You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Copy file name to clipboardExpand all lines: articles/ai-services/document-intelligence/overview.md
+2-18Lines changed: 2 additions & 18 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -213,7 +213,6 @@ Custom models are trained using your labeled datasets to extract distinct data f
213
213
214
214
:::row:::
215
215
:::column:::
216
-
[**Custom generative (preview)**](#custom-generative-extraction-preview) | Build a custom extraction model using generative AI for documents with unstructured format and varying templates.
217
216
:::column-end:::
218
217
:::column span="":::
219
218
[**Custom neural**](#custom-neural) | Extract data from mixed-type documents.
@@ -248,9 +247,9 @@ Document Intelligence supports optional features that can be enabled and disable
@@ -543,21 +542,6 @@ You can use Document Intelligence to automate document processing in application
543
542
> [!div class="nextstepaction"]
544
543
> [Return to custom model types](#custom-models)
545
544
546
-
#### Custom generative extraction (preview)
547
-
548
-
:::image type="content" source="media/overview/analyze-custom-generative.png" alt-text="Screenshot of Custom generative model analysis using Azure AI Studio.":::
549
-
550
-
> [!NOTE]
551
-
> Custom generative model is only available in Azure AI Studio.
552
-
> To try out custom generative model in AI Studio, *visit*[Document field extraction (custom generative)](https://aka.ms/custom-generative)
553
-
554
-
| About | Description |Automation use cases | Development options |
|[**Custom generative model**](train/custom-generative-extraction.md)| The custom generative model is used to extract fields from unstructured documents or structured forms with a wide variety of visual templates.|The model uses Generative AI to extract fields, improve quality with only a few labeled samples and can be integrated into your processes with grounding and confidence scores.|[**Azure AI Studio**](https://aka.ms/custom-generative)</br>● [**REST API**](/rest/api/aiservices/document-models/build-model?view=rest-aiservices-2023-07-31&preserve-view=true&tabs=HTTP)</br>● [**C# SDK**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-4.0.0&preserve-view=true)</br>● [**Java SDK**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-4.0.0&preserve-view=true)</br>● [**JavaScript SDK**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-4.0.0&preserve-view=true)</br>● [**Python SDK**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-4.0.0&preserve-view=true)|
557
-
558
-
> [!div class="nextstepaction"]
559
-
> [Return to custom model types](#custom-models)
560
-
561
545
#### Custom neural
562
546
563
547
:::image type="content" source="media/overview/analyze-custom-neural.png" alt-text="Screenshot of Custom Neural model analysis using Document Intelligence Studio.":::
0 commit comments