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‎articles/cognitive-services/language-service/custom-text-analytics-for-health/how-to/deploy-model.md

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* A successfully [created project](create-project.md) with a configured Azure storage account.
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* Text data that has [been uploaded](design-schema.md#data-preparation) to your storage account.
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* [Labeled data](tag-data.md) and successfully [trained model](train-model.md)
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* [Labeled data](label-data.md) and a successfully [trained model](train-model.md).
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* Reviewed the [model evaluation details](view-model-evaluation.md) to determine how your model is performing.
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For more information, see [project development lifecycle](../overview.md#project-development-lifecycle).
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# [Language Studio](#tab/language-studio)
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[!INCLUDE [Assign resource](../../includes/custom/conversational-language-understanding/includes/language-studio/assign-resources.md)]
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[!INCLUDE [Assign resource](../../conversational-language-understanding/includes/language-studio/assign-resources.md)]
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# [REST APIs](#tab/rest-api)
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‎articles/cognitive-services/language-service/custom-text-analytics-for-health/how-to/train-model.md

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# Train your custom Text Analytics for health model
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Training is the process where the model learns from your [labeled data](tag-data.md). After training is completed, you'll be able to view the [model's performance](view-model-evaluation.md) to determine if you need to improve your model.
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Training is the process where the model learns from your [labeled data](label-data.md). After training is completed, you'll be able to view the [model's performance](view-model-evaluation.md) to determine if you need to improve your model.
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To train a model, you start a training job and only successfully completed jobs create a model. Training jobs expire after seven days, which means you won't be able to retrieve the job details after this time. If your training job completed successfully and a model was created, the model won't be affected. You can only have one training job running at a time, and you can't start other jobs in the same project.
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* A successfully [created project](create-project.md) with a configured Azure blob storage account
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* Text data that [has been uploaded](design-schema.md#data-preparation) to your storage account.
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* [Labeled data](tag-data.md)
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* [Labeled data](label-data.md)
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See the [project development lifecycle](../overview.md#project-development-lifecycle) for more information.
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> [!NOTE]
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> If you choose the **Automatically splitting the testing set from training data** option, only the data assigned to training set will be split according to the percentages provided.
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* **Use a manual split of training and testing data**: This method enables users to define which labeled documents should belong to which set. This step is only enabled if you have added documents to your testing set during [data labeling](tag-data.md).
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* **Use a manual split of training and testing data**: This method enables users to define which labeled documents should belong to which set. This step is only enabled if you have added documents to your testing set during [data labeling](label-data.md).
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## Train model
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‎articles/cognitive-services/language-service/custom-text-analytics-for-health/includes/language-studio/cancel-training.md

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---
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services: cognitive-services
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author: aahill
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manager: nitinme
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ms.service: cognitive-services
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ms.subservice: language-service
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ms.custom: event-tier1-build-2022
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ms.topic: include
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ms.date: 05/24/2022
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ms.author: aahi
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---
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To cancel a training job from within [Language Studio](https://aka.ms/languageStudio), go to the **Training jobs** page. Select the training job you want to cancel and click on **Cancel** from the top menu.

‎articles/cognitive-services/language-service/custom-text-analytics-for-health/includes/rest-api/cancel-training.md

