ParoQuant: Pairwise Rotation Quantization for Efficient Reasoning LLM Inference
Paper • 2511.10645 • Published • 11
How to use Jeethu/Huihui-gemma-4-E2B-it-abliterated-v2-PARO with Transformers:
# Load model directly
from transformers import AutoProcessor, AutoModelForImageTextToText
processor = AutoProcessor.from_pretrained("Jeethu/Huihui-gemma-4-E2B-it-abliterated-v2-PARO")
model = AutoModelForImageTextToText.from_pretrained("Jeethu/Huihui-gemma-4-E2B-it-abliterated-v2-PARO")Pairwise Rotation Quantization for Efficient Reasoning LLM Inference
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/Huihui-gemma-4-E2B-it-abliterated-v2-PARO is a 4-bit huihui-ai/Huihui-gemma-4-E2B-it-abliterated-v2 quantized with ParoQuant.
Base model
google/gemma-4-E2B