Blog
We're excited to announce the launch of the Trainwave Jupyter Extension - a game-changing integration that brings the power of cloud GPU computing directly into your JupyterLab environment. No more context switching, no more complex CLI commands, and no more manual file uploads. Now you can seamlessly run your machine learning experiments on powerful GPU infrastructure with just a few clicks, all from within your familiar Jupyter notebook interface.
How can you finetune LLAMA 3 for your specific use case and not break the bank? In this article, we're going to look at the different options available to you and how you can optimize your training costs.
Where is the bang for buck? We all know that GPUs are expensive, how does one go about finding the best price/performance for their workload? Well we're about to find out, keep reading!
Ever dreamed of training cutting-edge AI models without the hassle of complex cloud setups and hefty GPU costs? We've got you covered! Trainwave is designed to revolutionize the way you approach AI development.