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---
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author: aahill
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manager: nitinme
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ms.service: cognitive-services
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ms.subservice: language-service
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ms.custom: event-tier1-build-2022
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ms.topic: include
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ms.date: 05/06/2022
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ms.author: aahi
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---
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Create a **POST** request by using the following URL, headers, and JSON body to cancel a training job.
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### Request URL
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Use the following URL when creating your API request. Replace the placeholder values below with your own values.
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```rest
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{Endpoint}/language/authoring/analyze-text/projects/{PROJECT-NAME}/train/jobs/{JOB-ID}/:cancel?api-version={API-VERSION}
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```
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|Placeholder |Value | Example |
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|---------|---------|---------|
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|`{ENDPOINT}` | The endpoint for authenticating your API request. | `https://<your-custom-subdomain>.cognitiveservices.azure.com` |
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|`{PROJECT-NAME}` | The name for your project. This value is case-sensitive. | `EmailApp` |
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|`{JOB-ID}` | This value is the training job ID.| `XXXXX-XXXXX-XXXX-XX`|
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|`{API-VERSION}` | The version of the API you're calling. The value referenced is for the latest released [model version](../../../concepts/model-lifecycle.md#choose-the-model-version-used-on-your-data). | `2022-05-01` |
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### Headers
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Use the following header to authenticate your request.
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|Key|Value|
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|--|--|
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|`Ocp-Apim-Subscription-Key`| The key to your resource. Used for authenticating your API requests.|
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After you send your API request, you'll receive a 202 response with an `Operation-Location` header used to check the status of the job.

‎articles/cognitive-services/language-service/custom-text-analytics-for-health/includes/rest-api/export-project.md

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---
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services: cognitive-services
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author: aahill
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manager: nitinme
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ms.service: cognitive-services
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ms.subservice: language-service
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ms.topic: include
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ms.date: 05/09/2022
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ms.author: aahi
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ms.custom: ignite-fall-2021, event-tier1-build-2022
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---
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Create a **POST** request using the following URL, headers, and JSON body to export your project.
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### Request URL
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Use the following URL when creating your API request. Replace the placeholder values below with your own values.
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```rest
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{ENDPOINT}/language/authoring/analyze-text/projects/{PROJECT-NAME}/:export?stringIndexType=Utf16CodeUnit&api-version={API-VERSION}
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```
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|Placeholder |Value | Example |
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|---------|---------|---------|
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|`{ENDPOINT}` | The endpoint for authenticating your API request. | `https://<your-custom-subdomain>.cognitiveservices.azure.com` |
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|`{PROJECT-NAME}` | The name for your project. This value is case-sensitive. | `MyProject` |
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|`{API-VERSION}` | The version of the API you are calling. The value referenced here is the latest [model version](../../../concepts/model-lifecycle.md#choose-the-model-version-used-on-your-data) released. | `2022-05-01` |
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### Headers
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Use the following header to authenticate your request.
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|Key|Value|
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|--|--|
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|`Ocp-Apim-Subscription-Key`| The key to your resource. Used for authenticating your API requests.|
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#### Body
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Use the following JSON in your request body specifying that you want to export all the assets.
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```json
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{
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"assetsToExport": ["*"]
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}
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```
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Once you send your API request, you’ll receive a `202` response indicating that the job was submitted correctly. In the response headers, extract the `operation-location` value. It will be formatted like this:
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```rest
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{ENDPOINT}/language/authoring/analyze-text/projects/{PROJECT-NAME}/export/jobs/{JOB-ID}?api-version={API-VERSION}
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```
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`{JOB-ID}` is used to identify your request, since this operation is asynchronous. You’ll use this URL to get the export job status.

‎articles/cognitive-services/language-service/custom-text-analytics-for-health/includes/rest-api/get-export-status.md

