raquiba/sarcasm-detection-BanglaSARC
from transformers import AutoTokenizer, AutoModelForSequenceClassification ironyname = "raquiba/sarcasm-detection-BanglaSARC" tokenizerirony = AutoTokenizer.frompretrained(ironyname) modelirony = AutoModelForSequenceClassification.frompretrained(ironyname) ironypipeline = pipeline("sentiment-analysis", model=modelirony, tokenizer=tokenizerirony, device=0,max_length=512, padding=True, truncation=True)
#Model Evaluation tokenizer = AutoTokenizer.frompretrained(ironyname) dftrain, dftest = tokenizeddata(dfeval) modelirony = AutoModelForSequenceClassification.frompretrained(ironyname, numlabels=2, ignoremismatchedsizes=True).to(device) trainingargs = TrainingArguments("test-trainer-banglaBERT", {'reprocessinputdata': True}, evaluationstrategy="epoch") trainer_irony.train()
