|
|
--- |
|
|
license: apache-2.0 |
|
|
pipeline_tag: text-generation |
|
|
library_name: transformers |
|
|
--- |
|
|
|
|
|
**Paper**: [https://arxiv.org/pdf/2502.07780](https://arxiv.org/pdf/2502.07780) |
|
|
**Code**: https://github.com/IST-DASLab/DarwinLM |
|
|
**Models**: [DarwinLM-2.7B](https://huggingface.co/Shengkun/DarwinLM-2.7B), [DarwinLM-4.6B](https://huggingface.co/Shengkun/DarwinLM-4.6B), [DarwinLM-8.4B](https://huggingface.co/Shengkun/DarwinLM-8.4B) |
|
|
**Pruned Models without Post-training**: [DarwinLM-2.7B-Pruned](https://huggingface.co/Shengkun/DarwinLM-2.7B-Pruned), [DarwinLM-4.6B-Pruned](https://huggingface.co/Shengkun/DarwinLM-4.6B-Pruned), [DarwinLM-8.4B-Pruned](https://huggingface.co/Shengkun/DarwinLM-8.4B-Pruned) |
|
|
|
|
|
--- |
|
|
|
|
|
This repository contains the weights of DarwinLM, an evolutionary structured pruning methods for large language models, as introduced in our paper. DarwinLM builds upon an evolutionary search process, generating multiple offspring models in each generation through mutation, and selecting the fittest for survival. |
|
|
``` |
|
|
# Please add trust_remote_code=True as the repo includes custom code to load and run DarwinLM |
|
|
from transformers import AutoModelForCausalLM |
|
|
|
|
|
model = AutoModelForCausalLM.from_pretrained("Shengkun/DarwinLM-4.6B", trust_remote_code=True) |
|
|
``` |
|
|
|
|
|
## Downstream Tasks |
|
|
|
|
|
**2.7B** |
|
|
|
|
|
| Method | Param. | SciQ | PIQA | WG | ArcE | ArcC | HS | LogiQA | BoolQ | Avg | |
|
|
|----------------------------|--------|------|------|------|------|------|------|--------|-------|------| |
|
|
| **Dense** | 6.7B | 93.7 | 78.1 | 69.3 | 76.4 | 53.0 | 78.6 | 30.7 | 77.7 | 69.2 | |
|
|
| **Uniform** | 3.4B | 44.1 | 57.1 | 53.3 | 33.5 | 32.2 | 27.3 | 25.0 | 49.0 | 40.1 | |
|
|
| **ZipLM** | 4.0B | 87.4 | 64.4 | 58.3 | 53.2 | 33.6 | 50.1 | 25.5 | 63.6 | 54.5 | |
|
|
| **ShearedLLama** | 2.7B | 84.5 | 66.4 | 53.4 | 49.8 | 28.4 | 47.6 | 27.6 | 50.9 | 51.0 | |
|
|
| *DarwinLM (one-shot)* | 2.7B | 85.6 | 70.8 | 55.8 | 63.3 | 38.1 | 53.2 | 28.5 | 62.7 | 57.2 | |
|
|
| **ShearedLLama (50B)** | 2.7B | 90.8 | 75.8 | 64.2 | 67.0 | 41.2 | 70.8 | 28.2 | 63.0 | 62.6 | |
|
|
| **ShearedLLama (10B†)** | 2.7B | 92.0 | 73.6 | 63.1 | 69.8 | 42.0 | 64.4 | 29.0 | 62.1 | 61.9 | |
|
|
| *DarwinLM (10B)* | 2.6B | 90.8 | 72.2 | 65.1 | 68.5 | 45.0 | 67.2 | 28.5 | 64.6 | 62.8 | |
|
|
|
|
|
**4.6B** |
|
|
|
|
|
| Model | Method | Param. | SciQ | PIQA | WG | ArcE | ArcC | HS | LogiQA | BoolQ | MMLU | Avg | |
|
|
|-----------------|------------------------|--------|------|------|------|------|------|------|--------|-------|------|------| |
|
|
| **Llama-3.1-8B** | **Dense** | 8B | 96.3 | 81.2 | 74.3 | 81.4 | 58.2 | 81.7 | 31.1 | 84.0 | 65.2 | 72.8 | |
|
|
| | **Uniform** | 4.5B | 29.1 | 53.6 | 51.7 | 26.0 | 23.6 | 27.1 | 25.5 | 62.1 | 25.7 | 36.1 | |
|
|
| | **ZipLM** | 6B | 65.5 | 60.6 | 56.0 | 40.2 | 34.4 | 34.4 | 28.1 | 63.0 | 27.9 | 45.7 | |
|
|
| | *DarwinLM (one-shot)* | 4.6B | 84.9 | 69.4 | 57.3 | 59.6 | 34.2 | 44.6 | 24.1 | 62.2 | 28.5 | 51.6 | |
|
|
| | **OLMO (2.5T)** | 7B | 92.8 | 79.4 | 70.4 | 73.3 | 44.9 | 77.1 | 27.9 | 72.5 | 28.3 | 62.9 | |
|
|
| | *DarwinLM (10.0B)* | 4.6B | 93.2 | 74.8 | 67.4 | 73.2 | 51.6 | 71.3 | 30.7 | 71.1 | 40.6 | 63.7 | |
|
|
|
|
|
**8.4B** |
|
|
|
|
|
| Model | Method | Param. | SciQ | PIQA | WG | ArcE | ArcC | HS | LogiQA | BoolQ | MMLU | Avg | |
|
|
|---------------------------|------------------------|--------|------|------|------|------|------|------|--------|-------|------|------| |
|
|
| **Qwen-2.5-14B-Instruct** | **Dense** | 14B | 96.8 | 81.9 | 79.1 | 85.7 | 72.8 | 85.1 | 38.5 | 87.9 | 80.0 | 78.6 | |
|
|
| | **Uniform** | 8.6B | 78.2 | 72.7 | 57.6 | 76.1 | 45.6 | 47.0 | 28.1 | 61.6 | 45.5 | 56.9 | |
|
|
| | **ZipLM** | 8.5B | 69.0 | 66.4 | 52.8 | 60.1 | 38.3 | 43.3 | 29.6 | 60.2 | 25.0 | 49.4 | |
|
|
| | *DarwinLM (one-shot)* | 8.4B | 84.3 | 73.9 | 60.5 | 75.7 | 48.0 | 53.3 | 29.3 | 66.9 | 43.1 | 59.4 | |
|
|
| | **OLMO-0424 (2.05T)** | 7B | 96.1 | 80.1 | 72.1 | 73.8 | 49.2 | 78.0 | 29.3 | 80.8 | 52.1 | 67.9 | |
|
|
| | *DarwinLM (10.0B)* | 8.4B | 89.5 | 78.1 | 70.7 | 79.6 | 57.6 | 74.9 | 33.5 | 73.9 | 57.9 | 68.4 | |
|
|
|
|
|
## Bibtex |
|
|
``` |
|
|
@article{tang2025darwinlm, |
|
|
title={DarwinLM: Evolutionary Structured Pruning of Large Language Models}, |
|
|
author={Tang, Shengkun and Sieberling, Oliver and Kurtic, Eldar and Shen, Zhiqiang and Alistarh, Dan}, |
|
|
journal={arXiv preprint arXiv:2502.07780}, |
|
|
year={2025} |
|
|
} |
|
|
``` |
