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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
ClearML Agent - MLOps/LLMOps made easy. MLOps/LLMOps scheduler & orchestration solution
| Date | Stars |
|---|---|
| 2026-07-31 | 308 |
| 2026-08-06 | 308 |
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<div align="center"> <img src="https://github.com/clearml/clearml-agent/blob/master/docs/clearml_agent_logo.png?raw=true" width="250px"> **ClearML Agent - MLOps/LLMOps made easy MLOps/LLMOps scheduler & orchestration solution supporting Linux, macOS and Windows** [](https://img.shields.io/github/license/clearml/clearml-agent.svg) [](https://img.shields.io/pypi/pyversions/clearml-agent.svg) [](https://img.shields.io/pypi/v/clearml-agent.svg) [](https://pypi.org/project/clearml-agent/) [](https://artifacthub.io/packages/search?repo=clearml) `🌟 ClearML is open-source - Leave a star to support the project! 🌟` </div> --- ### ⚡ [ClearML Agent Bootstrap](https://github.com/clearml/clearml-agent#clearml-agent-bootstrap) Boot agents up to 10x faster with rock-solid stability — git, git-lfs, agent, ssh and UV come precompiled for x86/arm in a single self-contained bootstrap, so there's nothing to install at runtime. --- ### ClearML-Agent * Run jobs (experiments) on any local or cloud based resource * Implement optimized resource utilization policies * Deploy execution environments with either virtualenv or fully docker containerized with zero effort * Launch-and-Forget service containers * [Cloud autoscaling](https://clear.ml/docs/latest/docs/guides/services/aws_autoscaler) * [Customizable cleanup](https://clear.ml/docs/latest/docs/guides/services/cleanup_service) * Advanced [pipeline building and execution](https://clear.ml/docs/latest/docs/guides/frameworks/pytorch/notebooks/table/tabular_training_pipeline) It is a zero configuration fire-and-forget execution agent, providing a full ML/DL cluster solution. **Full Automation in 5 steps** 1. ClearML Server [self-hosted](https://github.com/clearml/clearml-server) or [free tier hosting](https://app.clear.ml) 2. `pip install clearml-agent` ([install](#installing-the-clearml-agent) the ClearML Agent on any GPU machine: on-premises / cloud / ...) 3. Create a [job](https://clear.ml/docs/latest/docs/apps/clearml_task) or add [ClearML](https://github.com/clearml/clearml) to your code with just 2 lines of code 4. Change the [parameters](#using-the-clearml-agent) in the UI & schedule for [execution](#using-the-clearml-agent) (or automate with a [pipeline](#orchestration-pipes)) 5. :chart_with_downwards_trend: :chart_with_upwards_trend: :eyes: :beer: "All the Deep/Machine-Learning DevOps your research needs, and then some... Because ain't nobody got time for that" **Try ClearML now** [Self Hosted](https://github.com/clearml/clearml-server) or [Free tier Hosting](https://app.clear.ml) <a href="https://app.clear.ml"><img src="https://github.com/clearml/clearml-agent/blob/master/docs/screenshots.gif?raw=true" width="100%"></a> ### Simple, Flexible Experiment Orchestration **The ClearML Agent was built to address the DL/ML R&D DevOps needs:** * Easily add & remove machines from the cluster * Reuse machines without the need for any dedicated containers or images * **Combine GPU resources across any cloud and on-prem** * **No need for yaml / json / template configuration of any kind** * **User friendly UI** * Manageable resource allocation that can be used by researchers and engineers * Flexible and controllable scheduler with priority support * Automatic instance spinning in the cloud **Using the ClearML Agent, you can now set up a dynamic cluster with \*epsilon DevOps** *epsilon - Because we are :triangular_ruler: and nothing is really zero work ### Kubernetes Integration (Optional) We think Kubernetes is awesome, but it is not a must to get started with remote execution age
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:d287f82b21d37ab8, topic:mlops, topic:llmops, desc:mlops
matched fp:d287f82b21d37ab8, topic:gpu, topic:kubernetes