Accelerate Colab Model Training

My Google Colab notebook already trains and runs perfectly, but Colab Pro’s GPUs are still too slow for my current machine-learning model training workload. I want the exact same code moved to a faster environment—ideally one offering an NVIDIA A100, V100, or anything comparable—so that epoch times drop dramatically without me having to rewrite the notebook.

What I need from you:
• Spin up or access a high-end GPU instance, install the same Python and ML libraries, and import my notebook.
• Run a short proof-of-concept training cycle to confirm it executes error-free and faster than my current Colab Pro setup.
• Hand over clear, step-by-step instructions (or an automated script) so I can repeat the process on demand, along with any platform or pricing tips you recommend for sustained usage.

No architecture changes are required; this is purely about hardware speed-up and environment replication. If you’re comfortable with AWS, GCP, Azure, Gradient, Paperspace, or a similar service that can supply the required GPU power, I’m open to whichever option you feel delivers the best time-to-train improvement.