Based on the Pytorch-Transformers library by HuggingFace. To be used as a starting point for employing Transformer models in text classification tasks. Contains code to easily train BERT, XLNet, RoBERTa, and XLM models for text classification.
Question: After I've fine-tuned a roberta model for sentence classification, how do I run inference on a sample sentence in real-time? Is there a specific function in your code base you can point me to?
This repo doesn't really have built-in support for that, although it shouldn't be hard to implement. I recommend you use Simple Transformers, which does support this (and a lot more) out of the box.
Hello Thilina, thank you for this repo.
Question: After I've fine-tuned a roberta model for sentence classification, how do I run inference on a sample sentence in real-time? Is there a specific function in your code base you can point me to?