IMPARA QE
Collection
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How to use gotutiyan/IMPARA-QE with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="gotutiyan/IMPARA-QE") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("gotutiyan/IMPARA-QE")
model = AutoModelForSequenceClassification.from_pretrained("gotutiyan/IMPARA-QE")A trained QE model for IMPARA, a reference-less performance measure for GEC task.
This model achieves 95.93 for Pearson's correlation and 93.01 for Spearman's, for Grundkiewicz +15's Expected Wins score (Note that bert-base-cased is used for SE model).
You can see the detail in this GitHub repository, e.g. How to use this model.