# VLM Field Extraction Models

- 5 Articles

[ORCA (Optical Reasoning and Cognition Agent) VLMs](https://help.hyperscience.ai/v43/docs/orca-optical-reasoning-and-cognition-agent-vlms)
  
  - Published on May 6, 2026

Accessing this feature Your access to the feature described in this article depends on your license package and pricing plan. To learn which features are available to your organization and how to add more, contact your Hyperscience representative.

[TDM for ORCA VLMs](https://help.hyperscience.ai/v43/docs/tdm-for-orca-vlms)
  
  - Updated on Jul 22, 2026
  - Published on May 6, 2026
  
Training Data Management (TDM) is where you prepare and manage the data used to train your models. In TDM, you review and annotate documents, build your training dataset, and improve model performance for your specific use case. In this article,

[Installing ORCA VLMs](https://help.hyperscience.ai/v43/docs/installing-orca-vlms)
  
  - Updated on Jun 11, 2026
  - Published on May 6, 2026
  
This article explains how to install ORCA (Optical Reasoning and Cognition Agent) VLMs and configure your instance to use them for document processing. For information about the capabilities of ORCA VLMs, see our ORCA (Optical Reasoning and Cognition Agent) documentation.

[Model Definitions](https://help.hyperscience.ai/v43/docs/model-definitions)
  
  - Updated on Jul 7, 2026
  - Published on May 6, 2026
  
Building an effective document-processing solution requires understanding how the components involved in model training work together. The Model Definitions table is designed to help manage these components. Model definitions separate configurations and functionality into distinct categories to ease understanding.

[Training a Specialized Model](https://help.hyperscience.ai/v43/docs/training-a-specialized-model)
  
  - Updated on Jul 8, 2026
  - Published on May 6, 2026
  
ORCA is a Vision Language Model (VLM) that extracts information from documents. To learn more, see ORCA (Optical Reasoning and Cognition Agent) VLMs. While the base model works out of the box, you can improve its performance by training it on specific datasets.