A high-throughput and memory-efficient inference and serving engine for LLMs

The official Meta Llama 3 GitHub site

Universal LLM Deployment Engine with ML Compilation

On-device AI across mobile, embedded and edge for PyTorch

本项目分享了中山大学计算机学院本科和研究生阶段的课程资料、笔记、期末考试卷和其他实用的相关资源。希望对同学们的学习有所帮助❤️，如果喜欢记得给个star🌟

Code for the ACL 2017 paper "Get To The Point: Summarization with Pointer-Generator Networks"

"MiniRAG: Making RAG Simpler with Small and Open-Sourced Language Models"

Code for paper Fine-tune BERT for Extractive Summarization

MobileLLM Optimizing Sub-billion Parameter Language Models for On-Device Use Cases. In ICML 2024.

Qualcomm® AI Hub Models is our collection of state-of-the-art machine learning models optimized for performance (latency, memory etc.) and ready to deploy on Qualcomm® devices.

Inference RWKV v5, v6 and v7 with Qualcomm AI Engine Direct SDK

YOLOv5在高通AI Engine Direct环境下进行QNN量化，CPU推理的项目