Percepat beban kerja TensorFlow dengan perangkat keras NVIDIA GPU. model kereta api, melayani prediksi, dan membangun pipa ML dengan dukungan penuh CUDA.
$ pip install tensorflow[and-cuda] # Menjalankan NVIDIA Tesla P40 (24GB) Siap. _
TelesorFlow adalah kerangka kerja mesin open-source Google untuk mempelajari pembuatan dan menyebarkan model ML. Dengan GPU VPS, Anda mendapatkan perangkat keras khusus untuk mempercepat pelatihan dan inferensi tanpa berbagi sumber daya.
Pribumi CUDA mendukung operasi TensorFlow. Sampai 50x lebih cepat dari CPU.
Integrasi penuh untuk gedung model tingkat tinggi dengan backend GPU.
Monitor pelatihan dengan Board sensor pada server Anda sendiri.
Menyebarkan model untuk produksi dengan PenyensorFlow Melayani di GPU.
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.
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.
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.
GPU VPS plans are billed monthly with no lock-in contracts and can be cancelled anytime. Contact us for current GPU pricing tiers.
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.
Yes. Full root SSH on every GPU VPS — install drivers, swap CUDA versions, customize the environment for TensorFlow however you need.
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.
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.
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.
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.
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.
Yes — 30-day money-back guarantee on every plan including GPU. Try TensorFlow on a GPU VPS risk-free.
Sebarkan server GPU NVIDIA yang berdedikasi dalam beberapa menit.