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AIGC-progress

Follow the rapid development of AIGC models and applications. | 跟上AIGC模型和应用快速发展的步伐 🚀

ChineseGLUE-AutoFinetune

bert

TensorFlow code and pre-trained models for BERT

book

Deep Learning 101 with PaddlePaddle （『飞桨』深度学习框架入门教程）

ChatGLM-Tuning

一种平价的chatgpt实现方案, 基于ChatGLM-6B + LoRA

Chinese-BERT-wwm

Pre-Training with Whole Word Masking for Chinese BERT（中文BERT-wwm系列模型）

Chinese-ELECTRA

Pre-trained Chinese ELECTRA（中文ELECTRA预训练模型）

cloud

PaddleCloud distributed training job scheduling

DDParser

百度开源的依存句法分析系统

deep-learning-coursera

Deep Learning Specialization by Andrew Ng on Coursera.

Deep-Learning-Coursera-1

Deep Learning Specialization by Andrew Ng, deeplearning.ai.

DeepSpeech

A PaddlePaddle implementation of DeepSpeech2 architecture for ASR.

EasyRec

A framework for large scale recommendation algorithms.

ERNIE

An Implementation of ERNIE For Language Understanding (including Pre-training models and Fine-tuning tools)

FluidDoc

Documentations for PaddlePaddle

HubModule

Module repo of PaddleHub

interview_python

关于Python的面试题

LLaMA-Efficient-Tuning

Easy-to-use LLM fine-tuning framework (LLaMA-2, BLOOM, Falcon, Baichuan, Qwen, ChatGLM2)

lstm-crf-pytorch

LSTM-CRF in PyTorch

machine-reading-comprehension

MedicalGPT

MedicalGPT: Training Your Own Medical GPT Model with ChatGPT Training Pipeline. 训练医疗大模型，实现了包括增量预训练、有监督微调、RLHF(奖励建模、强化学习训练)和DPO(直接偏好优化)。

models

Pre-trained and Reproduced Deep Learning Models （『飞桨』官方模型库，包含多种学术前沿和工业场景验证的深度学习模型）

Paddle

PArallel Distributed Deep LEarning （『飞桨』核心框架，高性能单机、分布式训练和跨平台部署）

PaddleCraft

Take neural networks as APIs for human-like AI.

PaddleHub

A toolkit for managing pretrained models of PaddlePaddle and helping user getting started with transfer learning more efficiently. （『飞桨』预训练模型管理和迁移学习工具 ）

PaddleNLP

NLP Core Library and Model Zoo based on PaddlePaddle 2.0

PRMLT

Matlab code for algorithms in PRML book

R-Net

Tensorflow Implementation of R-Net

SEASS

Code for the ACL 2017 paper "Selective Encoding for Abstractive Sentence Summarization"

SEASS-pytorch

Pytorch implementation for paper "Selective Encoding for Abstractive Sentence Summarization"