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