zhoushewei

Awesome-Code-LLM

A curated list of language modeling researches for code and related datasets.

bert4keras

keras implement of transformers for humans

ultralytics

NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite

ijepa

Official codebase for I-JEPA, the Image-based Joint-Embedding Predictive Architecture. First outlined in the CVPR paper, "Self-supervised learning from images with a joint-embedding predictive architecture."

yolov5

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

dockerfiles

Various Dockerfiles I use on the desktop and on servers.

open-chatgpt

The open source implementation of chatgpt and RLHF. 从0开始实现一个ChatGPT.

Sketch2Code_Python

Sketch2Code with python implementation

linux

Linux kernel source tree

transformers_tasks

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

visual-chatgpt

Official repo for the paper: Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation Models

unilm

Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities

ChineseNMT

ChineseNMT: Translate English to Chinese with PyTorch Implementation of Transformer

deep-learning-for-image-processing

deep learning for image processing including classification and object-detection etc.

nanoGPT

The simplest, fastest repository for training/finetuning medium-sized GPTs.

awesome-chatgpt-prompts

This repo includes ChatGPT prompt curation to use ChatGPT better.

BERT-pytorch

Google AI 2018 BERT pytorch implementation

freeCodeCamp

freeCodeCamp.org's open-source codebase and curriculum. Learn to code for free.

gpt-2

Code for the paper "Language Models are Unsupervised Multitask Learners"

GPT2-Chinese

Chinese version of GPT2 training code, using BERT tokenizer.

NLP_ability

总结梳理自然语言处理工程师(NLP)需要积累的各方面知识，包括面试题，各种基础知识，工程能力等等，提升核心竞争力

DeepLearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06

bert_seq2seq

pytorch实现 Bert 做seq2seq任务，使用unilm方案,现在也可以做自动摘要，文本分类，情感分析，NER，词性标注等任务,支持t5模型，支持GPT2进行文章续写。

Screenshot-to-code

A neural network that transforms a design mock-up into a static website.

faster-rcnn.pytorch

A faster pytorch implementation of faster r-cnn

Unilm-1

PrefixTuning

Prefix-Tuning: Optimizing Continuous Prompts for Generation