Learning on NVidia GTX 650 Ti

Can NVidia GTX 650 Ti process model learning?
After required DeepSpeech installations (with tensorflow-gpu/pre removed tensorflow) - all just instructions i got only message:

Illegal instruction

Maybe GPU won’t to be used?! How can i clarify if it so?

$ nvidia-smi
gives this:

+-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.64       Driver Version: 440.64       CUDA Version: 10.2     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  GeForce GTX 650 Ti  Off  | 00000000:01:00.0 N/A |                  N/A |
| 40%   41C    P0    N/A /  N/A |      0MiB /   979MiB |     N/A      Default |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID   Type   Process name                             Usage      |
|=============================================================================|
|    0                    Not Supported                                       |

This likely means TensorFlow build uses instructions your CPU does not support (AVX, AVX2 likely)

This looks like your GPU can work with CUDA 10.2, which would be okay for running learning.

However, this is old GPU, and it’s unlikely you can expect it to be realistically usable for any serious training process: its computational power is way too low, and you have not even 1GB of VRAM.

It might be enough for testing purposes, but that’s it.

Yeap, I’ve been just wanted to do some tests. Nothing more.
CPU falgs are:
flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx rdtscp lm constant_tsc arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx est tm2 ssse3 cx16 xtpr pdcm pcid sse4_1 sse4_2 popcnt tsc_deadline_timer xsave lahf_lm cpuid_fault epb pti ssbd ibrs ibpb stibp tpr_shadow vnmi flexpriority ept vpid fsgsbase smep erms xsaveopt dtherm arat pln pts md_clear flush_l1d

Does it meens i can’t process on this machine?

Unfortunately, it means you cannot use official tensorflow packages, no. This is definitively not a DeepSpeech-level issue here.