Update README.md

README.md

@@ -42,26 +42,21 @@ regression_config_path = hf_hub_download(
 with open(regression_config_path, "r") as f:
     regression_config = json.load(f)
 
-
 def inverse_scale(prediction, config):
     """apply inverse scaling to a prediction"""
     min_value, max_value = config["min_value"], config["max_value"]
     return prediction * (max_value - min_value) + min_value
 
-
-def predict_with_pipeline(text, pipe, config, ndigits=4):
-    result = pipe(text, truncation=True)[0]  # Get the first (and likely only) result
-    score = result["score"] if result["label"] == "LABEL_1" else 1 - result["score"]
-    # Apply inverse scaling
-    scaled_score = inverse_scale(score, config)
+def predict_with_pipeline(text, pipe, config, ndigits=5):
+    result = pipe(text, truncation=True)[0] 
+    scaled_score = inverse_scale(result['score'], config)
     return round(scaled_score, ndigits)
 
-
 text = "This is an example text for regression prediction."
 
 # Get predictions
 predictions = predict_with_pipeline(text, pipe, regression_config)
-print("Predicted returns (frec):", predictions)
+print("Predicted Value:", predictions)
 ```
 
 </details>