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In this post, we will explore the up-to-date Cloud IDE that is both free and user-friendly. It is an improved version of Google Colab that allows you to save projects, exploit the necessary plugins, and run generative models on GPU for free.
Lightning AI Studio 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.
Here are the key features of Lightning AI Studio:
- It integrates popular machine learning tools into a single interface so you don’t have to switch between different tools. This allows you to more easily build scalable AI applications and endpoints.
- No environment configuration required. You can code in your browser or connect your local IDE (VSCode or PyCharm). You can also easily switch between CPU and GPU without changing your environment.
- It allows you to host and share AI apps built with Streamlit, Gradio, React JS, etc. It also allows multiple users to collaborate by coding together.
- It provides unlimited storage space and the ability to upload and share files, as well as connect to S3 containers.
- Enables massive model training using thousands of GPUs (paid option). You can run massive hyperparameter scanning, data preprocessing, and model deployment in parallel.
- It provides a local development environment, leveraging the potential of cloud infrastructure.
- Discover community templates (Studio) that let you quickly deploy, tune, and train models in the cloud with your data in minutes, with no configuration required.
Your Jupyter Notebook/VSCode in the cloud provides scalable hardware for training huge language models and running swift inferences.
You can sign up for a free account at lightning.ai/sign-up . For instant verification, make sure you exploit an official company email or .edu. I signed up with my @kdnuggets.com email and got instant access.
Once you have created your account, follow a few plain steps to customize your Studio experience. To get 7 hours of free GPU, you will need to verify your phone number.
After completing the initial steps, you will be redirected to a sample project that contains a basic Python file. Within a few minutes, your Studio will be ready to process images and fine-tune your Renest model. To get started, simply write the code and run the file.
The user interface (UI) is quite similar to that of VSCode, but with additional options available on the right panel.
The Lightning AI platform offers studios, which are user-designed project templates. These templates include code, environment settings, and data to lend a hand you get started with your project. You can find different studios in the platforms, such as training, tuning, preprocessing, inference, and hyperparameter mining templates. You can easily search and scroll through these templates to find the one that meets your requirements.
For example, access to Mistral 7B API. You click “Get” and wait for it to finish.
Click on the `run.ipynb` file and run the first cell.
After accessing the Mistral 7B API, the code returns the result. To view the client code, go to the server folder and open the file `client.py`.
I exploit VSCode regularly and found it uncomplicated 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 on the right panel. The right panel is where you will find all kinds of Lightning AI Studio plugins.
To add a up-to-date plugin, click the “+” button and select one of the plugins: IDE, AI Agents, Training, Serving or Webapps.
It’s that plain. Now you can exploit 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 user-friendly platform is packed with all the necessary features, eliminating the need to assemble different tools.
You can leverage the power and scale of the cloud without learning the intricacies of cloud computing or infrastructure management. Developers have abstracted the complexity, allowing even data scientists without cloud experience to independently develop and deploy solutions.
Whether you want to prototype an idea or build a production-grade app, Lightning AI Studio has everything you need. The free tier gives you access to all the core features, including Studio GPUs to accelerate training. This makes Lightning AI Studio an obvious choice for both learning and building impactful machine learning applications.
Abid Ali Awan (@1abidaliawan) is a certified data science professional who loves building machine learning models. He currently focuses on content creation and writing technical blogs on machine learning and data science technologies. Abid has a Masters in Technology Management and a Bachelors in Telecommunication Engineering. His vision is to build an AI product using Graph Neural Network for students struggling with mental illness.