NVIDIA Tesla P40 · 24GB VRAM

PyTorch GPU VPS

Vadba in razporeditev modelov globoko učenje s PyTorch na namenskih NVIDIA GPUs. Vnaprej nastavljeno okolje CUDA s polnim dostopom do korenine.

$ pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu124
# Tekanje na NVIDIA Tesla P40 (24GB)
Pripravljeni. _

Kaj je {ime} na GPU VPS?

PyTorch je vodilni okvir za globoko učenje, ki ga uporabljajo raziskovalci in inženirji po vsem svetu. GPU VPS vam daje posebno NVIDIA strojno opremo za hitrejše usposabljanje modelov in teči ugotovitve na skali.

Zakaj {ime} na VPS.org GPU

CUDA pripravljena

Vnaprej nastavljeni NVIDIA vozniki in CUDA toolkit. Začnite trenirati takoj.

Celoten GPU pomnilnik

24GB VRAM za usposabljanje večjih modelov in večje velikosti serij.

Vključevanje Jupyterja

Poženite Jupyter beležke s podporo GPU za interaktiven razvoj.

Razdeljeno usposabljanje

Skaliraj na več GPU nastavitev za hitrejše usposabljanje na velikih podatkovnih zbirkah.

Priljubljeno {ime} Uporabni primeri

Usposabljanje nevralnih omrežij
Računalniški vizijski modeli
Modeli NLP in transformatorja
Generativna raziskava AI
Vzorec finega uravnavanja
Zaključek proizvodnje

Specifikacije GPU

GPUNVIDIA Tesla P40
VRAM24 GB GDDR5X
Jedra CUDA3,840
FP3212 TFLOPS
INT847 TOPS
Spomin BW346 GB/s
ArhitekturaPascal (GP102)
Prehaja skoziBare-kovina PCIe

Pogosta vprašanja

What is PyTorch on a GPU VPS?

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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.

How do I set up PyTorch on a GPU VPS?

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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.

How much VRAM do I need for PyTorch?

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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.

Is PyTorch GPU VPS billed hourly or monthly?

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GPU VPS plans are billed monthly with no lock-in contracts and can be cancelled anytime. Contact us for current GPU pricing tiers.

Can I run other tools alongside PyTorch?

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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.

Do I get full root on the PyTorch GPU VPS?

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Yes. Full root SSH on every GPU VPS — install drivers, swap CUDA versions, customize the environment for PyTorch however you need.

Which CUDA version is installed for PyTorch?

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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.

Does my PyTorch GPU VPS persist between sessions?

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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.

Where should I store data for my PyTorch workload?

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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.

Can I scale my PyTorch GPU VPS later?

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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.

Are backups available for my GPU VPS?

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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.

Is there a money-back guarantee on the GPU VPS?

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Yes — 30-day money-back guarantee on every plan including GPU. Try PyTorch on a GPU VPS risk-free.

Pripravljeni za teči {ime} na GPU?

V nekaj minutah razporedite poseben strežnik NVIDIA GPU. Brez rezervacij, brez prodajnih klicev.

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