Update README.md

README.md

@@ -17,6 +17,48 @@ tags:
 - classification
 ---
 
+**How to Use the Model for Inference:**
+
+You can use the Hugging Face `pipeline` for easy inference:
+
+```python
+from transformers import pipeline
+
+# Load the model
+model_path = "venkatd/NCBI_NER"
+pipe = pipeline(
+    task="token-classification",
+    model=model_path,
+    tokenizer=model_path,
+    aggregation_strategy="simple"
+)
+
+# Test the pipeline
+text = ("A 48-year-old female presented with vaginal bleeding and abnormal Pap smears. "
+        "Upon diagnosis of invasive non-keratinizing SCC of the cervix, she underwent a radical "
+        "hysterectomy with salpingo-oophorectomy which demonstrated positive spread to the pelvic "
+        "lymph nodes and the parametrium.")
+result = pipe(text)
+print(result)
+```
+
+**Output Example:**
+
+The output will be entity type of Disease, score, and start/end positions in the text. Here’s a sample output format:
+
+```json
+[
+    {
+        "entity_group": "Disease",
+        "score": 0.98,
+        "word": "SCC of the cervix",
+        "start": 121,
+        "end": 139
+    },
+    ...
+]
+```
+
 
 **Model Summary and Training Details**