Organiza tus páginas con colecciones
Guarda y categoriza el contenido según tus preferencias.
En esta página, se explica cómo limpiar los recursos de Google Cloud que creaste para entrenar tu modelo de clasificación de imágenes y entregar predicciones con él.
En este instructivo, se incluyen las siguientes páginas:
En cada página, se supone que ya realizaste las instrucciones de las páginas anteriores del instructivo.
En el resto de este documento, se supone que usas el mismo entorno de Cloud Shell que creaste cuando sigues la primera página de este instructivo. Si tu sesión original de Cloud Shell ya no está abierta, puedes volver al entorno de la siguiente manera:
In the Google Cloud console, activate Cloud Shell.
En la sesión de Cloud Shell, ejecuta el siguiente comando:
cdhello-custom-sample
Borrar recursos de Vertex AI
En esta sección, se describe cómo borrar todos los recursos de Vertex AI que creaste para este instructivo.
Anula la implementación del modelo en el extremo
En esta sección, se describe cómo anular la implementación de tu modelo en tu extremo. Puedes pensar en esta acción como una forma de desconectar el modelo del extremo.
Busca la fila de tu modelo, hello_custom. En esa fila, haz clic en Ver más more_vert. Luego, haz clic en Borrar modelo.
En el cuadro de diálogo Borrar modelo, haz clic en Borrar.
Borra tu trabajo y canalización de entrenamiento personalizados
La canalización de entrenamiento y el trabajo personalizado son solo registros del entrenamiento que se produjo antes. Si deseas borrar tu trabajo personalizado, haz lo siguiente:
En la Google Cloud consola, en la sección Vertex AI, ve a la página Canalizaciones de entrenamiento.
Busca la fila de tu canalización de entrenamiento, hello_custom. En esa fila, haz clic en Ver más more_vert. Luego, haz clic en Borrar canalización de entrenamiento.
En el cuadro de diálogo Borrar trabajo de entrenamiento, haz clic en Borrar.
Para ir a la página Trabajos personalizados, haz clic en Trabajo personalizado en la
consola deGoogle Cloud o haz clic en el siguiente vínculo:
Encuentra la fila de tu trabajo personalizado, hello_custom-custom-job. En esa fila, haz clic en Ver más more_vert. Luego, haz clic en Borrar trabajo personalizado.
En el cuadro de diálogo Borrar trabajo de entrenamiento, haz clic en Borrar.
[[["Fácil de comprender","easyToUnderstand","thumb-up"],["Resolvió mi problema","solvedMyProblem","thumb-up"],["Otro","otherUp","thumb-up"]],[["Difícil de entender","hardToUnderstand","thumb-down"],["Información o código de muestra incorrectos","incorrectInformationOrSampleCode","thumb-down"],["Faltan la información o los ejemplos que necesito","missingTheInformationSamplesINeed","thumb-down"],["Problema de traducción","translationIssue","thumb-down"],["Otro","otherDown","thumb-down"]],["Última actualización: 2025-09-04 (UTC)"],[],[],null,["# Hello custom training: Clean up your project\n\nThis page guides you through cleaning up the Google Cloud resources that you\ncreated to train your image classification model and serve predictions from it.\nThis tutorial has several pages:\n\n\u003cbr /\u003e\n\n1. [Setting up your project and environment.](/vertex-ai/docs/tutorials/image-classification-custom)\n\n2. [Training a custom image classification\n model.](/vertex-ai/docs/tutorials/image-classification-custom/training)\n\n3. [Serving predictions from a custom image classification\n model.](/vertex-ai/docs/tutorials/image-classification-custom/serving)\n\n4. Cleaning up your project.\n\nEach page assumes that you have already performed the instructions from the\nprevious pages of the tutorial.\nThe rest of this document assumes that you are using the same Cloud Shell environment that you created when following the [first page of this\ntutorial](/vertex-ai/docs/tutorials/image-classification-custom). If your original Cloud Shell session is no longer open, you can return to the environment by doing the following:\n\n\u003cbr /\u003e\n\n1. In the Google Cloud console, activate Cloud Shell.\n\n [Activate Cloud Shell](https://console.cloud.google.com/?cloudshell=true)\n2. In the Cloud Shell session, run the following command:\n\n ```bash\n cd hello-custom-sample\n ```\n\nDelete Vertex AI resources\n--------------------------\n\nThis section describes how to delete all of the Vertex AI resources\nthat you created for this tutorial.