From 9fa8d7264016ac06a0eebb89f43cfe70428ee4bd Mon Sep 17 00:00:00 2001 From: clearml <> Date: Mon, 13 Jan 2025 18:36:16 +0200 Subject: [PATCH] Update github repo link --- LICENSE | 2 +- README.md | 34 +++++++++++++++++----------------- setup.py | 4 ++-- 3 files changed, 20 insertions(+), 20 deletions(-) diff --git a/LICENSE b/LICENSE index ec79a07..9700080 100644 --- a/LICENSE +++ b/LICENSE @@ -186,7 +186,7 @@ same "printed page" as the copyright notice for easier identification within third-party archives. - Copyright 2019 allegro.ai + Copyright 2025 ClearML Inc Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. diff --git a/README.md b/README.md index 4e2ee00..6b2956c 100644 --- a/README.md +++ b/README.md @@ -1,15 +1,15 @@
- + **ClearML Agent - MLOps/LLMOps made easy MLOps/LLMOps scheduler & orchestration solution supporting Linux, macOS and Windows** -[![GitHub license](https://img.shields.io/github/license/allegroai/clearml-agent.svg)](https://img.shields.io/github/license/allegroai/clearml-agent.svg) +[![GitHub license](https://img.shields.io/github/license/clearml/clearml-agent.svg)](https://img.shields.io/github/license/clearml/clearml-agent.svg) [![PyPI pyversions](https://img.shields.io/pypi/pyversions/clearml-agent.svg)](https://img.shields.io/pypi/pyversions/clearml-agent.svg) [![PyPI version shields.io](https://img.shields.io/pypi/v/clearml-agent.svg)](https://img.shields.io/pypi/v/clearml-agent.svg) [![PyPI Downloads](https://pepy.tech/badge/clearml-agent/month)](https://pypi.org/project/clearml-agent/) -[![Artifact Hub](https://img.shields.io/endpoint?url=https://artifacthub.io/badge/repository/allegroai)](https://artifacthub.io/packages/search?repo=allegroai) +[![Artifact Hub](https://img.shields.io/endpoint?url=https://artifacthub.io/badge/repository/clearml)](https://artifacthub.io/packages/search?repo=clearml) `🌟 ClearML is open-source - Leave a star to support the project! 🌟` @@ -33,21 +33,21 @@ It is a zero configuration fire-and-forget execution agent, providing a full ML/ **Full Automation in 5 steps** -1. ClearML Server [self-hosted](https://github.com/allegroai/clearml-server) +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/allegroai/clearml) to your code with just 2 lines of code + 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 an [AutoML pipeline](#automl-and-orchestration-pipelines-)) 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/allegroai/clearml-server) +**Try ClearML now** [Self Hosted](https://github.com/clearml/clearml-server) or [Free tier Hosting](https://app.clear.ml) - + ### Simple, Flexible Experiment Orchestration @@ -71,7 +71,7 @@ or [Free tier Hosting](https://app.clear.ml) We think Kubernetes is awesome, but it is not a must to get started with remote execution agents and cluster management. We designed `clearml-agent` so you can run both bare-metal and on top of Kubernetes, in any combination that fits your environment. -You can find the Dockerfiles in the [docker folder](./docker) and the helm Chart in https://github.com/allegroai/clearml-helm-charts +You can find the Dockerfiles in the [docker folder](./docker) and the helm Chart in https://github.com/clearml/clearml-helm-charts #### Benefits of integrating existing Kubernetes cluster with ClearML @@ -86,8 +86,8 @@ You can find the Dockerfiles in the [docker folder](./docker) and the helm Chart - **Enterprise Features**: RBAC, vault, multi-tenancy, scheduler, quota management, fractional GPU support **Run the agent in Kubernetes Glue mode an map ClearML jobs directly to K8s jobs:** -- Use the [ClearML Agent Helm Chart](https://github.com/allegroai/clearml-helm-charts/tree/main/charts/clearml-agent) to spin an agent pod acting as a controller - - Or run the [clearml-k8s glue](https://github.com/allegroai/clearml-agent/blob/master/examples/k8s_glue_example.py) on +- Use the [ClearML Agent Helm Chart](https://github.com/clearml/clearml-helm-charts/tree/main/charts/clearml-agent) to spin an agent pod acting as a controller + - Or run the [clearml-k8s glue](https://github.com/clearml/clearml-agent/blob/master/examples/k8s_glue_example.py) on a Kubernetes cpu node - The clearml-k8s glue pulls jobs from the ClearML job execution queue and prepares a Kubernetes job (based on provided yaml template) @@ -151,7 +151,7 @@ The ClearML Agent executes experiments using the following process: #### System Design & Flow -clearml-architecture +clearml-architecture #### Installing the ClearML Agent @@ -279,7 +279,7 @@ clearml-agent daemon --detached --gpus 0 --queue default --docker nvidia/cuda:11 ### How do I create an experiment on the ClearML Server? -* Integrate [ClearML](https://github.com/allegroai/clearml) with your code +* Integrate [ClearML](https://github.com/clearml/clearml) with your code * Execute the code on your machine (Manually / PyCharm / Jupyter Notebook) * As your code is running, **ClearML** creates an experiment logging all the necessary execution information: - Git repository link and commit ID (or an entire jupyter notebook) @@ -326,21 +326,21 @@ The ClearML Agent can also be used to implement AutoML orchestration and Experim ClearML package. Sample AutoML & Orchestration examples can be found in the -ClearML [example/automation](https://github.com/allegroai/clearml/tree/master/examples/automation) folder. +ClearML [example/automation](https://github.com/clearml/clearml/tree/master/examples/automation) folder. AutoML examples: -- [Toy Keras training experiment](https://github.com/allegroai/clearml/blob/master/examples/optimization/hyper-parameter-optimization/base_template_keras_simple.py) +- [Toy Keras training experiment](https://github.com/clearml/clearml/blob/master/examples/optimization/hyper-parameter-optimization/base_template_keras_simple.py) - In order to create an experiment-template in the system, this code must be executed once manually -- [Random Search over the above Keras experiment-template](https://github.com/allegroai/clearml/blob/master/examples/automation/manual_random_param_search_example.py) +- [Random Search over the above Keras experiment-template](https://github.com/clearml/clearml/blob/master/examples/automation/manual_random_param_search_example.py) - This example will create multiple copies of the Keras experiment-template, with different hyperparameter combinations Experiment Pipeline examples: -- [First step experiment](https://github.com/allegroai/clearml/blob/master/examples/automation/task_piping_example.py) +- [First step experiment](https://github.com/clearml/clearml/blob/master/examples/automation/task_piping_example.py) - This example will "process data", and once done, will launch a copy of the 'second step' experiment-template -- [Second step experiment](https://github.com/allegroai/clearml/blob/master/examples/automation/toy_base_task.py) +- [Second step experiment](https://github.com/clearml/clearml/blob/master/examples/automation/toy_base_task.py) - In order to create an experiment-template in the system, this code must be executed once manually ### License diff --git a/setup.py b/setup.py index 411ec39..be50ee3 100644 --- a/setup.py +++ b/setup.py @@ -1,7 +1,7 @@ """ ClearML Inc. CLEARML-AGENT DevOps for machine/deep learning -https://github.com/allegroai/clearml-agent +https://github.com/clearml/clearml-agent """ import os.path @@ -39,7 +39,7 @@ setup( long_description=long_description, long_description_content_type='text/markdown', # The project's main homepage. - url='https://github.com/allegroai/clearml-agent', + url='https://github.com/clearml/clearml-agent', author='clearml', author_email='clearml@clearml.ai', license='Apache License 2.0',