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 |
- Downloads last month
- 726
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.