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Run GPU inference and training jobs on serverless infrastructure that scales with you.

Home Page: https://beam.cloud

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artificial-intelligence machine-learning python serverless cloud-computing cost-optimization data-science deep-learning distributed-computing gpu-acceleration gpu-computing hpc llm-serving llm-training ml-infrastructure mlops serverless-architectures

get-beam's Introduction

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Run GPU inference and training jobs on serverless infrastructure that scales with you

Get Started

The examples folder in this repo contains various examples of programs built with Beam.

You can run any of these examples yourself. All you need is a free account on Beam.

What can you do with Beam?

  • ๐Ÿ›ฐ Develop locally on remote hardware. Beam provides a brand new type of cloud development experience. You can write code on your laptop and execute it on cloud hardware immediately, with lightning fast build times.
  • ๐Ÿ“ฆ Instantly containerize any Python function and run it on a GPU. Configure your runtime in Python - tell us how many GPUs you need and which libraries you want installed, and Beam will spawn a remote environment for you.
  • ๐Ÿš€ Deploy apps as serverless functions. Deploy your apps as serverless REST APIs, scheduled cron jobs, or task queues - all with just a single line of Python. It's great for deploying LangChain apps, Stable Diffusion APIs, or Dreambooth.
  • โฐ Run scheduled jobs. You can run any code on a schedule, and do things like train machine learning models and setup data pipelines on S3 buckets.
  • ๐Ÿ—‚๏ธ Mount storage volumes. Read and write data to highly-performant distributed file systems.

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