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---
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author: aahill
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manager: nitinme
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ms.service: cognitive-services
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ms.subservice: language-service
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ms.custom: event-tier1-build-2022
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ms.topic: include
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ms.date: 05/09/2022
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ms.author: aahi
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---
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Use the following **GET** request to get the status of exporting your project assets. Replace the placeholder values below with your own values.
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### Request URL
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```rest
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{ENDPOINT}/language/authoring/analyze-text/projects/{PROJECT-NAME}/export/jobs/{JOB-ID}?api-version={API-VERSION}
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```
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|Placeholder |Value | Example |
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|---------|---------|---------|
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|`{ENDPOINT}` | The endpoint for authenticating your API request. | `https://<your-custom-subdomain>.cognitiveservices.azure.com` |
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|`{PROJECT-NAME}` | The name of your project. This value is case-sensitive. | `myProject` |
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|`{JOB-ID}` | The ID for locating your model's training status. This is in the `location` header value you received in the previous step. | `xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxxx` |
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|`{API-VERSION}` | The version of the API you are calling. The value referenced here is for the latest version released. See [Model lifecycle](../../../concepts/model-lifecycle.md#choose-the-model-version-used-on-your-data) to learn more about other available API versions. | `2022-05-01` |
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### Headers
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Use the following header to authenticate your request.
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|Key|Value|
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|--|--|
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|`Ocp-Apim-Subscription-Key`| The key to your resource. Used for authenticating your API requests.|
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### Response body
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```json
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{
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"resultUrl": "{RESULT-URL}",
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"jobId": "string",
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"createdDateTime": "2021-10-19T23:24:41.572Z",
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"lastUpdatedDateTime": "2021-10-19T23:24:41.572Z",
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"expirationDateTime": "2021-10-19T23:24:41.572Z",
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"status": "unknown",
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"errors": [
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{
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"code": "unknown",
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"message": "string"
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}
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]
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}
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```
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Use the URL from the `resultUrl` key in the body to view the exported assets from this job.
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### Get export results
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Submit a **GET** request using the `{RESULT-URL}` you received from the previous step to view the results of the export job.
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#### Headers
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Use the following header to authenticate your request.
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|Key|Value|
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|--|--|
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|`Ocp-Apim-Subscription-Key`| The key to your resource. Used for authenticating your API requests.|

‎articles/cognitive-services/language-service/custom-text-analytics-for-health/includes/rest-api/get-project-details.md

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---
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author: aahill
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manager: nitinme
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ms.service: cognitive-services
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ms.subservice: language-service
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ms.custom: event-tier1-build-2022
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ms.topic: include
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ms.date: 05/09/2022
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ms.author: aahi
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---
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Use the following **GET** request to get your project details. Replace the placeholder values below with your own values.
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```rest
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{ENDPOINT}/language/authoring/analyze-text/projects/{PROJECT-NAME}?api-version={API-VERSION}
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```
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|Placeholder |Value | Example |
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|---------|---------|---------|
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|`{ENDPOINT}` | The endpoint for authenticating your API request. | `https://<your-custom-subdomain>.cognitiveservices.azure.com` |
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|`{PROJECT-NAME}` | The name for your project. This value is case-sensitive. | `myProject` |
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|`{API-VERSION}` | The version of the API you are calling. The value referenced here is for the latest version released. See [Model lifecycle](../../../concepts/model-lifecycle.md#choose-the-model-version-used-on-your-data) to learn more about other available API versions. | `2022-05-01` |
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#### Headers
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Use the following header to authenticate your request.
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|Key|Value|
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|--|--|
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|`Ocp-Apim-Subscription-Key`| The key to your resource. Used for authenticating your API requests.|
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#### Response body
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```json
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{
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"createdDateTime": "2021-10-19T23:24:41.572Z",
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"lastModifiedDateTime": "2021-10-19T23:24:41.572Z",
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"lastTrainedDateTime": "2021-10-19T23:24:41.572Z",
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"lastDeployedDateTime": "2021-10-19T23:24:41.572Z",
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"projectKind": "CustomEntityRecognition",
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"storageInputContainerName": "{CONTAINER-NAME}",
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"projectName": "{PROJECT-NAME}",
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"multilingual": false,
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"description": "Project description",
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"language": "{LANGUAGE-CODE}"
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}
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```
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‎articles/cognitive-services/language-service/toc.yml

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- name: View model evaluation
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href: custom-text-analytics-for-health/how-to/view-model-evaluation.md
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- name: Deploy a model
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href: custom-text-analytics-for-health/how-to/deploy-model
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href: custom-text-analytics-for-health/how-to/deploy-model.md
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- name: Call the API
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href: custom-text-analytics-for-health/how-to/call-api.md
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- name: Back up and recover your models

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