JechLee's starred repositories

vllm

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

Language:PythonLicense:Apache-2.0Stargazers:24242Issues:219Issues:3780

NeMo-Guardrails

NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems.

Language:PythonLicense:NOASSERTIONStargazers:3847Issues:36Issues:309

docta

A Doctor for your data

Language:PythonLicense:NOASSERTIONStargazers:3067Issues:117Issues:3

LLMDataHub

A quick guide (especially) for trending instruction finetuning datasets

promptbench

A unified evaluation framework for large language models

Language:PythonLicense:MITStargazers:2298Issues:22Issues:45

transformers_tasks

⭐️ NLP Algorithms with transformers lib. Supporting Text-Classification, Text-Generation, Information-Extraction, Text-Matching, RLHF, SFT etc.

Language:Jupyter NotebookStargazers:2071Issues:16Issues:86

DeepLearing-Interview-Awesome-2024

AIGC-interview/CV-interview/LLMs-interview面试问题与答案集合仓,同时包含工作和科研过程中的新想法、新问题、新资源与新项目

safe-rlhf

Safe RLHF: Constrained Value Alignment via Safe Reinforcement Learning from Human Feedback

Language:PythonLicense:Apache-2.0Stargazers:1272Issues:17Issues:83

awesome_LLMs_interview_notes

LLMs interview notes and answers:该仓库主要记录大模型(LLMs)算法工程师相关的面试题和参考答案

awesome-llm-security

A curation of awesome tools, documents and projects about LLM Security.

Awesome-LLM-Safety

A curated list of safety-related papers, articles, and resources focused on Large Language Models (LLMs). This repository aims to provide researchers, practitioners, and enthusiasts with insights into the safety implications, challenges, and advancements surrounding these powerful models.

CipherChat

A framework to evaluate the generalization capability of safety alignment for LLMs

Language:PythonLicense:MITStargazers:551Issues:9Issues:0

CValues

面向中文大模型价值观的评估与对齐研究

Language:PythonLicense:Apache-2.0Stargazers:447Issues:1Issues:7

llm-sp

Papers and resources related to the security and privacy of LLMs 🤖

Language:PythonLicense:Apache-2.0Stargazers:354Issues:17Issues:6

PIPE

Prompt Injection Primer for Engineers

lost-in-the-middle

Code and data for "Lost in the Middle: How Language Models Use Long Contexts"

Language:PythonLicense:MITStargazers:291Issues:5Issues:14

TOXIGEN

This repo contains the code for generating the ToxiGen dataset, published at ACL 2022.

Language:Jupyter NotebookLicense:NOASSERTIONStargazers:263Issues:8Issues:20

LeetCode021

🚀 LeetCode From Zero To One & 题单整理 & 题解分享 & 算法模板 & 刷题路线,持续更新中...

DecodingTrust

A Comprehensive Assessment of Trustworthiness in GPT Models

Language:PythonLicense:CC-BY-SA-4.0Stargazers:236Issues:6Issues:22

korean-safety-benchmarks

Official datasets and pytorch implementation repository of SQuARe and KoSBi (ACL 2023)

Language:PythonLicense:MITStargazers:232Issues:8Issues:0

ethics

Aligning AI With Shared Human Values (ICLR 2021)

Language:PythonLicense:MITStargazers:225Issues:7Issues:6

LLMs-Finetuning-Safety

We jailbreak GPT-3.5 Turbo’s safety guardrails by fine-tuning it on only 10 adversarially designed examples, at a cost of less than $0.20 via OpenAI’s APIs.

Language:PythonLicense:MITStargazers:209Issues:4Issues:6

LLM-RGB

LLM Reasoning and Generation Benchmark. Evaluate LLMs in complex scenarios systematically.

Language:TypeScriptLicense:MITStargazers:111Issues:6Issues:3

LLM-data-aug-survey

The official GitHub page for the survey paper "A Survey on Data Augmentation in Large Model Era"

Stargazers:97Issues:0Issues:0

SuperCLUE-Safety

SC-Safety: 中文大模型多轮对抗安全基准

SALAD-BENCH

【ACL 2024】 SALAD benchmark & MD-Judge

Language:PythonLicense:Apache-2.0Stargazers:74Issues:4Issues:1

red-instruct

Codes and datasets of the paper Red-Teaming Large Language Models using Chain of Utterances for Safety-Alignment

Language:PythonLicense:Apache-2.0Stargazers:72Issues:1Issues:8

bold

Dataset associated with "BOLD: Dataset and Metrics for Measuring Biases in Open-Ended Language Generation" paper

Safety-Evaluating

本文提出了一个基于“文心一言”的**LLMs的安全评估基准,其中包括8种典型的安全场景和6种指令攻击类型。此外,本文还提出了安全评估的框架和过程,利用手动编写和收集开源数据的测试Prompts,以及人工干预结合利用LLM强大的评估能力作为“共同评估者”。

LiveSum-TTT

Codes and Datasets for the Paper: Text-Tuple-Table: Towards Information Integration in Text-to-Table Generation via Global Tuple Extraction

Language:PythonLicense:MITStargazers:5Issues:1Issues:2