Update README.md

README.md

@@ -1,11 +1,14 @@
 ---
 language: en
+pipeline_tag: text-classification
+library_name: transformers
 tags:
 - medical
 - classification
 - healthcare
 - clinicalbert
 - symptom-checker
+- text-classification
 license: apache-2.0
 datasets:
 - qilex/Symptom2Disease
@@ -39,8 +42,6 @@ It has been trained on a massive merged dataset of over **96,000 patient cases**
 | 2     | 0.3092        | 0.2852          | 
 | 3     | 0.2526        | **0.2577**      | 
 
-
-
 The model achieves a final validation loss of **0.2577**, demonstrating high confidence and generalization capabilities across 115 disease classes.
 
 ## 🚀 How to Use (Python)
@@ -51,7 +52,7 @@ You can use this model directly with the Hugging Face `pipeline`.
 from transformers import pipeline
 
 # Load the pipeline
-classifier = pipeline("text-classification", model="YOUR_USERNAME/YOUR_MODEL_NAME", top_k=3)
+classifier = pipeline("text-classification", model="Iloriayomide/Symptom_Prediction", top_k=3)
 
 # Test with symptoms
 symptoms = "I have a severe headache, sensitivity to light, and I feel nauseous."