I have a training task that auto-magically saves a model for me to GCS
task = Task.init( project_name=project_name, task_name=f"Image classification training", output_uri = "gs://" + bucket_name ) ... PATH = "./classifier_net.pth" torch.save(net.state_dict(), PATH) # auto-uploads to GCS
Now I'd like to https://clear.ml/docs/latest/docs/references/sdk/model_model#set_metadata to the model.
I've not seen any examples of how it's done. Do I need to forgo auto-magic
and create an OutputModel?
Sample code example would be nice 🙏
Hi PanickyMoth78
` torch.save(net.state_dict(), PATH) # auto-uploads to GCS
output_models = Task.current_task().models["output"]
last_model = output_models[-1]
last_model.set_metadata(key="my key", value="my value", type="str") `
