Faʻaititia le mamafa o galuega TensorFlow ma le NVIDIA GPU hardware faapitoa. Faʻavasega ni faʻataʻitaʻiga, faʻatino taunuuga, ma fausia ni ML pipelines ma le lagolago atoa a CUDA.
$ pip install tensorflow[and-cuda] # Taʻalo i luga o NVIDIA Tesla P40 (24GB) Faʻatonu _
TensorFlow o le Google's open-source machine learning framework mo le fausiaina ma le faʻaaogaina o ituaiga ML. Ma le GPU VPS, e te maua ai le hardware faapitoa e faʻaititia ai le aʻoaʻoina ma le faʻaiuga e aunoa ma le faʻasoaina o punaoa.
Tuʻuina atu le lagolago CUDA mo galuega TensorFlow. E oo atu i le 50x vave nai lo le CPU.
Faʻatino le faʻatino Keras mo le fausiaina o se faʻataʻitaʻiga maualuga-vaega ma le GPU backend.
Faʻamautinoa le aʻoaʻoina ma TensorBoard i lau lava 'au'aunaga.
Faʻaaogaina o ituaiga i le gaosiga ma le TensorFlow Serving i le GPU.
TensorFlow on a GPU VPS is a CUDA-accelerated deployment. TensorFlow is a training / fine-tuning workload. Plan for long-running jobs — snapshot your VPS regularly, and consider an external cold-storage backup for trained weights.
Deploy a GPU VPS with the NVIDIA Tesla P40, SSH in, and run pip install tensorflow[and-cuda]. Your TensorFlow environment is ready in minutes with full GPU acceleration.
Training VRAM is dominated by the optimizer state plus activations. Full fine-tuning of a 7B LLM needs ~24-48 GB; LoRA / QLoRA fits in 8-16 GB. Our Tesla P40 supports LoRA-class fine-tuning out of the box; full training of larger models requires multi-GPU.
GPU VPS plans are billed monthly with no lock-in contracts and can be cancelled anytime. Contact us for current GPU pricing tiers.
Yes — you have full root on the GPU VPS. Run whatever fits inside the 24 GB VRAM and the available RAM / storage budget alongside TensorFlow.
Yes. Full root SSH on every GPU VPS — install drivers, swap CUDA versions, customize the environment for TensorFlow however you need.
GPU VPSs ship with a recent CUDA runtime and the matching NVIDIA driver pre-installed. You can pin or upgrade CUDA versions as required by your TensorFlow workload.
Yes — your TensorFlow GPU VPS is a long-running persistent server, not an ephemeral instance. Models, configs, and data stay on the SSD between sessions.
Keep working data on the VPS SSD for fast access during TensorFlow runs; back up finished artifacts (weights, generations, embeddings) off-server via snapshots or object storage for safety.
Yes — plan upgrades are instant from your control panel; the GPU itself can be swapped to a larger tier on request. Your TensorFlow install carries over.
Yes. Automated daily backups are an add-on; manual snapshots are free. Useful for long TensorFlow training runs where you want a checkpointable server state.
Yes — 30-day money-back guarantee on every plan including GPU. Try TensorFlow on a GPU VPS risk-free.
Faʻaaogaina se NVIDIA GPU server faʻapitoa i minute. E leai se faʻatapulaʻaina, leai se telefoni faʻatau.