NVIDIA Tesla P40 · 24GB VRAM

TensorFlow GPU VPS

TensorFlow иш жүктөмдөрү NVIDIA GPU аппаратурасы менен тездетилген. Моделдерди машыктыруу, болжолдоолорду берүү жана ML конвейерлерин түзүү толук CUDA колдоосу менен.

Серверди орнотуу Бардык GPU параметрлери

$ pip install tensorflow[and-cuda]
# NVIDIA Tesla P40 (24GB) иштелип жатат
Даяр. _

GPU VPS'те TensorFlow деген эмне?

TensorFlow - бул Google компаниясынын ML моделдерин түзүү жана жайылтуу үчүн ачык булактуу машиналык окутуу фреймворку. GPU VPS менен сиз ресурстарды бөлүшпөй туруп, машыгуу жана индукцияны тездетүү үчүн атайын жабдууларды аласыз.

TensorFlow VPS.org GPU'да эмне үчүн

Графикалык процессор менен тездетилген

TensorFlow операциялары үчүн CUDA колдоосу. Процессордон 50 эсеге тез.

Совместимые жесткие диски

Full Hard интеграциясы жогорку деңгээлдеги моделдерди түзүү үчүн GPU backend менен.

Тенсордук стол

Өз сервериңизде TensorBoard менен машыгууларды көзөмөлдөө.

TF кызматы даяр

Графикалык процессордо TensorFlow Server менен моделдерди иштеп чыгууга киргизүү.

TensorFlow популярные варианты использования

Сүрөттүн классификациясы

Объектти аныктоо

Табигый тил иштетүү

Рекомендациялык системалар

Временные серии прогнозов

Продукциялык ML конвейерлери

Серверди орнотуу

Графикалык процессордун мүнөздөмөсү

Графикалык процессорNVIDIA Tesla P40

ВРМ24 GB GDDR5X

CUDA түстөрү3,840

FP3212 TFLOPS

INT847 TOPS

Жад346 GB/s

АрхитектураPascal (GP102)

Кеңири өтмөкБар-метал PCIe

Кайсы убакта суроолор берилет

What is TensorFlow on a GPU VPS?

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.

How do I set up TensorFlow on a GPU VPS?

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.

How much VRAM do I need for TensorFlow?

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 TensorFlow 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 TensorFlow?

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.

Do I get full root on the TensorFlow GPU VPS?

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

Which CUDA version is installed for TensorFlow?

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.

Does my TensorFlow GPU VPS persist between sessions?

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.

Where should I store data for my TensorFlow workload?

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.

Can I scale my TensorFlow 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 TensorFlow 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 TensorFlow 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 TensorFlow on a GPU VPS risk-free.