Views
No views yet
| Prediction | Tweet |
|---|---|
| sexist | Every woman wants to be a model. It's codeword for "I get everything for free and people want me" |
| not sexist | basically I placed more value on her than I should then? |
1from transformers import AutoModelForSequenceClassification, AutoTokenizer,pipeline
2import torch
3model = AutoModelForSequenceClassification.from_pretrained('sana-ngu/BERTweet-large-sexism-detector')
4tokenizer = AutoTokenizer.from_pretrained('vinai/bertweet-large')
5classifier = pipeline("text-classification", model=model, tokenizer=tokenizer)
6prediction=classifier("Every woman wants to be a model. It's codeword for 'I get everything for free and people want me' ")
7label_pred = 'not sexist' if prediction == 0 else 'sexist'
8
9print(label_pred)