Increase logits sensitivity, fix typo

pipeline.py

@@ -41,10 +41,10 @@ class PreTrainedPipeline():
         similarities = distance.cdist(embeddings.reshape((1,300)), self.comparisons, "cosine")[0]
         top_indices = similarities.argsort()[:10]
         top_words = [self.id2h[str(top_indices[i])] for i in range(10)]
-        logits = np.exp(-10*np.array(similarities[top_indices]))
+        logits = np.exp(-1000*np.array(similarities[top_indices]))
         softmax_probs = tf.nn.softmax(logits).numpy()
         top_scores = [round(float(softmax_probs[i]), 3) for i in range(10)]
         
         return [
-            [{'lable': word, 'score': score} for word, score in zip(top_words, top_scores)]
+            [{'label': word, 'score': score} for word, score in zip(top_words, top_scores)]
         ]