Update README.md

README.md

@@ -8,4 +8,19 @@ pipeline_tag: text-classification
 # BERT for hate speech classification
 The model is based on BERT and used for classifying a text as **toxic** and **non-toxic**. 
 
-The model was fine-tuned on the HateXplain dataset found here: https://huggingface.co/datasets/hatexplain
+The model was fine-tuned on the HateXplain dataset found here: https://huggingface.co/datasets/hatexplain
+
+## How to use
+
+```python
+from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline
+
+# Load model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained('tum-nlp/bert-hateXplain')
+model = AutoModelForSequenceClassification.from_pretrained('tum-nlp/bert-hateXplain')
+
+# Create the pipeline for classification
+hate_classifier = pipeline("text-classification", model=model, tokenizer=tokenizer)
+
+# Predict
+hate_classifier("Girls like attention and they get desperate")