![]() ![]() ![]() Here is an example of generation for Wikipedia page disambiguation: from transformers import AutoTokenizer, AutoModelForSeq2SeqLM Please consider citing our works if you use code from this repository. This model was trained on the full training set of BLINK (i.e., 9M datapoints for entity-disambiguation grounded on Wikipedia). The model was first released in the facebookresearch/GENRE repository using fairseq (the transformers models are obtained with a conversion script similar to this. GENRE performs retrieval generating the unique entity name conditioned on the input text using constrained beam search to only generate valid identifiers. In a nutshell, GENRE uses a sequence-to-sequence approach to entity retrieval (e.g., linking), based on fine-tuned BART architecture. The GENRE (Generative ENtity REtrieval) system as presented in Autoregressive Entity Retrieval implemented in pytorch.
0 Comments
Leave a Reply. |