Papers by Colton Chapin
An Architecture for Accelerated Large-Scale Inference of Transformer-Based Language Models (2021.naacl-industry)
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| Challenge: | a recent paper shows that attention-based language models can be used to train, evaluate, and perform inference on predictive models. |
| Approach: | They develop a machine learning architecture that can scale to a large volume of requests . they use a BERT model that is fine-tuned for emotion analysis . |
| Outcome: | The proposed architecture can scale to a large volume of requests with a minimum of 96 hours of running time. |