NVIDIA Tesla P40 · 24GB VRAM

TensorFlow GPU VPS

Ṣàfikún àwọn iṣẹ́ TensorFlow láti inú àwọn ìṣàmúlò-ètò NVIDIA GPU. Ṣàfikún àwọn àwọn àwòrán, fi àwọn àwọn ìṣàfilọ́lẹ̀ pamọ́, àti ìṣàfilọ́lẹ̀ àwọn pánẹ́ẹ̀lì ML láti inú ìmọ̀ràn CUDA.

Fí Sáàbù GPU Hàn Àwọn Àtòjọ-ẹ̀yàn GPU

$ pip install tensorflow[and-cuda]
# Ń bọ́ nípa NVIDIA Tesla P40 (24GB)
Tí a tì ṣè _

Àwọn àwọn ààyè-iṣẹ́ tí a fi pamọ́

TensorFlow ní àwọn àwọn ààyè-iṣẹ́ ìmọ́ràn-ìṣàfilọ́lẹ̀-ìṣàfilọ́lẹ̀ Google fun ìṣàfilọ́lẹ̀ àwọn à

Kini idi ti TensorFlow lo lori VPS.org GPU

GPU tí a fi pẹ̀lú

Àwọn ìṣàfilọ́lẹ̀ CUDA àwọn iṣẹ́ TensorFlow. Lẹ́ẹ̀kan lọ́wọ́lọ́wọ́ jú CPU lọ.

Àwọn Ìrọ̀kọ̀sì Tí A Fẹ̀

Ìdákọ́rà tí a fi kọ́ nípá ìṣàmúlò-ètò tí o gàjú nípá ìpele-òkè GPU.

Àwọn Àwọn Ààyè-iṣẹ́

Àwọn ìṣàmúlò-ètò ìṣàfihàn láti inú TensorBoard lórí àwọn sáà rẹ̀.

Tí a tí ṣẹ́ṣẹ̀ fi TF pamọ́

Fi àwọn àwọn ààyè-iṣẹ́ pamọ́ sí ìṣàfilọ́lẹ̀ láti inú TensorFlow Serving lórí GPU.

Àwọn Ààyè Lòjútó TensorFlow

Àwọn àwọn àwòrán

Àwọn àwọn

Ìṣàmúlò-ètò ìtàn

Àwọn ìṣàmúlò-ètò ìṣàmúlò-ètò

Àwọn àwọn

Àwọn ìṣàmúlò-ètò ML

Fí Sáàbù GPU Hàn

Àwọn À

GPUNVIDIA Tesla P40

VRAM24 GB GDDR5X

Àwọn àwọ̀ CUDA3,840

FP3212 TFLOPS

INT847 TOPS

Àwọn àwọn àmì-ìwé346 GB/s

Àwọn Ìṣàmúlò-ètòPascal (GP102)

Àwọn Ìjánu-ìṣàmúlò-ètòPCIe àìdárá

Àwọn Àtòjọ-ẹ̀yàn

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.