Update README.md

README.md

@@ -6,8 +6,54 @@ license: apache-2.0
 license: apache-2.0
 ---
 
+**Paper**: [https://arxiv.org/pdf/2310.06694.pdf](https://arxiv.org/pdf/2310.06694.pdf)  
+**Code**: https://github.com/princeton-nlp/LLM-Shearing  
+**Models**: [Sheared-LLaMA-1.3B](https://huggingface.co/princeton-nlp/Sheared-LLaMA-1.3B), [Sheared-LLaMA-2.7B](https://huggingface.co/princeton-nlp/Sheared-LLaMA-2.7B)  
+
+---
+
 Sheared-LLaMA-2.7B is a model pruned and further pre-trained from [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf). We dynamically load data from different domains in the [RedPajama dataset](https://github.com/togethercomputeub.com/togethercomputer/RedPajama-Data). We use 0.4B tokens for pruning and 50B tokens for continued pre-training the pruned model. This model can be loaded into huggingface via
 
 ```
 model = AutoModelForCausalLM.from_pretrained("princeton-nlp/Sheared-LLaMA-2.7B")
 ```
+
+- Smaller-scale
+- Same vocabulary as LLaMA1 and LLaMA2
+- Derived with 50B tokens by utilizing existing strong LLMs
+
+## Downstream Tasks
+
+We evaluate on an extensive set of downstream tasks including reasoning, reading comprehension, language modeling and knowledge intensive tasks. Our Sheared-LLaMA models outperform existing large language models. 
+
+| Model               | # Pre-training Tokens | Average Performance |
+| ------------------- | --------------------- | ------------------- |
+| LLaMA2-7B           | 2T                    | 64.6                |
+
+**1.3B**
+
+| Model               | # Pre-training Tokens | Average Performance |
+| ------------------- | --------------------- | ------------------- |
+| OPT-1.3B            | 300B                  | 48.2                |
+| Pythia-1.4B         | 300B                  | 48.9                |
+| Sheared-LLaMA-1.3B  | 50B                   | 51.0                |
+
+**3B**
+
+| Model               | # Pre-training Tokens | Average Performance |
+| ------------------- | --------------------- | ------------------- |
+| OPT-2.7B            | 300B                  | 51.4                |
+| Pythia-2.8B         | 300B                  | 52.5                |
+| INCITE-Base-3B      | 800B                  | 54.7                |
+| Open-LLaMA-3B-v1    | 1T                    | 55.1                |
+| Open-LLaMA-3B-v2    | 1T                    | 55.7                |
+| **Sheared-LLaMA-2.7B**  | **50B**                   | **56.7**                |
+
+## Bibtex
+```
+@article{xia2023sheared,
+   title={Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning},
+   author={Xia, Mengzhou and Gao, Tianyu, and Zeng Zhiyuan, and Chen Danqi},
+   year={2023}
+}
+```