JarvisLabs.ai

Open your browser, pick a GPU profile, and start training before your coffee cools. With JarvisLabs.ai, the setup dance disappears. Create a workspace, choose a ready‑to‑use stack (PyTorch, TensorFlow, JAX, or RAPIDS), and spin up a machine instantly with a single action. Jupyter launches automatically in your tab, preloaded with CUDA, drivers, and common libraries. Import your Git repo or upload notebooks, then run a quick smoke test to verify the GPU. From zero to runnable code takes minutes, not hours.

Bring data in without wrangling servers. Mount an attached volume for persistent datasets, connect S3, GCS, or Azure Blob via credentials, or sync from Drive and Hugging Face with built‑in tools. Caching keeps frequently used files local to the instance. Start iterating: explore samples, prototype augmentations, and try new architectures right in notebooks. The environment supports conda and pip, and you can freeze exact versions to lock experiments for later reuse.

When you’re ready to train, pick the right horsepower. Scale from a single T4 to multi‑GPU A100 nodes, enable mixed precision, and schedule long runs from the UI or CLI. Detach and let jobs continue while you close the browser. Track metrics with TensorBoard or Weights & Biases; store checkpoints on persistent storage so you can resume after stopping the machine. Logs, GPU utilization, and memory charts are built in, so you can catch bottlenecks early. more