hanlinxuy's Stars
QSCTech/zju-icicles
浙江大学课程攻略共享计划
HigherOrderCO/Bend
A massively parallel, high-level programming language
lltcggie/waifu2x-caffe
waifu2xのCaffe版
Buuntu/fastapi-react
🚀 Cookiecutter Template for FastAPI + React Projects. Using PostgreSQL, SQLAlchemy, and Docker
sustcsonglin/flash-linear-attention
Efficient implementations of state-of-the-art linear attention models in Pytorch and Triton
Event-AHU/Mamba_State_Space_Model_Paper_List
[Mamba-Survey-2024] Paper list for State-Space-Model/Mamba and it's Applications
princeton-nlp/LLM-Shearing
[ICLR 2024] Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning
wolfparticle/machineLearningDeepLearning
李宏毅2021机器学习深度学习笔记PPT作业
Ai00-X/ai00_server
The all-in-one RWKV runtime box with embed, RAG, AI agents, and more.
Leeroo-AI/mergoo
A library for easily merging multiple LLM experts, and efficiently train the merged LLM.
Cornell-RelaxML/QuIP
Code for paper: "QuIP: 2-Bit Quantization of Large Language Models With Guarantees"
FlagOpen/FlagGems
FlagGems is an operator library for large language models implemented in Triton Language.
cryscan/web-rwkv
Implementation of the RWKV language model in pure WebGPU/Rust.
FasterDecoding/SnapKV
RWKV/RWKV-infctx-trainer
RWKV infctx trainer, for training arbitary context sizes, to 10k and beyond!
jshuadvd/LongRoPE
Implementation of the LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens Paper
neromous/RWKV-Ouroboros
This project is established for real-time training of the RWKV model.
LuJunru/MemoChat
MemoChat: Tuning LLMs to Use Memos for Consistent Long-Range Open-Domain Conversation
radarFudan/mamba
Dan-wanna-M/bnf_sampler
StarRing2022/RingRWKV
修复Transformer官方库中RWKV的适配问题,支持RWKV所有系列模型在转换后,通过RingRWKV库,与其他transfomer模型一样简单方便地部署和微调。
fsndzomga/rag-fastapi
A simple implementation of RAG (Retrieval Augmented Generation) using fastapi and postgreSQL
hanlinxuy/RWKV-LM
RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.