67 lines
2.1 KiB
Markdown
67 lines
2.1 KiB
Markdown
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---
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license: cc-by-sa-4.0
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---
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# **koOpenChat-sft🐧**
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## Support Me
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시나트라는 개인 프로젝트로, 1인의 자원으로 개발되고 있습니다. 모델이 마음에 드셨다면 약간의 연구비 지원은 어떨까요?
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[<img src="https://cdn.buymeacoffee.com/buttons/default-orange.png" alt="Buy me a Coffee" width="217" height="50">](https://www.buymeacoffee.com/mwell)
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Wanna be a sponser? (Please) Contact me on Telegram **AlzarTakkarsen**
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# **Model Details**
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**Base Model**
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OpenChat3.5
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**Trained On**
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A100 80GB * 1
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**Instruction format**
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It follows [ChatML](https://github.com/openai/openai-python/blob/main/chatml.md) format and **Alpaca(No-Input)** format.
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# **Model Benchmark**
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None
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# **Implementation Code**
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Since, chat_template already contains insturction format above.
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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("maywell/koOpenChat-sft")
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tokenizer = AutoTokenizer.from_pretrained("maywell/koOpenChat-sft")
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messages = [
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{"role": "user", "content": "바나나는 원래 하얀색이야?"},
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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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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_maywell__koOpenChat-sft)
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| Metric | Value |
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|-----------------------|---------------------------|
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| Avg. | 51.36 |
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| ARC (25-shot) | 59.81 |
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| HellaSwag (10-shot) | 78.73 |
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| MMLU (5-shot) | 61.32 |
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| TruthfulQA (0-shot) | 51.24 |
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| Winogrande (5-shot) | 76.4 |
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| GSM8K (5-shot) | 24.18 |
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| DROP (3-shot) | 7.82 |
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