NVIDIA Tesla P40 · 24GB VRAM

PyTorch GPU VPS

NVIDIA GPU'лар устида PyTorch билан чуқур ўқув моделларини тайёрлаш ва ўрнатиш. CUDA муҳитини root'га тўлиқ кириш билан олдиндан созлаш.

GPU серверини ўрнатиш Ҳамма GPU параметрлари

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

GPU VPS'да PyTorch нима?

PyTorch бутун дунё бўйлаб тадқиқотчилар ва муҳандислар томонидан фойдаланиладиган чуқур ўқув дастури. GPU VPS сизга моделларни тезроқ ўқитиш ва миқёсли индукцияни амалга ошириш учун NVIDIA жиҳозларини беради.

Нима учун PyTorch VPS.org GPU устида

CUDA тайёр

Аввалдан мослаштирилган NVIDIA драйверлари ва CUDA асбоблар тўплами. Дарҳол машғулотларни бошлаш.

ГПЮ хотираси тўлиқ

24GB VRAM катта моделларни ва катта партияларни ўқитиш учун.

Jupyter интеграцияси

Интерактив ривожланиш учун GPU қўллаб-қувватлаши билан Jupyter ноутбукларини ишга туширинг.

Тарқатилган машғулот

Кўп GPU лар билан катта маълумотлар тўпламлари устида тезроқ машқ қилиш учун масштаблаш.

PyTorch нинг машҳур ишлатилиши

Нейрон тармоғини машқ қилиш

Компьютер кўриш моделлари

NLP & трансформатор моделлари

Генерациявий AI тадқиқотлари

Модельни яхшилаш

Производство индукцияси

GPU серверини ўрнатиш

GPU хусусиятлари

ГПУNVIDIA Tesla P40

VRAM24 GB GDDR5X

CUDA ранглари3,840

FP3212 TFLOPS

INT847 TOPS

Ёдда сақлаш346 GB/s

АрхитектураPascal (GP102)

ЎтишБар-метал PCIe

Кўп бериладиган саволлар

What is PyTorch on a GPU VPS?

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?

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?

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?

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?

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?

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?

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?

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?

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?

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?

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?

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