Gemma 4 E2B It PARO

--- license: apache-2.0 license_link: https://ai.google.dev/gemma/docs/gemma_4_license library_name: transformers pipeline_tag: any-to-any tags: - gemma4 - gemma - google - paroquant base_model: - google/gemma-4-E2B-it --- # Jeethu/gemma-4-E2B-it-PARO **Pairwise Rotation Quantization for Efficient Reasoning LLM Inference** <p> <a href="https://arxiv.org/abs/2511.10645"><img src="https://img.shields.io/badge/arXiv-2511.10645-b31b1b.svg" alt="Paper"></a> <a href="https://paroquant.z-lab.ai"><img src="https://img.shields.io/badge/Blog-ParoQuant-blue" alt="Blog"></a> <a href="https://huggingface.co/collections/z-lab/paroquant"><img src="https://img.shields.io/badge/%F0%9F%A4%97-Models-yellow" alt="Models"></a> <a href="https://pypi.org/project/paroquant/"><img src="https://img.shields.io/pypi/v/paroquant" alt="PyPI"></a> </p> ParoQuant is the state-of-the-art INT4 quantization for LLMs. It closes the accuracy gap with FP16 while running at near-AWQ speed. Supports NVIDIA GPUs (vLLM, Transformers) and Apple Silicon (MLX). For more information, see https://github.com/z-lab/paroquant. Jeethu/gemma-4-E2B-it-PARO is a 4-bit [google/gemma-4-E2B-it](https://huggingface.co/google/gemma-4-E2B-it) quantized with ParoQuant.

Source context: 11 downloads · 0 likes · Pipeline any-to-any · Library transformers · Repo Jeethu/gemma-4-E2B-it-PARO