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Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"

🐧 Linux教程，主要内容：Linux 命令、Linux 系统运维、软件运维、精选常用Shell脚本

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Resources about Aspect-based Sentiment Analysis (ABSA)

Linux命令行与shell脚本编程大全案例

📚 The starting point of your career as a Software Quality Assurance Engineer | Quality Automation Engineer 📚

Transformer: PyTorch Implementation of "Attention Is All You Need"

Code for the ALiBi method for transformer language models (ICLR 2022)

🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…

Code for the paper "Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer"

A small package to create visualizations of PyTorch execution graphs

Code and data for COLING 2022 paper titled "Structural Bias For Aspect Sentiment Triplet Extraction"

Repo for "MvP: Multi-view Prompting Improves Aspect Sentiment Tuple Prediction" [ACL'2023]

This is for paper "A semantically enhanced dual encoder for aspect sentiment triplet extraction"

a sample pytorch Implementation of ACL 2021 research paper "Learning Span-Level Interactions for Aspect Sentiment Triplet Extraction".

Code Implementation of "Learning Span-Level Interactions for Aspect Sentiment Triplet Extraction".

Code and data for paper "Grid Tagging Scheme for Aspect-oriented Fine-grained Opinion Extraction". Aspect opinion pair datasets and aspect triplet datasets.

An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Models for All.

code for our NAACL 2019 paper: "BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment Analysis"

程序员延寿指南 | A programmer's guide to live longer

Collection of different types of transformers for learning purposes

An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites

🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐

Fast and memory-efficient exact attention

中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs)