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CorpusBrain++: A Continual Generative Pre-Training Framework for Knowledge-Intensive Language Tasks
Two Stones Hit One Bird: Bilevel Positional Encoding for Better Length Extrapolation, ICML 2024
程序员在家做饭方法指南。Programmer's guide about how to cook at home (Simplified Chinese only).
Tevatron - A flexible toolkit for neural retrieval research and development.
[ECIR'24] Implementation of "Large Language Models are Zero-Shot Rankers for Recommender Systems"
A Windows and Office activator using HWID / Ohook / KMS38 / Online KMS activation methods, with a focus on open-source code and fewer antivirus detections.
Hackable and optimized Transformers building blocks, supporting a composable construction.
Official codebase for permutation self-consistency.
Daily updated LLM papers. 每日更新 LLM 相关的论文，欢迎订阅 👏 喜欢的话动动你的小手 🌟 一个
Automatically split your PyTorch models on multiple GPUs for training & inference
A curated list of resources dedicated to retrieval-augmented generation (RAG).
A high-throughput and memory-efficient inference and serving engine for LLMs
Instruct-tune LLaMA on consumer hardware
Is ChatGPT Good at Search? LLMs as Re-Ranking Agent [EMNLP 2023 Outstanding Paper Award]
Repository for prompt-decoding using LLMs (GPT3.5, GPT4, Vicuna, and Zephyr)
Retrieval and Retrieval-augmented LLMs
The official repository for "Bridging the Gap Between Indexing and Retrieval for Differentiable Search Index with Query Generation", Shengyao Zhuang, Houxing Ren, Linjun Shou, Jian Pei, Ming Gong, …
A huggingface transformers implementation of "Transformer Memory as a Differentiable Search Index"
CLEVER 2023: Continual Learning for Generative Retrieval over Dynamic Corpora
一个可以将 Clash 订阅转换成 Proxy Provider 和 External Group(Surge) 的工具
A curated list of papers dedicated to neural text (semantic) matching.
Pyserini is a Python toolkit for reproducible information retrieval research with sparse and dense representations.
Unsupervised text tokenizer for Neural Network-based text generation.
Pytorch implementation of Bert and Pals: Projected Attention Layers for Efficient Adaptation in Multi-Task Learning (https://arxiv.org/abs/1902.02671)
CIKM 2021 Full Paper: FedMatch: Federated Learning Over Heterogeneous Question Answering Data