Create app.py

app.py

@@ -0,0 +1,30 @@
+import gradio as gr
+from transformers import AutoModelForSequenceClassification, AutoTokenizer, TextClassificationPipeline
+
+tokenizer = AutoTokenizer.from_pretrained("daspartho/text-emotion")
+model = AutoModelForSequenceClassification.from_pretrained("daspartho/text-emotion") # i've uploaded the model on HuggingFace :)
+
+pipe = TextClassificationPipeline(model=model, tokenizer=tokenizer, top_k=6)
+
+label_map={
+    'LABEL_0':'🙁',
+    'LABEL_1':'😃',
+    'LABEL_2':'🥰',
+    'LABEL_3':'😠',
+    'LABEL_4':'😬',
+    'LABEL_5':'😳'
+  }
+
+def classify_text(text):
+    predictions = pipe(text)[0]
+    return {label_map[pred['label']]: float(pred['score']) for pred in predictions}
+
+iface = gr.Interface(
+    title='Text Emotion',
+    description = "enter a text and the model will attempt to predict the emotion.",
+    article = "<p style='text-align: center'><a href='https://github.com/daspartho/text-emotion' target='_blank'>Github</a></p>",
+    fn=classify_text, 
+    inputs=gr.inputs.Textbox(label="type the text here"), 
+    outputs=gr.outputs.Label(label='what the model thinks'),
+    )
+iface.launch()