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verl/HybridFlow: A Flexible and Efficient RL Post-Training Framework
SGLang is a high-performance serving framework for large language models and multimodal models.
Chronos: Pretrained Models for Time Series Forecasting
CUDA Templates and Python DSLs for High-Performance Linear Algebra
Multi-LoRA inference server that scales to 1000s of fine-tuned LLMs
Medusa: Simple Framework for Accelerating LLM Generation with Multiple Decoding Heads
Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"
TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. Tensor…
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
The simplest, fastest repository for training/finetuning medium-sized GPTs.
DeepRec is a high-performance recommendation deep learning framework based on TensorFlow. It is hosted in incubation in LF AI & Data Foundation.
Easy Parallel Library (EPL) is a general and efficient deep learning framework for distributed model training.
BladeDISC is an end-to-end DynamIc Shape Compiler project for machine learning workloads.
apeforest / incubator-mxnet
Forked from apache/mxnetLightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Public repo for DeepLearning.AI MLEP Specialization
Unified Interface for Constructing and Managing Workflows on different workflow engines, such as Argo Workflows, Tekton Pipelines, and Apache Airflow.
An Engine-Agnostic Deep Learning Framework in Java
apeforest / horovod
Forked from horovod/horovodDistributed training framework for TensorFlow, Keras, and PyTorch.
A Low Power Finite State Machine Encoding Package for Sequential Logic Synthesis
Introduction to deep learning with Apache MXNet GLUON. MLP, CNN, RNN and Model Server
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more