lisheng89

lisheng89's Stars

• karpathy/LLM101n

  LLM101n: Let's build a Storyteller

  25.6k1.4k

• facebookresearch/schedule_free

  Schedule-Free Optimization in PyTorch

  Language:Python1.7k55

• mistralai/mistral-inference

  Official inference library for Mistral models

  Language:Jupyter Notebook9.3k817

• google/cityhash

  Automatically exported from code.google.com/p/cityhash

  Language:Shell1.1k178

• naklecha/llama3-from-scratch

  llama3 implementation one matrix multiplication at a time

  Language:Jupyter Notebook11.5k872

• ml-explore/mlx

  MLX: An array framework for Apple silicon

  Language:C++16k908

• nyonicai/nyonic-public

  Reference implementation of models from Nyonic Model Factory

  Language:Python11

• karpathy/minbpe

  Minimal, clean code for the Byte Pair Encoding (BPE) algorithm commonly used in LLM tokenization.

  Language:Python8.8k803

• openai/tiktoken

  tiktoken is a fast BPE tokeniser for use with OpenAI's models.

  Language:Python11.3k766

• shenweichen/DeepCTR

  Easy-to-use,Modular and Extendible package of deep-learning based CTR models .

  Language:Python7.5k2.2k

• torvalds/linux

  Linux kernel source tree

  Language:C175k52.7k

• huangzworks/redis-3.0-annotated

  带有详细注释的 Redis 3.0 代码（annotated Redis 3.0 source code）。

  Language:C10k4.2k

• Coobiw/MPP-LLaVA

  Personal Project: MPP-Qwen14B & MPP-Qwen-Next(Multimodal Pipeline Parallel based on Qwen-LM). Support [video/image/multi-image] {sft/conversations}. Don't let the poverty limit your imagination! Train your own 8B/14B LLaVA-training-like MLLM on RTX3090/4090 24GB.

  Language:Jupyter Notebook31716

• mlfoundations/open_clip

  An open source implementation of CLIP.

  Language:Python9.3k930

• facebookresearch/moco

  PyTorch implementation of MoCo: https://arxiv.org/abs/1911.05722

  4.7k774

• meta-llama/llama-recipes

  Scripts for fine-tuning Meta Llama3 with composable FSDP & PEFT methods to cover single/multi-node GPUs. Supports default & custom datasets for applications such as summarization and Q&A. Supporting a number of candid inference solutions such as HF TGI, VLLM for local or cloud deployment. Demo apps to showcase Meta Llama3 for WhatsApp & Messenger.

  Language:Jupyter Notebook10.8k1.5k

• hongleizhang/RSPapers

  A Curated List of Must-read Papers on Recommender System.

  6k1.3k

• geekan/HowToLiveLonger

  程序员延寿指南 | A programmer's guide to live longer

  29.6k2.1k

• geekan/MetaGPT

  🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming

  Language:Python41.9k5k

• PersiaML/PERSIA

  High performance distributed framework for training deep learning recommendation models based on PyTorch.

  Language:Rust39252

• google/flatbuffers

  FlatBuffers: Memory Efficient Serialization Library

  Language:C++22.6k3.2k

• sparsehash/sparsehash

  C++ associative containers

  Language:C++1.5k255

• etcd-io/etcd

  Distributed reliable key-value store for the most critical data of a distributed system

  Language:Go46.9k9.7k

• bytedance/ByteTransformer

  optimized BERT transformer inference on NVIDIA GPU. https://arxiv.org/abs/2210.03052

  Language:C++44233

• wangshusen/DRL

  Deep Reinforcement Learning

  3.1k552

• wangshusen/SearchEngine

  搜索引擎原理

  1.3k105

• wangshusen/RecommenderSystem

  2k310

• pinterest/transformer_user_action

  Transformer-based Realtime User Action Model for Recommendation at Pinterest

  Language:Python458

• skywind3000/asynctasks.vim

  :rocket: Modern Task System for Project Building, Testing and Deploying !!

  Language:Vim Script90229

• guyulongcs/Awesome-Deep-Learning-Papers-for-Search-Recommendation-Advertising

  Awesome Deep Learning papers for industrial Search, Recommendation and Advertising. They focus on Embedding, Matching, Ranking (CTR and CVR prediction), Post Ranking, Multi-task Learning, Graph Neural Networks, Transfer Learning, Reinforcement Learning, Self-supervised Learning and so on.

  Language:Python1.4k215