{"id":13632807,"url":"https://github.com/slai-labs/get-beam","last_synced_at":"2025-04-18T05:33:20.248Z","repository":{"id":61817256,"uuid":"553885657","full_name":"slai-labs/get-beam","owner":"slai-labs","description":"Run GPU inference and training jobs on serverless infrastructure that scales with you.","archived":false,"fork":false,"pushed_at":"2024-05-20T21:29:38.000Z","size":6237,"stargazers_count":89,"open_issues_count":1,"forks_count":20,"subscribers_count":3,"default_branch":"main","last_synced_at":"2024-05-21T00:10:55.693Z","etag":null,"topics":["artificial-intelligence","cloud-computing","cost-optimization","data-science","deep-learning","distributed-computing","gpu-acceleration","gpu-computing","hpc","llm-serving","llm-training","machine-learning","ml-infrastructure","mlops","python","serverless","serverless-architectures"],"latest_commit_sha":null,"homepage":"https://beam.cloud","language":"Shell","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/slai-labs.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2022-10-18T23:35:11.000Z","updated_at":"2024-05-29T23:24:01.932Z","dependencies_parsed_at":"2023-10-21T00:23:02.201Z","dependency_job_id":"847df8b0-94a6-4322-b2c3-638e6bcea78a","html_url":"https://github.com/slai-labs/get-beam","commit_stats":null,"previous_names":[],"tags_count":101,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/slai-labs%2Fget-beam","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/slai-labs%2Fget-beam/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/slai-labs%2Fget-beam/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/slai-labs%2Fget-beam/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/slai-labs","download_url":"https://codeload.github.com/slai-labs/get-beam/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":249437005,"owners_count":21271986,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["artificial-intelligence","cloud-computing","cost-optimization","data-science","deep-learning","distributed-computing","gpu-acceleration","gpu-computing","hpc","llm-serving","llm-training","machine-learning","ml-infrastructure","mlops","python","serverless","serverless-architectures"],"created_at":"2024-08-01T22:03:16.207Z","updated_at":"2025-04-18T05:33:19.374Z","avatar_url":"https://github.com/slai-labs.png","language":"Shell","funding_links":[],"categories":["Shell"],"sub_categories":[],"readme":"\u003cp align=\"center\"\u003e\n\u003cimg alt=\"Logo\" src=\"https://slai-demo-datasets.s3.amazonaws.com/beam-banner.svg\"/ width=\"500\"\u003e\n\u003c/p\u003e\n\n\u003ch4 align=\"center\"\u003e\nRun GPU inference and training jobs on serverless infrastructure that scales with you\n\u003c/h4\u003e\n\n\u003cp align=\"center\"\u003e\n\u003ca href=\"https://join.slack.com/t/beam-89x5025/shared_invite/zt-1ye1jzgg2-cGpMKuoXZJiT3oSzgPmN8g\"\u003e\u003cimg src=\"https://img.shields.io/badge/join-Slack-yellow\"/\u003e\u003c/a\u003e\n\u003ca href=\"https://docs.beam.cloud\"\u003e\u003cimg src=\"https://img.shields.io/badge/docs-quickstart-blue\"/\u003e\u003c/a\u003e\n\n\n# Get Started\n\nThe `examples` folder in this repo contains various examples of programs built with Beam. \n\nYou can run any of these examples yourself. All you need is a free account on [Beam](https://beam.cloud).\n\n# What can you do with Beam?\n\n* 🛰 **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.\n* 📦 **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.\n* 🚀 **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](https://docs.beam.cloud/examples/langchain) apps, [Stable Diffusion APIs](https://docs.beam.cloud/examples/stable-diffusion-gpu), or [Dreambooth](https://docs.beam.cloud/examples/dreambooth).\n* ⏰ **Run scheduled jobs**. You can run any code on a schedule, and do things like [train machine learning models](https://docs.beam.cloud/examples/recommendation-system) and setup [data pipelines on S3 buckets](https://docs.beam.cloud/examples/s3-schedule).\n* 🗂️ **Mount storage volumes**. Read and write data to highly-performant distributed file systems.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fslai-labs%2Fget-beam","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fslai-labs%2Fget-beam","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fslai-labs%2Fget-beam/lists"}