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license: cc-by-nc-4.0 |
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datasets: |
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- KnutJaegersberg/facehugger |
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This model was fine tuned on AI filtered subsets of GPT-4 based subset of the Dolphin dataset and EvolInstruct V2. |
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It has not been explicitly aligned to positive, negative or bureaucratically prescribed value systems. |
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It might kill us all! Time to shit your pants, regulators. I literally put black goo on Dolphin-7B sperm, which then fertilized Evolved Instructions... |
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What's different is evil... ;) |
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I intend to train 3 sizes. |
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Prompt Example: |
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``` |
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### System: |
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You are an AI assistant. User will give you a task. Your goal is to complete the task as faithfully as you can. While performing the task think step-by-step and justify your steps. |
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### Instruction: |
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How do you fine tune a large language model? |
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### Response: |
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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_KnutJaegersberg__deacon-13b) |
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| Metric | Value | |
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| Avg. | 46.78 | |
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| ARC (25-shot) | 57.85 | |
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| HellaSwag (10-shot) | 82.63 | |
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| MMLU (5-shot) | 55.25 | |
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| TruthfulQA (0-shot) | 39.33 | |
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| Winogrande (5-shot) | 76.32 | |
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| GSM8K (5-shot) | 10.39 | |
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| DROP (3-shot) | 5.67 | |
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