fixed

app.py

@@ -8,9 +8,11 @@ def predict_fn(text: str) -> Tuple[Any, Any]:
     model = LongformerForSequenceClassification.from_pretrained("model")
     tokenizer = LongformerTokenizer.from_pretrained("allenai/longformer-base-4096")
     p = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)
-    results = p(text)
-    factor = 100 if results[0]['label'] == 'Hawkish' else -100
-    return results[0]['label'], round(results[0]['score'] * factor, 0)
+    results = p(text, top_k=3)
+    WEIGHTS = {"Dovish": -100, "Neutral": 0, "Hawkish": 100}
+    scores = [d["score"] * WEIGHTS.get(d["label"]) for d in results]
 
+    return results[0]["label"], round(sum(scores), 0)
 
-gr.Interface(predict_fn, "textbox", ["label", "label"]).launch()
+
+gr.Interface(predict_fn, "textbox", ["label", "label"]).launch(share=True)

model/config.json

@@ -26,17 +26,19 @@
   "hidden_act": "gelu",
   "hidden_dropout_prob": 0.1,
   "hidden_size": 768,
-   "id2label":{
-      "0":"Dovish",
-      "1":"Hawkish"
-   },
+  "id2label": {
+    "0": "Dovish",
+    "1": "Neutral",
+    "2": "Hawkish"
+  },
   "ignore_attention_mask": false,
   "initializer_range": 0.02,
   "intermediate_size": 3072,
-   "label2id":{
-      "LABEL_0":"Dovish",
-      "LABEL_1":"Hawkish"
-   },
+  "label2id": {
+    "LABEL_0": "Dovish",
+    "LABEL_1": "Neutral",
+    "LABEL_2": "Hawkish"
+  },
   "layer_norm_eps": 1e-05,
   "max_position_embeddings": 4098,
   "model_type": "longformer",

model/pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5f5daad85f1a3aedbea3d920a514def2499f5eceb60db14cebe408d8637480c3
-size 594737055
+oid sha256:f71b1e9b130a6356c987737aa2f9e9154cabff16f6c581e86548de746941f2b7
+size 594740127