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asterhiredis

A seastar implement for redis client.

clash-for-linux-backup

Linux最完整的Clash for Linux的备份仓库，完全可以使用！由Yizuko进行修复及维护

deepray

Deepray for continuous integration development.

deepspeed

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

hierarchicalkv

HierarchicalKV is a part of NVIDIA Merlin and provides hierarchical key-value storage to meet RecSys requirements. The key capability of Merlin-KV is to store key-value feature-embeddings on high-bandwidth memory (HBM) of GPUs and in host memory. It also can be used as a generic key-value storage.

llama-alpa

A LLaMa pretrain code by using Alpa(https://github.com/alpa-projects/alpa).

llama-megatron

A LLaMA1/LLaMA12 Megatron implement.

ludo

meepoembedding

A distributed high-performance dynamic lookuptable-style Embedding designed for recommendation, search, CTR and advertising systems. Supports GPU, CPU, remote distributed KV (such as Redis), SSD, and other backends.

megatron-autockpt

A Megatron checkpoint auto-saving patch at the end of each iteration, inspired by Alibaba PAI EasyCkpt for Megatron.

megatron-lm

Ongoing research training transformer models at scale

nemo

NeMo: a toolkit for conversational AI

recommenders-addons

Additional utils and helpers to extend TensorFlow when build recommendation systems, contributed and maintained by SIG Recommenders.

resp3

RESP protocol V3 repository. Contains the specification, and other related resource

runtime

A performant and modular runtime for TensorFlow

tairhash

A redis module, similar to redis hash, but you can set expire and version for the field

transformerengine

A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper GPUs, to provide better performance with lower memory utilization in both training and inference.

transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

unit-scaling

A library for unit scaling in PyTorch