Update app.py

app.py

@@ -1,34 +1,30 @@
+import torch
+from transformers import pipeline
 import gradio as gr
 import pandas as pd
+from datasets import Dataset
 
-from transformers import pipeline
-
-
-from datasets import Dataset,DatasetDict
+# Enable SafeTensors if available
+if torch.__version__ >= "1.10":
+    torch.set_safety_enabled(True)
 
+# Load the model
+model_nm = 'microsoft/deberta-v3-small'
 classifier = pipeline("text-classification", model=model_nm)
 
-
-df = pd.read_csv(path/'train.csv')
-
+# Read and preprocess data
+df = pd.read_csv("path/to/train.csv")  # Replace "path/to/train.csv" with the actual path
 df.describe(include='object')
-
 df['input'] = 'TEXT1: ' + df.context + '; TEXT2: ' + df.target + '; ANC1: ' + df.anchor
-
-df.input.head()
-
-
 ds = Dataset.from_pandas(df)
 
+# Define prediction function
 def predict_text(input_text):
     prediction = classifier(input_text)
     return prediction
 
-
-
+# Define Gradio interface
 text_input = gr.inputs.Textbox(lines=7, label="Unesite tekst")
 output_text = gr.outputs.Textbox(label="Predikcija")
-
 gr.Interface(predict_text, inputs=text_input, outputs=output_text).launch()
 
-