Entrenatu eta hedatu ikaskuntza sakona duten ereduak PyTorch-ekin NVIDIA GPU dedikatuetan. Aurrekonfiguratutako CUDA ingurunea root sarbide osoarekin.
$ pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu124 # NVIDIA Tesla P40 (24GB) gailuan exekutatzen Prest. _
PyTorch mundu osoko ikertzaileek eta ingeniariek erabiltzen duten ikaskuntza sakonerako marko nagusia da. GPU VPS batek NVIDIA hardware dedikatu bat ematen dizu modeloak azkarrago entrenatzeko eta eskalan inferentzia exekutatzeko.
Aurrekonfiguratutako NVIDIA kontrolatzaileak eta CUDA tresna-kutxa. Hasi entrenatzen berehala.
24 GB VRAM, modelo handiagoak eta batch tamaina handiagoak entrenatzeko.
Exekutatu Jupyter koadernoak GPU euskarriarekin garapen interaktiborako.
Eskalatu GPU anitzeko konfigurazioetara datu multzo handietan entrenamendu azkarragoa lortzeko.
PyTorch on a GPU VPS is a CUDA-accelerated deployment. PyTorch 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 torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu124. Your PyTorch 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 PyTorch.
Yes. Full root SSH on every GPU VPS — install drivers, swap CUDA versions, customize the environment for PyTorch 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 PyTorch workload.
Yes — your PyTorch 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 PyTorch 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 PyTorch install carries over.
Yes. Automated daily backups are an add-on; manual snapshots are free. Useful for long PyTorch training runs where you want a checkpointable server state.
Yes — 30-day money-back guarantee on every plan including GPU. Try PyTorch on a GPU VPS risk-free.
Instalatu NVIDIA GPU zerbitzari dedikatu bat minutu gutxitan. Erreserbarik ez, salmenta-deirik ez.