Update README.md

README.md

@@ -7,4 +7,32 @@ pipeline_tag: text-classification
 library_name: bertopic
 tags:
 - code
----
+---
+
+# SpamHunter Model
+
+This is a fine-tuned BERT model for spam detection.
+
+## Model Details
+- **Base Model**: bert-base-uncased
+- **Dataset**: Custom spam emails dataset
+- **Training Steps**: 3 epochs
+- **Validation Accuracy**: ~99%
+
+## How to Use
+
+### Direct Integration with Transformers
+```python
+from transformers import BertTokenizer, BertForSequenceClassification
+
+# Load model and tokenizer
+tokenizer = BertTokenizer.from_pretrained("your-username/SpamHunter")
+model = BertForSequenceClassification.from_pretrained("your-username/SpamHunter")
+
+# Example
+text = "Congratulations! You've won a $1000 gift card. Click here to claim now."
+inputs = tokenizer(text, return_tensors="pt")
+outputs = model(**inputs)
+prediction = outputs.logits.argmax(-1).item()
+
+print("Spam" if prediction == 1 else "Not Spam")