Configuring model preferences

On a self-hosted instance, you can configure settings to determine whether to the auxiliary model, and model use on GPU.

Configuring whether to use an auxiliary model

To improve overall inference, you can configure whether Textual uses the en_core_web_sm auxiliary NER model.

Entity types that the auxiliary model detects

The auxiliary model detects the following types:

• EVENT

• LANGUAGE

• LAW

• NRP

• NUMERIC_VALUE

• PRODUCT

• WORK_OF_ART

Indicating whether to use the auxiliary model

To configure whether to use the auxiliary model, you use the environment variable TEXTUAL_AUX_MODEL.

The available values are:

• en_core_web_sm - This is the default value.

• none - Indicates to not use the auxiliary model.

Configuring model use for GPU

When you use a textual-ml-gpu container on accelerated hardware, you can configure:

• Whether to use the auxiliary model,

• Whether to use the date synthesis model

Indicating whether to use the auxiliary model for GPU

To configure whether to use the auxiliary model for GPU, you configure the environment variable TEXTUAL_AUX_MODEL_GPU.

By default, on GPU, Textual does not use the auxiliary model, and TEXTUAL_AUX_MODEL_GPU is false.

To use the auxiliary model for GPU, based on the configuration of TEXTUAL_AUX_MODEL, set TEXTUAL_AUX_MODEL_GPU to true.

When TEXTUAL_AUX_MODEL_GPU is true, and TEXTUAL_MULTI_LINGUAL is true, Textual also loads the multilingual models on GPU.

Indicating whether to use the date synthesis model for GPU

By default, on GPU, Textual loads the date synthesis model on GPU.

Note that this model requires 600MB of GPU RAM for each machine learning worker.

To not load the date synthesis model on GPU, set the environment variable TEXTUAL_DATE_SYNTH_GPU to false.