Open yonesora56 opened 1 year ago
I am having the same problem, did you find any solutions?
The CLI version of proteinfer can be executed even without GCP.
NVIDIA GPU and python3.7 are required.
I was able to run proteinfer on a G4dn instance of AWS EC2. The nvidia gpu environment is as follows
$ nvidia-smi
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 530.41.03 Driver Version: 530.41.03 CUDA Version: 12.1 |
|-----------------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|=========================================+======================+======================|
| 0 Tesla T4 Off| 00000000:00:1E.0 Off | 0 |
| N/A 26C P8 14W / 70W| 2MiB / 15360MiB | 0% Default |
| | | N/A |
+-----------------------------------------+----------------------+----------------------+
proteinfer uses Tensorflow1 so python must be 3.7.
I am terribly sorry to ask such a basic question, but I would like to ask you about creating a GCP instance.
I attempted to utilize proteinfer in the CLI by following the instructions in the README to create an instance. However, I encountered the below error.
ERROR
Are there any alternative parameters that would work best for using Proteinfer, such as machine type, zones, accelerators, etc.?