kaimary,kaimary,github

30-days-of-python

30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw

auto-gpt

An experimental open-source attempt to make GPT-4 fully autonomous.

awesome-database-testing

数据库测试资料 This repo is a collection of resources on testing database systems

awesome-nlp-research

awesome-rl

Reinforcement learning resources curated

bertviz

Tool for visualizing attention in the Transformer model (BERT, GPT-2, Albert, XLNet, RoBERTa, CTRL, etc.)

chinese-llama-alpaca

中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs)

codes

The source code of CodeS (SIGMOD 2024).

confidence

crossfit

Code for paper "CrossFit :weight_lifting:: A Few-shot Learning Challenge for Cross-task Generalization in NLP" (https://arxiv.org/abs/2104.08835)

cyclesql

Closing the Feedback Loop: Improving Natural Language to SQL Translation Using Natural Language Explanations

damo-convai

DAMO-ConvAI: The official repository which contains the codebase for Alibaba DAMO Conversational AI.

data_preprocessing

db-gpt

Revolutionizing Database Interactions with Private LLM Technology

deepspeed

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

evaporate

This repo contains data and code for the paper "Language Models Enable Simple Systems for Generating Structured Views of Heterogeneous Data Lakes"

fairseq

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

ganhacks

starter from "How to Train a GAN?" at NIPS2016

gap-text2sql

GAP-text2SQL: Learning Contextual Representations for Semantic Parsing with Generation-Augmented Pre-Training

gar

ICDE 2023 Paper, GAR: A Generate-and-Rank Approach for Natural Language to SQL Translation

google-research

Google Research

hands-on-meta-learning-with-python

Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow

howtotrainyourmamlpytorch

The original code for the paper "How to train your MAML" along with a replication of the original "Model Agnostic Meta Learning" (MAML) paper in Pytorch.