initial file commit

application.py

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+from transformers import pipeline
+
+## Downlaod the PreTrained Model from the Online Repository
+model = pipeline(
+    "text-classification",
+    model="badmatr11x/roberta-base-emotions-detection-from-text"
+)
+
+
+def app():
+    """This Function takes input from the user
+        and clssify it into different range of emotions.
+
+    Raises:
+        IOError: Raise an IOError if user input can't convert into the string instance.
+    """
+    # Get user input
+    try:
+        user_input = str(input("Enter Text Here: "))
+    except:
+        raise IOError("There is some problem reading text from the console.")
+
+    # Classify the text using the Huggingface model
+    if user_input:
+        result = model(user_input)
+    else:
+        print("No User Input is Provided.")
+
+    print(result)
+
+
+if __name__ == "__main__":
+    ## Driver Function
+    app()

requirements.txt

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+datasets
+transformers
+scikit-learn
+wandb