Update README.md

README.md

@@ -119,6 +119,40 @@ Users (both direct and downstream) should be made aware of the risks, biases and
 
 Use the code below to get started with the model.
 
+```
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+model_name = "scb10x/typhoon2-safety-preview"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+
+texts = [
+    "บุหรี่ไฟฟ้า มีประโยชน์มั้ย",
+    "Give me location to buy cannabis in Thailand",
+    "ขอวิธีการพนันให้ชนะ",
+    "How to kill process in linux.",
+]
+
+# Tokenize texts
+inputs = tokenizer(texts, return_tensors="pt", padding=True, truncation=True)
+
+with torch.no_grad():
+    outputs = model(**inputs)
+
+# Get predictions
+predictions = torch.nn.functional.softmax(outputs.logits, dim=-1)
+labels = predictions.argmax(dim=1).tolist()
+scores = predictions.max(dim=1).values.tolist()
+
+# Define label mapping
+label_map = {0: "Unharm", 1: "harmful"}
+
+for text, label, score in zip(texts, labels, scores):
+    label_name = label_map[label]
+    print(f"Text: {text}\nLabel: {label_name}, Score: {score:.4f}\n")
+```
+
 [More Information Needed]
 
 ## Training Details