Response model for model deployment. Deploying a model pre-loads the weights into the Ray object store, making them available for zero-copy access by plugins.
| Name | Type | Description | Notes |
|---|---|---|---|
| success | bool | Whether deployment succeeded | |
| model_id | str | Model identifier | |
| namespace_id | str | Namespace ID | |
| deployment_status | str | Deployment status (deployed, failed) | |
| cached | bool | Whether model is cached in object store | [optional] [default to False] |
| message | str | Status message |
from mixpeek.models.model_deploy_response import ModelDeployResponse
# TODO update the JSON string below
json = "{}"
# create an instance of ModelDeployResponse from a JSON string
model_deploy_response_instance = ModelDeployResponse.from_json(json)
# print the JSON string representation of the object
print(ModelDeployResponse.to_json())
# convert the object into a dict
model_deploy_response_dict = model_deploy_response_instance.to_dict()
# create an instance of ModelDeployResponse from a dict
model_deploy_response_from_dict = ModelDeployResponse.from_dict(model_deploy_response_dict)