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Code for paper "W-RAG: Weakly Supervised Dense Retrieval in RAG for Open-domain Question Answering"
Soft Prompt Tuning for Augmenting Dense Retrieval with Large Language Models
⚡FlashRAG: A Python Toolkit for Efficient RAG Research
Anserini is a Lucene toolkit for reproducible information retrieval research
[ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-…
[CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.
A Heterogeneous Benchmark for Information Retrieval. Easy to use, evaluate your models across 15+ diverse IR datasets.
Easily use and train state of the art late-interaction retrieval methods (ColBERT) in any RAG pipeline. Designed for modularity and ease-of-use, backed by research.
Reference implementation for DPO (Direct Preference Optimization)
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
Build ChatGPT over your data, all with natural language
The source code of paper "CHEF: A Pilot Chinese Dataset for Evidence-Based Fact-Checking"
EMNLP 2021 - Pre-training architectures for dense retrieval
An annotated implementation of the Transformer paper.
The ChatGPT Retrieval Plugin lets you easily find personal or work documents by asking questions in natural language.
TensorFlow code and pre-trained models for BERT
text2vec, text to vector. 文本向量表征工具，把文本转化为向量矩阵，实现了Word2Vec、RankBM25、Sentence-BERT、CoSENT等文本表征、文本相似度计算模型，开箱即用。
中文语言理解测评基准 Chinese Language Understanding Evaluation Benchmark: datasets, baselines, pre-trained models, corpus and leaderboard
Example code for HTML, CSS, and Javascript for Web Developers Coursera Course
一些非常有趣的python爬虫例子,对新手比较友好,主要爬取淘宝、天猫、微信、微信读书、豆瓣、QQ等网站。(Some interesting examples of python crawlers that are friendly to beginners. )
An interactive guide to the game theory of cooperation
使用Spring Boot+gRPC构建微服务并部署到Istio的示例项目。
基于SpringBoot2.x、SpringCloud和SpringCloudAlibaba并采用前后端分离的企业级微服务多租户系统架构。并引入组件化的思想实现高内聚低耦合，项目代码简洁注释丰富上手容易，适合学习和企业中使用。真正实现了基于RBAC、jwt和oauth2的无状态统一权限认证的解决方案，面向互联网设计同时适合B端和C端用户，支持CI/CD多环境部署，并提供应用管理方便第三方系统…