A Coding Implementation to Build a Transformer-Based Regression Language Model to Predict Continuous Values from Text
We will construct a Regression Language Model (RLM), a mannequin that predicts steady numerical values immediately from textual content sequences on this coding implementation. Instead of classifying or producing textual content, we concentrate on coaching a transformer-based structure that learns quantitative relationships hidden inside pure language descriptions. We begin by producing artificial text-to-number information, tokenizing…
