Update for malaylam news classifier

app.py

@@ -1,11 +1,26 @@
-import gradio as gr
+from huggingface_hub import from_pretrained_fastai
 
 
-def greet(name):
-    return "Hello " + name
+LABELS = Path('class_names.txt').read_text().splitlines()
 
 
-# We instantiate the Textbox class
-textbox = gr.Textbox(label="Type your name here:", placeholder="Rajesh Radhakrishnan", lines=2)
 
-gr.Interface(fn=greet, inputs=textbox, outputs="text").launch()
+def predict(im):
+    learner = from_pretrained_fastai("rajeshradhakrishnan/ml-news-classify-fastai")
+
+    probabilities = learner.predict(sentences)
+
+    values, indices = torch.topk(probabilities, 5)
+
+    return {LABELS[i]: v.item() for i, v in zip(indices, values)}
+
+interface = gr.Interface(
+    predict, 
+    inputs="newsheadlines", 
+    outputs='label', 
+    theme="huggingface", 
+    title="Sketch Recognition", 
+    description="Malayalam News Classifier? Input a few malayalam news headlines and verify whether the model categorized it apporpirately!", 
+    article = "<p style='text-align: center'>Malayalam News Classifier | Demo Model</p>",
+    live=True)
+interface.launch(debug=True)

class_names.txt

@@ -0,0 +1,4 @@
+business
+entertainment
+sports
+technology

requirements.txt

@@ -0,0 +1,2 @@
+huggingface_hub[fastai]
+ohmeow-blurr