Update README.md

README.md

@@ -38,3 +38,41 @@ Notes:
 - The `tokenize_chinese_chars` parameter indicates special handling for Chinese characters.
 - The maximum model length is set to 512 tokens.
 
+## Run the model
+
+```Python
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+
+model_id = "0xnu/AGTD-v0.1"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForSequenceClassification.from_pretrained(model_id)
+
+# Input text
+text = "This model trains on a diverse dataset and serves functions in applications requiring a mechanism for distinguishing between human and AI-generated text."
+
+# Preprocess the text
+inputs = tokenizer(text, return_tensors='pt')
+
+# Run the model
+outputs = model(**inputs)
+
+# Interpret the output
+logits = outputs.logits
+
+# Apply softmax to convert logits to probabilities
+probabilities = torch.softmax(logits, dim=1)
+
+# Assuming the first class is 'human' and the second class is 'ai'
+human_prob, ai_prob = probabilities.detach().numpy()[0]
+
+# Print probabilities
+print(f"Human Probability: {human_prob:.4f}")
+print(f"AI Probability: {ai_prob:.4f}")
+
+# Determine if the text is human or AI-generated
+if human_prob > ai_prob:
+    print("The text is likely human-generated.")
+else:
+    print("The text is likely AI-generated.")
+```