.50897775** | **0.50917375** | **0.504809** | |
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### **[Ko-LLM-Leaderboard](https://huggingface.co./spaces/upstage/open-ko-llm-leaderboard)** |
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| Average | Ko-ARC | Ko-HellaSwag | Ko-MMLU | Ko-TruthfulQA | Ko-CommonGen V2 | |
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| ------: | -----: | -----------: | ------: | ------------: | --------------: | |
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| 31.5 | 25.26 | 33.53 | 24.56 | 43.34 | 30.81 | |
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## **Implementation Code** |
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This model contains the chat_template instruction format. |
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You can use the code below. |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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device = "cuda" # the device to load the model onto |
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model = AutoModelForCausalLM.from_pretrained("Edentns/DataVortexTL-1.1B-v0.1") |
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tokenizer = AutoTokenizer.from_pretrained("Edentns/DataVortexTL-1.1B-v0.1") |
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messages = [ |
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{"role": "system", "content": "당신은 사람들이 정보를 찾을 수 있도록 도와주는 인공지능 비서입니다."}, |
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{"role": "user", "content": "대한민국의 수도는 어디야?"}, |
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{"role": "assistant", "content": "대한민국의 수도는 서울입니다."}, |
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{"role": "user", "content": "서울 인구는 총 몇 명이야?"} |
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] |
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encodeds = tokenizer.apply_chat_template(messages, return_tensors="pt") |
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model_inputs = encodeds.to(device) |
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model.to(device) |
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generated_ids = model.generate(model_inputs, max_new_tokens=1000, do_sample=True) |
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decoded = tokenizer.batch_decode(generated_ids) |
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print(decoded[0]) |
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``` |
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## **License** |
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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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<div align="center"> |
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<a href="https://edentns.com/"> |
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<img src="./Logo.png" alt="Logo" style="height: 3em;"> |
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</a> |
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</div> |
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