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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: megastudy/M-SOLAR-10.7B-v1.3 |
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pipeline_tag: text-generation |
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--- |
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# **DataVortexS-10.7B-dpo-v1.6** |
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<img src="./DataVortex.png" alt="DataVortex" style="height: 8em;"> |
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## **Model Details** |
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### **Base Model** |
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[megastudy/M-SOLAR-10.7B-v1.3](https://huggingface.co/megastudy/M-SOLAR-10.7B-v1.3) |
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### **Trained On** |
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- **OS**: Ubuntu 22.04 |
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- **GPU**: H100 80GB 4ea |
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- **transformers**: v4.36.2 |
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### **Instruction format** |
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It follows **ChatML** format. |
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E.g. |
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```python |
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text = """\ |
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<|im_start|>system |
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λΉμ μ μ¬λλ€μ΄ μ 보λ₯Ό μ°Ύμ μ μλλ‘ λμμ£Όλ μΈκ³΅μ§λ₯ λΉμμ
λλ€.<|im_end|> |
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<|im_start|>user |
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λνλ―Όκ΅μ μλλ μ΄λμΌ?<|im_end|> |
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<|im_start|>assistant |
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λνλ―Όκ΅μ μλλ μμΈμ
λλ€.<|im_end|> |
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<|im_start|>user |
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μμΈ μΈκ΅¬λ μ΄ λͺ λͺ
μ΄μΌ?<|im_end|> |
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<|im_start|>assistant |
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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 | 0.491356 | 0.632476 | 0.648679 | 0.640638 | |
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| kobest_copa | 0.555845 | 0.589343 | 0.60019 | 0.580294 | |
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| kobest_hellaswag | 0.36013 | 0.353449 | 0.364599 | 0.346524 | |
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| kobest_sentineg | 0.448148 | 0.768864 | 0.753904 | 0.646915 | |
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| **Average** | **0.46387** | **0.586033** | **0.591843** | **0.553593** | |
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### **[Ko-LLM-Leaderboard](https://huggingface.co/spaces/upstage/open-ko-llm-leaderboard)** |
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On Benchmarking ... |
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| Average | Ko-ARC | Ko-HellaSwag | Ko-MMLU | Ko-TruthfulQA | Ko-CommonGen V2 | |
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| ------: | -----: | -----------: | ------: | ------------: | --------------: | |
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| 0 | 0 | 0 | 0 | 0 | 0 | |
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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/DataVortexS-10.7B-dpo-v1.6") |
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tokenizer = AutoTokenizer.from_pretrained("Edentns/DataVortexS-10.7B-dpo-v1.6") |
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messages = [ |
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{"role": "system", "content": "λΉμ μ μ¬λλ€μ΄ μ 보λ₯Ό μ°Ύμ μ μλλ‘ λμμ£Όλ μΈκ³΅μ§λ₯ λΉμμ
λλ€."}, |
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{"role": "user", "content": "λνλ―Όκ΅μ μλλ μ΄λμΌ?"}, |
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{"role": "assistant", "content": "λνλ―Όκ΅μ μλλ μμΈμ
λλ€."}, |
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{"role": "user", "content": "μμΈ μΈκ΅¬λ μ΄ λͺ λͺ
μ΄μΌ?"} |
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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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