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In this post, we will learn about a new cloud IDE that is free and easy to use. It is an improved version of Google Colab that allows you to save your projects, use essential plugins, and run generative models on GPU for free.
ai/” rel=”noopener” target=”_blank”>Lightning ai Study is a cloud-based ai development platform (similar to Google Colab) that aims to eliminate the hassle of setting up local environments for machine learning projects.
These are the key features of Lightning ai Studio:
- It integrates popular machine learning tools into a single interface, so there is no need to context switch between different tools. This makes it easier to build scalable ai applications and endpoints.
- No environment configuration required. You can code in the browser or connect your local IDE (VSCode or PyCharm). You can also easily switch between CPU and GPU without environment changes.
- Allows you to host and share ai applications created with Streamlit, Gradio, React JS, etc. It also allows multi-user collaboration by coding together.
- It provides unlimited storage and the ability to upload and share files, as well as connect S3 buckets.
- Allows you to train models on a massive scale using thousands of GPUs (paid option). You can run hyperparameter sweeps, data preprocessing, and model deployment in massively parallel.
- Offers a local development experience while leveraging the power of cloud infrastructure.
- Discover community templates (Studies) to quickly deploy, tune, and train models in your cloud with your data in minutes, with no configuration required.
Its Jupyter Notebook/VSCode cloud provides scalable hardware to train large language models and run fast inference.
You can create a free account at lightning.ai/sign-up. For instant verification, make sure you use an official company or .edu email. I signed up with the email @kdnuggets.com and got instant access.
Once you've created your account, follow a few simple steps to personalize your Studio experience. To get 7 hours of free GPU, you will need to verify your phone number.
Once you complete the initial steps, you will be directed to a sample project that includes a basic Python file. In just a few minutes, your Studio will be ready to process images and fine-tune the Renest model. To get started, simply write your code and run the file.
The user interface (UI) is quite similar to that of VSCode but with additional options available in the right panel.
The Lighting ai platform offers studies that are project templates designed by users. These templates include code, environment configuration, and data to help you get started with your project. You can find various studies on the platforms such as training templates, tuning, preprocessing, inference, and hyperparameter sweeping. You can easily search and scroll through these templates to find the one that suits your needs.
For example, accessing the Mistral 7B API. You click “Get” and wait for it to complete.
Click on the `run.ipynb` file and run the first cell.
After accessing the Mistral 7B API, the code returns the result. To review the client code, go to the server folder and open the `client.py` file.
I use VSCode regularly and found it easy to get started with Lightning ai Studio.
If you are comfortable with the Jupyter Notebook user interface, you can change the IDE by clicking the Jupyter Notebook button in the right panel. The right panel is where you will find all kinds of Lightning ai Studio plugins.
To add a new plugin, click the “+” button and choose from IDE, ai Agents, Training, Service, and Web Apps plugins.
It's that easy. Now you can enjoy Studio plugins with VSCode and Jupyter Notebook extensions.
Lightning ai Studio provides a complete platform for your machine learning needs, from experimenting with model architectures to deploying applications. This easy-to-use platform comes equipped with all the necessary features, eliminating the need to bundle multiple tools together.
You can harness the power and scale of the cloud without learning the intricacies of cloud computing or infrastructure management. Developers have eliminated complexity, allowing even data scientists without cloud experience to develop and deploy solutions independently.
Whether you're looking to prototype an idea or build a production app, Lightning ai Studio has you covered. The free tier grants access to all core features, including GPU Studio, to speed up training. This makes Lightning ai Studio an obvious choice for both learning and creating impactful machine learning applications.
Abid Ali Awan (@1abidaliawan) is a certified professional data scientist who loves building machine learning models. Currently, he focuses on content creation and writing technical blogs on data science and machine learning technologies. Abid has a Master's degree in technology Management and a Bachelor's degree in Telecommunications Engineering. His vision is to build an artificial intelligence product using a graph neural network for students struggling with mental illness.
