F Coref: Fast, Accurate and Easy to Use Coreference Resolution F Coref allows to process 2.8K OntoNotes documents in 25 seconds on a V100 GPU (compared to 6 minutes for the LingMess model, and to 12 minutes of the popular AllenNLP coreference model) with only a modest drop in accuracy. The fast speed is achieved through a combination of distillation of a compact model from the LingMess model, and an efficient batching implementation using a technique we call leftover Please check the official repository for more details and updates. Experiments Model Runtime Memory Joshi et al. (2020) 12:06 27.4 Otmazgin et al. (2022) 06:43 4.6 + Batching 06:00 6.6 Kirstain et al. (2021) 04:37 4.4 Dobrovolskii (2021) 03:49 3.5 F Coref 00:45 3.3 + Batching 00:35 4.5 + Leftovers batching 00:25 4.0 The inference time(Min:Sec) and memory(GiB) for each model on 2.8K documents. Average of 3 runs. Hardware, NVIDIA Tesla V100 SXM2. Citation F coref: Fast, Accurate and Easy to Use Coreference Resolution (Otmazgin et al., AACL IJCNLP 2022)
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