Upload NLIScorer

README.md

@@ -9,12 +9,12 @@ metrics:
 - accuracy
 - precision
 - recall
-model-index:
-- name: ModernBERT-base-nli-clf
-  results: []
 datasets:
 - param-bharat/scorers-nli
 pipeline_tag: text-classification
+model-index:
+- name: ModernBERT-base-nli-clf
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "param-bharat/ModernBERT-base-nli-clf",
+  "_name_or_path": "param-bharat/ModernBERT-base-nli-scorer",
   "architectures": [
     "ModernBertForSequenceClassification"
   ],

pipeline.py

@@ -379,8 +379,10 @@ class NLIScorer(Pipeline):
         outputs = self.model(**model_inputs)
         return outputs
 
-    def postprocess(self, model_outputs, task_type=None):
-        if task_type is not None:
+    def postprocess(self, model_outputs, task_type=None, threshold=None):
+        if threshold is not None:
+            threshold = threshold
+        elif task_type is not None:
             threshold = TASK_THRESHOLDS[task_type]
         else:
             threshold = 0.5