used native setfit head

README.md

@@ -99,7 +99,8 @@ classifier.to(device);
 mentions = ["working class people", "highly-educated professionals", "people without a stable job"]
 
 # Get predictions
-predictions = classifier.predict(mentions)
+with torch.no_grad():
+    predictions = classifier.predict(mentions)
 print(predictions)
 
 # Map predictions to labels
@@ -128,7 +129,8 @@ model = SentenceTransformer(model_name, device=device)
 mentions = ["working class people", "highly-educated professionals", "people without a stable job"]
 
 # Compute mention embeddings
-embeddings = model.encode(mentions)
+with torch.no_grad():
+    embeddings = model.encode(mentions)
 ````
 
 ## Training Details

config_setfit.json

@@ -1,4 +1,5 @@
 {
+  "normalize_embeddings": true,
   "labels": [
     "noneconomic__age",
     "noneconomic__crime",
@@ -10,6 +11,5 @@
     "noneconomic__place_location",
     "noneconomic__religion",
     "noneconomic__shared_values_mentalities"
-  ],
-  "normalize_embeddings": true
+  ]
 }

model_head.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:fa887ba37a9712fdad200062462031737e1ac7143cf0349d590de2e3cc57826a
-size 32270
+oid sha256:08e357b2020d40ddff8e26feae50c6b609c50049f075421a9a2f75134ee3eb53
+size 32266