Sebenzisa i-TensorFlow ne-Keras ukuqeqeshwa nokubikezela ku-NVIDIA Tesla P40 (24 GB VRAM, Pascal architecture). Amaseva we-GPU angeke akwazi ukukhethwa; xhumana nathi ukuze uqinisekiswe uma bekhona.
$ pip install tensorflow[and-cuda]
# Isibonelo sokufaka umyalo
I-TensorFlow yi-Google's open-source machine learning framework. Ku-GPU server, i-TensorFlow iqhuba imisebenzi yayo kwi-GPU nge-CUDA.
I-TensorFlow isebenzisa i-GPU nge-CUDA uma ufaka umshayeli ohambisanayo ne-CUDA version.
Yakha amamodeli nge-Keras API phezulu kwe-GPU backend.
Ukuhlola ukuqeqeshwa nge-TensorBoard kuseva yakho.
Sebenzisa amamodeli aqeqeshiwe nge-TensorFlow Serving.
TensorFlow ingasebenzisa i-NVIDIA GPU ukusheshisa umsebenzi wayo. VPS.org GPU amaseva akhona ukuthenga; xhumana nathi ukulalela lapho. TensorFlow uqeqesho / ubunzima bomsebenzi obuncane. Izinhlelo zemisebenzi ehamba isikhathi eside: thola isithombe se-VPS yakho njalo futhi ugcine ikhophi yesisindo esiqeqeshiwe ngaphandle kwe-VPS.org.
Amaseva we-GPU akhona ukucela okwamanje. Namuhla ungasebenzisa i-TensorFlow ku-CPU ejwayelekile, lapho isebenza khona ngokucophelela kunakwi-GPU: SSH ngaphakathi bese usebenzisa i-pip install tensorflow[and-cuda].
Ukuqeqeshwa kwe-VRAM kulawulwa yisimo se-optimise plus activations. Ukuthuthukiswa okuphelele kwe-7B LLM kudinga cishe i-24 kuya ku-48 GB; LoRA / QLoRA ilungele i-8 kuya ku-16 GB.
Intengo ye-GPU izoshicilelwa uma izisebenzisi ze-GPU zingasatshalaliswa. Xhumana nathi uma ufuna ukulalela uma lokhu kwenzeke.
Yebo. Yonke iseva ye-VPS.org ifika nge-root access egcwele, ngakho ungasebenzisa ezinye izisetshenziswa kanye ne-TensorFlow ngaphakathi kwe-RAM ne-storage yeseva.
Yonke isisebenzisi se VPS.org sifika sigcwele ukungena kwe-root SSH, ngakho ungafaka ama-driver, ama-library ne TensorFlow noma ngabe ufuna.
Akukho umsekeli ofika ngesikhathi sokusebenza se-CUDA noma umqhubi we-NVIDIA ofakwe ngaphambili, futhi ama-servers we-GPU atholakalanga ukuthenga okwamanje. Ungafaka izibuyekezo TensorFlow ezidingayo wena.
Yebo. Amaseva we-VPS.org asebenza ngama-machines aqhubekayo, hhayi izimo ezihambayo: amamodeli we-TensorFlow, izilungiselelo nedatha zihlala ku-SSD yokugcina yeseva kuze kube ucima.
Gcina idatha esebenza kuseva ye-SSD ukuze ufinyelele ngokushesha ngesikhathi se-TensorFlow, futhi ukope izitho eziqediwe (izitho, izizukulwane, izingeniso) ukugcinwa ngaphandle kwe-VPS.org; ama-snapshots nama-backup ahlala ku-storage cluster efanayo.
Ungakhuphula noma iyiphi iseva ye-VPS.org ibe yi-plan enkulu kusuka kwindawo yokulawula; ukushintsha ubukhulu kuqala kabusha futhi ukufakwa kwe-TensorFlow kudlulisa. Amaseva we-GPU akhona.
Yebo. Amafayela okugcina akhokhelwa angeza-on (ngesonto +30% yentengo yephrojekthi, igcinwe 7 izinsuku; ngeviki +20%, igcinwe 28 izinsuku) futhi ama-snapshots amahhala, okusiza ngaphambi kokuhamba isikhathi eside TensorFlow. Kokubili kuhlale ku-indawo yokugcina efanayo njengeseva.
Xhumana nosizo ngaphakathi kwezinsuku ezingama-30 zokuthenga kwakho okukuqala ukuze ucele ukubuyiselwa imali. Amaseva we-GPU athengiswe, ngakho-ke akukho sinqumo se-GPU esihlobene.
Ikhono le-GPU lilinganiselwe. Sitshele ngomsebenzi wakho futhi sizophendula ngokutholakala nokuthengwa.