Colin Taylor
colin2328
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A high-throughput and memory-efficient inference and serving engine for LLMs
TorchX is a universal job launcher for PyTorch applications. TorchX is designed to have fast iteration time for training/research and support for E2E production ML pipelines when you're ready.
Pytorch domain library for recommendation systems
A performant, memory-efficient checkpointing library for PyTorch applications, designed with large, complex distributed workloads in mind.
Config files for my GitHub profile.
Repositories
31A high-throughput and memory-efficient inference and serving engine for LLMs
TorchX is a universal job launcher for PyTorch applications. TorchX is designed to have fast iteration time for training/research and support for E2E production ML pipelines when you're ready.
Pytorch domain library for recommendation systems
A performant, memory-efficient checkpointing library for PyTorch applications, designed with large, complex distributed workloads in mind.
Config files for my GitHub profile.
PyTorch Single Controller
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Data manipulation and transformation for audio signal processing, powered by PyTorch
FB (Facebook) + GEMM (General Matrix-Matrix Multiplication) - https://code.fb.com/ml-applications/fbgemm/
An implementation of a deep learning recommendation model (DLRM)
TorchBench is a collection of open source benchmarks used to evaluate PyTorch performance.
Recipes are a standard, well supported set of blueprints for machine learning engineers to rapidly train models using the latest research techniques without significant engineering overhead.Specifically, recipes aims to provide- Consistent access to pre-trained SOTA models ready for production- Reference implementations for SOTA research reproducibility, and infrastructure to guarantee correctness, efficiency, and interoperability.
PyTorch tutorials.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
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