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Jeethu/Lizzy-7B-PARO
Lizzy-7B-PARO is a text generation model from Jeethu. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
Pairwise Rotation Quantization for Efficient Reasoning LLM Inference
Downloads · 30 days
16
15% of all-time downloads
All-time downloads
107
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5 GB on disk
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.safetensors5 GB · 100%
How the weights are stored.
F16878M · 52%
From the Hugging Face model README
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/Lizzy-7B-PARO is a 4-bit flwrlabs/Lizzy-7B quantized with ParoQuant.