yichenchou's Stars
aceliuchanghong/FAQ_Of_LLM_Interview
大模型算法岗面试题(含答案):常见问题和概念解析 "大模型面试题"、"算法岗面试"、"面试常见问题"、"大模型算法面试"、"大模型应用基础"
luckzack/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
hiyouga/LLaMA-Factory
Unified Efficient Fine-Tuning of 100+ LLMs (ACL 2024)
gouqi666/RAST
zpqiu/EDGE
Source code for "Automatic Distractor Generation for Multiple Choice Questions in Standard Tests"
shibing624/text2vec
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。
liucongg/ChatGLM-Finetuning
基于ChatGLM-6B、ChatGLM2-6B、ChatGLM3-6B模型,进行下游具体任务微调,涉及Freeze、Lora、P-tuning、全参微调等
hiyouga/ChatGLM-Efficient-Tuning
Fine-tuning ChatGLM-6B with PEFT | 基于 PEFT 的高效 ChatGLM 微调
voidful/BDG
Code for "A BERT-based Distractor Generation Scheme with Multi-tasking and Negative Answer Training Strategies."
patil-suraj/question_generation
Neural question generation using transformers
tangentor/SharedPrintingPlatformBackend
Printing platform for internal lab use with file sharing space, distributed document management and more
renatoviolin/Multiple-Choice-Question-Generation-T5-and-Text2Text
Question Generation using Google T5 and Text2Text
ramsrigouthamg/Questgen.ai
Question generation using state-of-the-art Natural Language Processing algorithms
KristiyanVachev/Leaf-Question-Generation
Easy to use and understand multiple-choice question generation algorithm using T5 Transformers.
minwhoo/CrossAug
Code for "CrossAug: A Contrastive Data Augmentation Method for Debiasing Fact Verification Models"
asahi417/lm-question-generation
Multilingual/multidomain question generation datasets, models, and python library for question generation.
lenve/vhr
微人事是一个前后端分离的人力资源管理系统,项目采用SpringBoot+Vue开发。
zhzhch335/todayMeal
今天吃什么,通过地图获得附近恰饭处来随机roll今天吃的东西
meghabyte/acl2021-education
Code for "Question Generation for Adaptive Education", to appear at ACL 2021.
ShuyangCao/open-ended_question_ontology
Code for ACL 2021 paper "Controllable Open-ended Question Generation with A New Question Type Ontology".
Olivia-fsm/P2MCQ
The codebase for NAACL-2022 special theme submission [Towards Process-Oriented, Modular, and Versatile Question Generation that Meets Educational Needs]
KristiyanVachev/Question-Generation
Generating multiple choice questions from text using Machine Learning.