app

app.py

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+import tensorflow as tf
+from transformers import TFDistilBertForSequenceClassification, DistilBertTokenizerFast
+import gradio as gr
+import random
+
+# Load the model architecture and weights
+model = TFDistilBertForSequenceClassification.from_pretrained("spam_detection_model/")
+
+# Load the tokenizer
+tokenizer = DistilBertTokenizerFast.from_pretrained("distilbert-base-uncased")
+
+
+# Define the process_input function
+def process_input(text):
+    # Preprocess the sample text using the tokenizer
+    encodings = tokenizer(text, truncation=True, padding=True, return_tensors="tf")
+
+    # Perform inference
+    logits = model(encodings.input_ids).logits
+
+    # Convert logits to probabilities using softmax
+    probabilities = tf.nn.softmax(logits, axis=-1)
+
+    # Get the predicted class
+    predicted_class = tf.argmax(probabilities, axis=-1).numpy()[0]
+
+    # Map the predicted class to label
+    label_mapping = {
+        0: '<b><div style="font-size:16px; text-align:center;">No need to worry, Not a spam message.</div></b>',
+        1: '<b><div style="font-size:16px; color:#ff3b5c; text-align:center;">Warning⚠️: This message has been identified as spam.</div></b>',
+    }
+    predicted_label = label_mapping[predicted_class]
+
+    return [
+        {
+            "Spam": float(probabilities.numpy()[0][1]),
+            "Not a Spam": float(probabilities.numpy()[0][0]),
+        },
+        predicted_label,
+    ]
+
+
+# Define the Gradio interface
+title = "Spam Detector⚠️"
+examples = [
+    "Dear Customer, Your account has been compromised. Click the link below to verify your account details immediately or risk suspension. **(Example 1)**",
+    "You've been selected as the lucky winner of our international sweepstakes! To claim your prize, reply with your full name, address, and bank details. <font color='blue' style='background-color: lightgray;'>(Example 2)</font>",
+    "Congratulations! You've won a free iPhone X. Click the link to claim your prize.",
+    "URGENT: Your bank account has been compromised. Click here to reset your password.",
+    "Get rich quick! Invest in our exclusive program and earn thousands overnight.",
+    "Your prescription refill is ready for pickup at your local pharmacy. Visit us at your convenience",
+    "Reminder: Your monthly utility bill is due on August 20th. Please make the payment.",
+    "You've been selected as the lucky winner of a million-dollar lottery. Reply to claim.",
+    "Limited time offer: Double your money with our amazing investment opportunity.",
+    "Hi, just checking in to see how you're doing. Let's catch up soon.",
+    "Reminder: Your dentist appointment is scheduled for tomorrow at 2 PM.",
+    "Invitation: Join us for a webinar on digital marketing strategies. Register now!",
+    "Your application for the scholarship has been reviewed. We're pleased to inform you that you've been selected.",
+    "Hi there! Just wanted to check in and see how you're doing.",
+    "Reminder: Your friend's birthday is coming up. Don't forget to send them a message.",
+    "Thank you for your purchase. Your order has been successfully processed.",
+    "Your monthly newsletter is here! Stay updated with the latest news and updates.",
+    "Invitation: Join us for a community clean-up event this weekend. Let's make a difference together.",
+    "Reminder: Your scheduled appointment is tomorrow. We look forward to seeing you.",
+    "Good news! You've earned a reward for your loyalty. Check your account for details.",
+    "Your recent transaction has been approved. Please keep this email for your records.",
+    "Exciting announcement: Our new store location is now open. Visit us and receive a special discount.",
+    "Welcome to our online community! Here's how to get started and connect with others.",
+    "Your request has been received and is being processed. We'll update you with the status soon.",
+    "Upcoming event: Join us for a free cooking class this Saturday. Learn new recipes and techniques.",
+    "Reminder: Don't forget to vote in the upcoming election. Your voice matters.",
+    "Join our book club and dive into a world of fascinating stories. Here's how to join.",
+]
+
+
+# Create Gradio components
+input_text = gr.Textbox(
+    lines=3, label="Enter the SMS/Message/Email you received", autofocus=True
+)
+output_text = gr.HTML("", label="Output")
+probabilities_text = gr.Label("", label="Probabilities")
+
+random.shuffle(examples)
+
+# Initialize the Gradio interface
+model_gui = gr.Interface(
+    fn=process_input,
+    inputs=input_text,
+    outputs=[probabilities_text, output_text],
+    title=title,
+    examples=examples,
+    interpretation="default",
+    theme="shivi/calm_seafoam",
+    css="""*{font-family:'IBM Plex Mono';}""",
+    examples_per_page=15,
+)
+
+# Launch the Gradio interface
+print("add '/?__theme=dark' to URL for rendering in dark theme.")
+model_gui.launch()

spam_detection_model/config.json

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+{
+  "_name_or_path": "distilbert-base-uncased",
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForSequenceClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_dim": 3072,
+  "initializer_range": 0.02,
+  "max_position_embeddings": 512,
+  "model_type": "distilbert",
+  "n_heads": 12,
+  "n_layers": 6,
+  "pad_token_id": 0,
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": false,
+  "tie_weights_": true,
+  "transformers_version": "4.31.0",
+  "vocab_size": 30522
+}

spam_detection_model/tf_model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:74b314fc3657a9f17379df8e858949536024f0cd090962752662e0479c948162
+size 267951808