ecotransformers 1.0.0

Towards Net-Zero AI: Reducing Latency and Energy Consumption with Eco-Transformers

EcoTransformers

Sustainable LLM Inference

EcoTransformers is a Python library designed for efficient and sustainable Large Language Model (LLM) inference. It helps developers to reduce inference time, energy consumption, and CO₂ emissions — through lightweight, built-in optimizations.

Key Features:

◦ Optimized inference for Hugging Face transformer models

◦ Primat Technique — a unified optimization method that intelligently reduces redundant computations, skips negligible activations, and applies smart caching

◦ Accelerates inference and lowers the environmental cost of LLM experiments without compromising performance.

Installation:

Install directly from PyPI:

pip install ecotransformers

Usage Examples:

1. Command-line Interface python -m ecotransformers.main
   --model ""
   --prompt "What are the benefits of sustainable AI?"
   --reference "Sustainable AI reduces energy usage and CO₂ emissions."

2. Python API

from ecotransformers.main import transformer results = transformer( model_name="" ) print(results)

PRIMAT(Pruning-Integrated Masked Activation for Transformers) Technique:

◦ The Primat Technique is the optimization engine behind EcoTransformers. ◦ PRIMAT uses adaptive pruning and activation masking for effective execution while maintaining model accuracy. ◦ The Primat Technique is applied automatically — no manual configuration required.

License: This project is licensed under the MIT License — see the LICENSE file for details.

Citation:

If you use EcoTransformers in your research, please cite:

@software{ecotransformers2025, author = {"Shriaarthy E","Sangeetha S"}, title = {Towards Net-Zero AI: Reducing Latency and Energy Consumption with Eco-Transformers}, year = {2025}, url = {https://pypi.org/project/ecotransformers/}, license = {MIT} }