NVIDIA Tesla P40 · 24GB VRAM

PyTorch GPU VPS

Trein e implante modelos de aprendizagem profunda com PyTorch em GPUs NVIDIA dedicadas. Ambiente CUDA pré-configurado com acesso completo à raiz.

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

O que é {nome} em um GPU VPS?

PyTorch é o referencial de aprendizagem profunda líder usado por pesquisadores e engenheiros em todo o mundo. Um hardware GPU VPS oferece-lhe dedicado NVIDIA para treinar modelos mais rápidos e executar inferência em escala.

Porquê {nome} em VPS.org GPU

CUDA Pronto

Motores NVIDIA pré-configurados e kit de ferramentas CUDA. Comece o treinamento imediatamente.

Memoria GPU completa

24GB VRAM para treinar modelos maiores e tamanhos de lote maiores.

Integração do Jupyter

Execute cadernos Jupyter com suporte GPU para desenvolvimento interativo.

Formação Distribuída

Escalar para configurações multi-GPU para treinamento mais rápido em conjuntos de dados grandes.

Processos de uso populares {nome}

Formação em rede neural
Modelos de visão computacional
Modelos NLP & transformador
Investigação geradora de IA
Modelo de ajuste fino
Inferência de produção

Especificações da GPU

GPUNVIDIA Tesla P40
VRAM24 GB GDDR5X
Núcleos CUDA3,840
FP3212 TFLOPS
INT847 TOPS
Memória BW346 GB/s
ArquiteturaPascal (GP102)
PassagemPCIe-metal

Perguntas Frequentes

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.

Pronto para executar {nome} na GPU?

Desenvolva um servidor NVIDIA GPU dedicado em minutos. Sem reservas, sem chamadas de venda.

Lançar o seu VPS
A partir de $2.0/mo