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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()
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