Sentiment analysis demo

app.py

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+import gradio as gr
+import torch
+from transformers import pipeline
+
+
+pipe = pipeline("text-classification",  # tarea a realizar
+            model="distilbert/distilbert-base-uncased-finetuned-sst-2-english",  # modelo a utilizar
+            torch_dtype=torch.bfloat16,)   #
+
+
+def text_classification(text):
+    result = pipe(text)
+    return result[0]['label']
+
+
+examples = ['You are the evil!', 'Doing great boy!']
+
+demo = gr.Interface(fn=text_classification,
+                    inputs= gr.Textbox(lines=2, label="Text", placeholder="Enter text here..."), 
+                    outputs=gr.Textbox(lines=2, label="Text Classification Result"),
+                    description="Enter a text and see the sentiment classification result!",
+                    examples=examples,
+                    title="Sentiment Classification")
+
+demo.launch()

requirements.txt

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+transformers
+torch
+gradio