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TLT/Jarvis - Named Entity Recognition

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Description

This collection contains models and notebooks for Token Classification training and deployment with TLT and Jarvis respectively

Curator

NVIDIA

Modified

July 28, 2021
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Helm Charts
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Token Classification Collection

This page contains the information about the Token Classification collection with TLT.

NGC Model Collection: Token Classification ==========================================

Overview --------

This collection contains end-to-end neural models for Token Classification Tasks using the Transfer Learning Toolkit (TLT). The TokenClassification Model in TLT supports Named entity recognition (NER), part-of-speech tagging and other token level classification tasks.

Available Models ----------------

For instructions on how to use a model, please see its corresponding model card page.

References ----------

Suggested Reading -----------------

Ethical AI ----------

NVIDIA’s platforms and application frameworks enable developers to build a wide array of AI applications. Consider potential algorithmic bias when choosing or creating the models being deployed. Work with the model’s developer to ensure that it meets the requirements for the relevant industry and use case; that the necessary instruction and documentation are provided to understand error rates, confidence intervals, and results; and that the model is being used under the conditions and in the manner intended.