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DeepSpeed MII download for Windows

Free download DeepSpeed MII Windows app to run online win Wine in Ubuntu online, Fedora online or Debian online

This is the Windows app named DeepSpeed MII whose latest release can be downloaded as DeepSpeedMIIv0.0.8.zip. It can be run online in the free hosting provider OnWorks for workstations.

Download and run online this app named DeepSpeed MII with OnWorks for free.

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Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.

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DeepSpeed MII


DESCRIPTION

MII makes low-latency and high-throughput inference possible, powered by DeepSpeed. The Deep Learning (DL) open-source community has seen tremendous growth in the last few months. Incredibly powerful text generation models such as the Bloom 176B, or image generation model such as Stable Diffusion are now available to anyone with access to a handful or even a single GPU through platforms such as Hugging Face. While open-sourcing has democratized access to AI capabilities, their application is still restricted by two critical factors: inference latency and cost. DeepSpeed-MII is a new open-source python library from DeepSpeed, aimed towards making low-latency, low-cost inference of powerful models not only feasible but also easily accessible. MII offers access to the highly optimized implementation of thousands of widely used DL models. MII-supported models achieve significantly lower latency and cost compared to their original implementation.



Features

  • MII offers access to highly optimized implementation of thousands of widely used DL models
  • MII supported models achieve significantly lower latency and cost compared to their original implementation
  • MII leverages an extensive set of optimizations from DeepSpeed-Inference such as deepfusion for transformers
  • State-of-the-art performance
  • MII supports low-cost deployment of these models both on-premises and on Azure via AML with just a few lines of codes
  • Automated tensor-slicing for multi-GPU inference, on-the-fly quantization with ZeroQuant


Programming Language

Python


Categories

Deep Learning Frameworks

This is an application that can also be fetched from https://sourceforge.net/projects/deepspeed-mii.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.


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