E-ba le lebelo la ho sebetsa TensorFlow ka NVIDIA GPU hardware e etselitsoeng. E-ba le li-models tsa ho ithuta, ho fana ka litlhahiso, le ho theha li-pipelines tsa ML ka tšehetso e felletseng ea CUDA.
$ pip install tensorflow[and-cuda] # Ho sebetsa ka NVIDIA Tesla P40 (24GB) E loketse. _
TensorFlow ke ts'ebetso ea ho ithuta ha li-machine e nang le li-source tse bulehileng tsa Google bakeng sa ho theha le ho kenya li-models tsa ML. Ka GPU VPS, u tla fumana lisebelisoa tse khethehileng ho potlakisa ho ithuta le ho lekanya ntle le ho arolelana li-resources.
Ho tšehetsa CUDA ea naha bakeng sa liphetoho tsa TensorFlow. Ho fihlela ho 50x ho potlakile ho feta CPU.
Li-GPU tse nang le li-processor tse phahameng li ka sebelisoa ho etsa li-GPU tse phahameng.
Tsebisa ho ithuta ka TensorBoard ho seva ea hau.
Ho kenya li-models ho tlhahiso ka TensorFlow Serving ho 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.
Sebetsa NVIDIA GPU server ka metsotso. Ha ho na li-reservations, ha ho na li-call tsa thekiso.