AI_text_detector

Detect AI-generated text using a Hugging Face model. This tool analyzes input and returns how likely it was written by AI vs a human. Built with Gradio.

AI_text_detector

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+import gradio as gr
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+import torch
+
+# Load model and tokenizer
+model_name = "roberta-base-openai-detector"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+
+def detect_ai(text):
+    inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=512)
+    with torch.no_grad():
+        outputs = model(**inputs)
+        logits = outputs.logits
+        probs = torch.softmax(logits, dim=1)
+        ai_score = probs[0][1].item() * 100
+        human_score = probs[0][0].item() * 100
+
+    result = f"AI-generated: {ai_score:.2f}%\\nHuman-written: {human_score:.2f}%"
+    return result
+
+iface = gr.Interface(
+    fn=detect_ai,
+    inputs=gr.Textbox(label="Enter text to analyze", lines=10),
+    outputs=gr.Textbox(label="Detection Result"),
+    title="AI Detector",
+    description="Detect if a piece of text was written by AI or a human using a Hugging Face model."
+)
+
+iface.launch()