add app.py

app.py

@@ -0,0 +1,28 @@
+import gradio as gr
+from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification
+
+# Authenticate with Hugging Face (if needed)
+# from transformers import set_token
+# set_token("your_hugging_face_token_here")
+
+# Load your self-hosted model
+model_name = "22A223R/bert-ITI110"  # Replace with your model's path
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+
+# Initialize the pipeline with your model
+classifier = pipeline("text-classification", model=model, tokenizer=tokenizer)
+
+def classify_text(text):
+    result = classifier(text)[0]
+    label = result['label']
+    score = round(result['score'], 4)
+    return f"Label: {label}, Score: {score}"
+
+iface = gr.Interface(fn=classify_text,
+                     inputs=gr.inputs.Textbox(lines=2, placeholder="Type your text here..."),
+                     outputs="text",
+                     title="Text Classification with Self-Hosted Hugging Face Model",
+                     description="This model classifies the input text. Try it out!")
+
+iface.launch()