Create App.py

App.py

@@ -0,0 +1,22 @@
+from transformers import TextClassificationPipeline, AutoTokenizer, AutoModelForSequenceClassification
+import gradio as gr
+
+model = AutoModelForSequenceClassification.from_pretrained("vangmayy/emotion")
+tokenizer = AutoTokenizer.from_pretrained("vangmayy/emotion")
+labels = ["sadness", "Joy", "love", "anger", "fear", "surprise"]
+label_map={
+    'LABEL_0':'Sadness',
+    'LABEL_1':'Joy',
+    'LABEL_2':'love',
+    'LABEL_3':'anger',
+    'LABEL_4':'fear',
+    'LABEL_5':'surprise'
+}
+pipe = TextClassificationPipeline(model=model, tokenizer=tokenizer, device=0)
+
+def run_inference(text):
+    emotion = label_map[pipe(text)[0]['label']]
+    return "Emotion detected: " + emotion
+
+intf = gr.Interface(fn = run_inference, inputs =["text"], outputs = ["text"], examples = ["Woah this is so cool", "I feel sad about what happened", "That room is so dark! I am not going inside"])
+intf.launch()