Some GGUF v2 quantizations of the model princeton-nlp/Sheared-LLaMA-1.3B
Sheared-LLaMA-1.3B is a model pruned and further pre-trained from meta-llama/Llama-2-7b-hf. We dynamically load data from the RedPajama dataset. We use 0.4B tokens for pruning and 50B tokens for continued pre-training the pruned model.
- Smaller-scale
- Same vocabulary as LLaMA1 and LLaMA2
- Derived with a budget of 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 |