# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("s-nlp/lewit-informal-tagger")
model = AutoModelForTokenClassification.from_pretrained("s-nlp/lewit-informal-tagger", device_map="auto")Quick Links
This is an auxilary model for content preserving formality transfer model LEWIP-informal. This particular model classifies the tokens from the source formal text and label them as keep or delete/replace. These labels are further used by LEWIP-informal to generate content preserving informal paraphrases.
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="s-nlp/lewit-informal-tagger")