use threshold

app.py

@@ -10,7 +10,8 @@ from transformers import CLIPProcessor, CLIPModel
 
 checkpoint = "vincentclaes/emoji-predictor"
 adjectives = pd.read_table("./adjectives.txt", header=None)[0].to_list()
-K = 4
+K = 10
+THRESHOLD = 0.05
 APP_NAME = "emoji-tagging"
 BUCKET = "drift-pilot-ml-model"
 
@@ -42,7 +43,7 @@ def get_tag(emoji, tags="", expected="", model=model, processor=processor, K=K):
     probs_formatted = torch.tensor([prob[0] for prob in probs])
     values, indices = probs_formatted.topk(K)
     return "Tag (confidence): " + ", ".join(
-        [f"{tags[i]} ({round(v.item(), 2)})" for v, i in zip(values, indices)]
+        [f"{tags[i]} ({round(v.item(), 2)})" for v, i in zip(values, indices) if v >= THRESHOLD]
     )
 
 
@@ -50,10 +51,12 @@ title = "Tagging an Emoji"
 description = """You provide an Emoji and our few-shot fine tuned CLIP model will suggest some tags that are appropriate.\n
 
 - We use the [228 most common adjectives in english](https://grammar.yourdictionary.com/parts-of-speech/adjectives/list-of-adjective-words.html).\n
-- You can also specify your own custom tags. try with; 
+- You can also specify your own custom tags. Try with; 
 
         love,hate,fun,bitterness,passion,dying,bliss
 
+- We show max 10 tags and only when the confidence is higher than 5% (0.05)
+
 """
 
 examples = [[f"emojis/{i}.png"] for i in range(32)]