---
license: llama3.1
base_model: unsloth/Meta-Llama-3.1-8B
pipeline_tag: text-generation
library_name: transformers
tags:
- code
- energy-efficient-code-generation
- green-software-engineering
- merged
---

# Llama-3.1-8B Energy-SFT

Part of the **Green Tea** replication package for *Beyond the Need for Speed: Energy-Aware Code Generation via Simulation-Guided Reinforcement Learning* (Rajput and Sharma). Energy-contrastive supervised fine-tuning. On the 143-problem held-out benchmark it achieves **5.97% CARET** (Correctness-Adjusted Reduction in Energy Total).

- Base model: `unsloth/Meta-Llama-3.1-8B`
- Training: Energy-contrastive supervised fine-tuning
- Code and full replication: https://github.com/SMART-Dal/green-tea
- Dataset (Zenodo): https://doi.org/10.5281/zenodo.21210099

## Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
m = AutoModelForCausalLM.from_pretrained('saurabh-singh-rajput/green-tea-llama-3.1-8b-energy-sft', device_map='auto')
t = AutoTokenizer.from_pretrained('saurabh-singh-rajput/green-tea-llama-3.1-8b-energy-sft')
```

## Citation
```bibtex
@misc{rajput2026greentea,
  title={Beyond the Need for Speed: Energy-Aware Code Generation via Simulation-Guided Reinforcement Learning},
  author={Rajput, Saurabhsingh and Sharma, Tushar},
  year={2026},
  note={Preprint}
}
```