README.md

---
language: en
license: apache-2.0
library_name: transformers
---

# SQFT Fine-tuned Model: PA-sqft-sparsepeft-llama-3-8b-30-gsm8k-heu (Patent application requirements, internal use only)

- Base Model: [IntelLabs/sqft-llama-3-8b-30-base](https://huggingface.co/IntelLabs/sqft-llama-3-8b-30-base)
- Sparsity: 30%
- Quantization: No
- Finetune Method: SQFT + SparsePEFT
- Finetune data: [GSM8K](https://huggingface.co/datasets/openai/gsm8k)
- Sub-Adapter: Heuristic

### Evaluation

```bash
lm_eval --model hf --model_args pretrained=${MODEL_PATH},add_bos_token=True,trust_remote_code=True --tasks gsm8k --batch_size auto:4
```

Refer to our [repo](https://github.com/IntelLabs/Hardware-Aware-Automated-Machine-Learning/tree/main/SQFT) for the environment information to run this command.

## Model Sources

- **Repository:** [https://github.com/IntelLabs/Hardware-Aware-Automated-Machine-Learning/tree/main/SQFT](https://github.com/IntelLabs/Hardware-Aware-Automated-Machine-Learning/tree/main/SQFT)
- **Paper:** [SQFT: Low-cost Model Adaptation in Low-precision Sparse Foundation Models]()

## Citation

```bash
@article{munoz2024sqft,
  title = {SQFT: Low-cost Model Adaptation in Low-precision Sparse Foundation Models},
  author={J. Pablo Munoz and Jinjie Yuan and Nilesh Jain},
  journal={},
  year={2024}
}
```

## License

Apache-2.0