Update app.py

app.py

@@ -1,9 +1,6 @@
-# import gradio as gr
-
-# gr.Interface.load("models/at2507/zeroshot_finetuned_sentiment").launch()
-
 import gradio as gr
 from transformers import AutoTokenizer
+import timm
 
 title = "Finetuning [BERT] on A Financial News Sentiment Dataset"
 description = """
@@ -18,7 +15,9 @@ article = "Check out the dataset that [BERT cased]((https://huggingface.co/bert-
 
 
 def sentiment_analyzer(tweet):
-  model = model.load("models/at2507/zeroshot_finetuned_sentiment")
+  model_reloaded = timm.create_model('hf_hub:at2507/zeroshot_finetuned_sentiment', pretrained=True)
+  # model = model.load("models/at2507/zeroshot_finetuned_sentiment")
+  # gr.Interface.load("models/at2507/zeroshot_finetuned_sentiment").launch()
   tokenizer = AutoTokenizer.from_pretrained("bert-base-cased")
   zeroshotsent_model = pipeline("text-classification", model = model.to('cpu:0'), tokenizer=tokenizer)
   return zeroshotsent_model(tweet)
@@ -33,4 +32,3 @@ gr.Interface(
     examples=[["CLNE, TRXC, TGE and ADMS among midday movers"], 
      ["CRISPR Therapeutics among healthcare gainers; Plus Therapeutics leads the losers"]],
 ).launch()
-