# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("His-Wardship/sarcasm-detector")
model = AutoModelForSequenceClassification.from_pretrained("His-Wardship/sarcasm-detector")Quick Links
A sarcasm detector built in an hour. Base model is microsoft/deberta-v3-base.
Training Dataset: Sarcasm Corpus V2 - Oraby, Vrindavan Harrison, Lena Reed, Ernesto Hernandez, Ellen Riloff and Marilyn Walker. "Creating and Characterizing a Diverse Corpus of Sarcasm in Dialogue." In The 17th Annual SIGdial Meeting on Discourse and Dialogue (SIGDIAL), Los Angeles, California, USA, 2016.
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="His-Wardship/sarcasm-detector")