\n\n### Undeploy your model from your endpoint\n\nThis section describes how to undeploy your model from your endpoint. You can\nthink about this action as a way of disconnecting your model from your endpoint.\n\nYou must follow this section before you can [delete your\nendpoint](#delete-endpoint) or [delete your model](#delete-model).\n\n1. In the Google Cloud console, in the Vertex AI section, go to\n the **Endpoints** page.\n\n [Go to Endpoints](https://console.cloud.google.com/vertex-ai/endpoints)\n2. Click `hello_custom` to go to the endpoint details page.\n\n3. On the row for your model, `hello_custom`, click **Undeploy model\n delete**.\n\n4. In the **Undeploy model from endpoint** dialog, click **Undeploy**.\n\n### Delete your endpoint\n\nBefore you delete an endpoint, you must [undeploy your model from your\nendpoint](#undeploy-model). After you've deleted your endpoint, you won't\nbe able to re-use that endpoint name for up to 7 days.\n\nAfter you've undeployed your model from the endpoint, do the following\nto delete your endpoint:\n\n1. In the Google Cloud console, in the Vertex AI section, go to\n the **Endpoints** page.\n\n [Go to Endpoints](https://console.cloud.google.com/vertex-ai/endpoints)\n2. Find your the row of your endpoint, `hello_custom`, again. On that row, click\n **View more more_vert** . Then click **Remove endpoint**.\n\n3. In the **Remove endpoint** dialog, click **Confirm**.\n\n### Delete your model\n\nBefore you follow this section, you must [undeploy your model from your\nendpoint](#undeploy-model). Afterward, do the following to delete your model:\n\n1. In the Google Cloud console, in the Vertex AI section, go to\n the **Models** page.\n\n [Go to Models](https://console.cloud.google.com/vertex-ai/models)\n2. Find your the row of your model, `hello_custom`. On that row, click **View\n more more_vert** . Then\n click **Delete model**.\n\n3. In the **Delete model** dialog, click **Delete**.\n\n### Delete your custom training pipeline and job\n\nYour training pipeline and custom job are just records of the training that\nhappened earlier. If you want to delete your custom job, do the following:\n\n1. In the Google Cloud console, in the Vertex AI section, go to\n the **Training pipelines** page.\n\n [Go to Training pipelines](https://console.cloud.google.com/vertex-ai/training/training-pipelines)\n2. Find your the row of your training pipeline, `hello_custom`. On that row,\n click **View more more_vert** . Then click **Delete training\n pipeline**.\n\n3. In the **Delete training job** dialog, click **Delete**.\n\n4. To go to the **Custom jobs** page, click **Custom job** in the\n Google Cloud console, or click the following link:\n\n [Go to Custom jobs](https://console.cloud.google.com/vertex-ai/training/custom-jobs)\n5. Find your the row of your custom job, `hello_custom-custom-job`. On that row,\n click **View more more_vert** . Then click **Delete custom job**.\n\n6. In the **Delete training job** dialog, click **Delete**.\n\nClean up your Cloud Shell session\n---------------------------------\n\nCloud Shell incurs no charges, and it [automatically deletes your home\ndisk after a period of inactivity](/shell/docs/limitations). However, if you\nplan to use Cloud Shell for other purposes in the near future, you\nmight want to manually remove the files that you created for this tutorial.\n\nIn your Cloud Shell session, run the following commands: \n\n cd ..\n rm -rf hello-custom-sample\n\nDelete your Cloud Storage bucket\n--------------------------------\n\nIn your Cloud Shell session, run the following command: \n\n gcloud storage rm gs://\u003cvar translate=\"no\"\u003eBUCKET_NAME\u003c/var\u003e --recursive --continue-on-error\n\nReplace \u003cvar translate=\"no\"\u003eBUCKET_NAME\u003c/var\u003e with the name of the Cloud Storage\nbucket that you created when reading the [first page of this\ntutorial](/vertex-ai/docs/tutorials/image-classification-custom).\n\nDelete your Cloud Run function\n------------------------------\n\nIn your Cloud Shell session, run the following command: \n\n gcloud functions delete classify_flower --region=us-central1 --quiet\n\nWhat's next\n-----------\n\n- To learn about additional ways to train ML models on Vertex AI,\n try one of the other [Vertex AI tutorials](/vertex-ai/docs/tutorials).\n\n- Read an [overview of how Vertex AI\n works](/vertex-ai/docs/start/introduction-unified-platform)."]]
