File size: 1,353 Bytes
b429e01
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
---
license: llama3
---
# 🔹 Key Highlights:

- 13% Fewer Parameters: nyun-c2-llama3-61B comprises approximately 13% fewer parameters than the popular Llama-3-70B.
- Better Performance: Despite having fewer parameters, this model performs better than Llama3-70B on multiple benchmarks.
- No Fine-Tuning Required: This model undergoes no fine-tuning, showcasing the raw potential of our optimization techniques.

## Pipeline and Collaboration

For insights into the pipeline and the list of methods used to optimize these models, check out our PruneGPT repository (https://github.com/nyunAI/PruneGPT). 
We invite companies and organizations interested in joining forces with us to release more such open-source variants to reach out at [email protected].

### Model Performance

| Dataset | nyun-c2-llama3-61B | Meta-Llama3-70B | Meta-Llama2-70B | MBZUAI K2-65B |
| --- | --- | --- | --- | --- |
| MMLU (5-shot) | 78.8 | 79.5 | 69.7 | 67.9 |
| Winogrande (5-shot) | 86.2 | 83.1 | 81.8 | 77.0 |
| BoolQ (0-shot) | 85.1 | 79.0 | 73.1 | 83.0 |
| Hellaswag (10-shot) | 87.4 | 88.0 | 86.9 | 85.5 |
| Arc Challenge (25-shot) | 67.6 | 68.8 | 67.2 | 64.8 |
| GSM8K (5-shot) | 79.4 | 76.9 | 52.6 | 50.2 |
| Average | 80.7 | 79.2 |  71.9 | 71.4 |

- **Developed by:** [Nyun AI](https://nyunai.com/)
- **Repository:** [Github](https://github.com/nyunAI/PruneGPT)