42 lines
1.2 KiB
Markdown
42 lines
1.2 KiB
Markdown
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---
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language:
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- en
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license: mit
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---
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Nape-0
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Nape series are small models that tries to exihibit much capabilities.
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The model is still in training process. This is very early preview.
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You can load it as follows:
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```
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from transformers import LlamaForCausalLM, AutoTokenizer
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tokenizer = AutoTokenizer.from_pretrained("nnpy/Nape-0")
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model = LlamaForCausalLM.from_pretrained("nnpy/Nape-0")
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```
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## Training
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It took 1 days to train 3 epochs on 4x A6000s using native deepspeed.
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```
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assistant role: You are Semica, a helpful AI assistant.
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user: {prompt}
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assistant:
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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_nnpy__Nape-0)
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| Metric | Value |
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|-----------------------|---------------------------|
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| Avg. | 30.93 |
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| ARC (25-shot) | 32.68 |
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| HellaSwag (10-shot) | 58.68 |
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| MMLU (5-shot) | 24.88 |
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| TruthfulQA (0-shot) | 38.99 |
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| Winogrande (5-shot) | 57.3 |
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| GSM8K (5-shot) | 0.08 |
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| DROP (3-shot) | 3.89 |
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