9yc

9yc's Stars

• azl397985856/leetcode

  LeetCode Solutions: A Record of My Problem Solving Journey.( leetcode题解，记录自己的leetcode解题之路。)

  Language:JavaScript54.7k1.3k2559.5k

• youngyangyang04/leetcode-master

  《代码随想录》LeetCode 刷题攻略：200道经典题目刷题顺序，共60w字的详细图解，视频难点剖析，50余张思维导图，支持C++，Java，Python，Go，JavaScript等多语言版本，从此算法学习不再迷茫！🔥🔥 来看看，你会发现相见恨晚！🚀

  Language:Shell51.6k38223911.5k

• vllm-project/vllm

  A high-throughput and memory-efficient inference and serving engine for LLMs

  Language:Python29.4k2445.1k4.4k

• huggingface/peft

  🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

  Language:Python16.3k1101.1k1.6k

• EleutherAI/lm-evaluation-harness

  A framework for few-shot evaluation of language models.

  Language:Python6.8k381.1k1.8k

• MegEngine/MegEngine

  MegEngine 是一个快速、可拓展、易于使用且支持自动求导的深度学习框架

  Language:C++4.8k137371540

• stanford-crfm/helm

  Holistic Evaluation of Language Models (HELM), a framework to increase the transparency of language models (https://arxiv.org/abs/2211.09110). This framework is also used to evaluate text-to-image models in HEIM (https://arxiv.org/abs/2311.04287) and vision-language models in VHELM (https://arxiv.org/abs/2410.07112).

  Language:Python1.9k351.1k245

• flexflow/FlexFlow

  FlexFlow Serve: Low-Latency, High-Performance LLM Serving

  Language:C++1.7k32659225

• kuleshov/minillm

  MiniLLM is a minimal system for running modern LLMs on consumer-grade GPUs

  Language:Python863151352

• Lyken17/pytorch-memonger

  Sublinear memory optimization for deep learning. https://arxiv.org/abs/1604.06174

  Language:Python58910954

• mallorbc/Finetune_LLMs

  Repo for fine-tuning Casual LLMs

  Language:Python448102084

• mit-han-lab/tiny-training

  On-Device Training Under 256KB Memory [NeurIPS'22]

  Language:Python43718860

• amirgholami/ai_and_memory_wall

  AI and Memory Wall

  2053425

• yxli2123/LoftQ

  Language:Python19743718

• ShishirPatil/poet

  ML model training for edge devices

  Language:Python15811418

• uwsampl/dtr-prototype

  Dynamic Tensor Rematerialization prototype (modified PyTorch) and simulator. Paper: https://arxiv.org/abs/2006.09616

  Language:Python12912416

• ssbuild/llm_finetuning

  Large language Model fintuning bloom , opt , gpt, gpt2 ,llama,llama-2,cpmant and so on

  Language:Python962812

• pittisl/Generative-AI-Tutorial

  A subjective learning guide for generative AI research

  683010

• longtanle/awesome-federated-LLM-learning

  This is a collection of research papers for Federated Learning for Large Language Models (FedLLM). And the repository will be continuously updated to track the frontier of FedLLM.

  64200

• bibikar/feddst

  Federated Dynamic Sparse Training

  Language:Python302311

• BaohaoLiao/mefts

  [NeurIPS 2023] Make Your Pre-trained Model Reversible: From Parameter to Memory Efficient Fine-Tuning

  Language:Python29301

• theyoungkwon/TinyTrain

  The official implementation of TinyTrain [ICML '24]

  20322

• taehokim20/LLMem

  LLMem: GPU Memory Estimation for Fine-Tuning Pre-Trained LLMs

  Language:Python15202

• pittisl/GreenTrainer

  Code for paper "Towards Green AI in Fine-tuning Large Language Models via Adaptive Backpropagation" (ICLR'24)

  Language:Python112

• TonyTangYu/pytorch

  DELTA-pytorch：DELTA: Dynamically Optimizing GPU Memory beyond Tensor Recomputation

  Language:C++10503

• zhenqincn/FedAPEN

  This repository contains the official implementation of the paper entitled with "FedAPEN: Personalized Cross-silo Federated Learning with Adaptability to Statistical Heterogeneity".

  Language:Python10223

• ChanYunHin/InCo-Aggregation

  The official source codes of ICLR2024 paper, "Internal Cross-layer Gradients for Extending Homogeneity to Heterogeneity in Federated Learning".

  Language:Python7111

• tianlwang/eval_gsm8k

  Language:Python6100

• uwsampl/dtr

  Dynamic Tensor Rematerialization

  61040

• pittisl/FL-with-intertwined-heterogeneity

  Language:Python2100