In this session we will see how to do transfer learning over a state-of-the-art pre-trained model like RoBERTa to achieve our own goal in Named Entity Recognition with our own DataSet. We will take and label new data to finally feed the network trying to achieve transfer learning. Then we will make use of the new fine tuned weights and use FastAPI to deploy our new fine tuned model to kubernetes to make inference.
We will be playing with Spacy, huggingface, pytorch, python, FastAPI, Azure Kubernetes Services, CUDA hardware and terraform :)