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---
language: en
license: apache-2.0
---
# SQFT Fine-tuned Model: sqft-mistral-7b-v0.3-50-gptq-gsm8k-heu-adapter
- Base Model: [IntelLabs/sqft-mistral-7b-v0.3-50-base-gptq](https://huggingface.co/IntelLabs/sqft-mistral-7b-v0.3-50-base-gptq)
- Sparsity: 50%
- Quantization: INT4 (GPTQ)
- Finetune Method: SQFT
- Finetune data: [GSM8K](https://huggingface.co/datasets/openai/gsm8k)
- Sub-Adapter: Heuristic
### Evaluation
```bash
BASE_MODEL_NAME=IntelLabs/sqft-mistral-7b-v0.3-50-base-gptq
ADAPTER_MODEL_NAME=IntelLabs/sqft-mistral-7b-v0.3-50-gptq-gsm8k-heu-adapter
lm_eval --model hf --model_args pretrained=${BASE_MODEL_NAME},peft=${ADAPTER_MODEL_NAME},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
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