Update README.md

README.md

@@ -17,6 +17,25 @@ This model is a text classification model trained on a large dataset of comments
 
 This model is intended to be used to automatically detect and flag potentially biased language in user-generated comments in various online platforms. It can also be used as a component in a larger pipeline for text classification, sentiment analysis, or bias detection tasks.
 
+`````
+import torch
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+
+tokenizer = AutoTokenizer.from_pretrained("shainaraza/toxity_classify_debiaser")
+
+model = AutoModelForSequenceClassification.from_pretrained("shainaraza/toxity_classify_debiaser")
+
+# Test the model with a sample comment
+comment = "you are a dumb person."
+inputs = tokenizer(comment, return_tensors="pt")
+outputs = model(**inputs)
+prediction = torch.argmax(outputs.logits, dim=1).item()
+
+print(f"Comment: {comment}")
+print(f"Prediction: {'biased' if prediction == 1 else 'not biased'}")
+
+`````
+
 ## Training data
 
 The model was trained on a labeled dataset of comments from various online platforms, which were annotated as toxic or non-toxic by human annotators. The training data was cleaned and preprocessed before training, and a variety of data augmentation techniques were used to increase the amount of training data and improve the model's robustness to various types of biases.