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Word embeddings can then be used to predict numerical variables, computesemantic similarity scores across texts, visually represent statistically significant words across multiple dimensions, and much more. Hugging Face transformer models BERT, GPT-2, RoBERTa, and T5 are included in the library.
The pre-train and fine-tune paradigm, exemplified by models like ELMo and BERT, has evolved into prompt-based reasoning used by the GPT family. Techniques such as BERTSCORE and BARTSCORE employ smaller models to computesemantic similarity and evaluate texts from various perspectives.
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