added airpassengers dataset

examples/quick_start.py

@@ -0,0 +1,27 @@
+"""Quick start example for FAIM SDK."""
+
+import numpy as np
+
+from faim_sdk import Chronos2ForecastRequest, ForecastClient
+
+# Initialize client
+client = ForecastClient(api_key="your-api-key")
+
+# Prepare your time-series data
+# Shape: (batch_size, sequence_length, features)
+data = np.random.randn(32, 100, 1).astype(np.float32)
+
+# Create probabilistic forecast request
+request = Chronos2ForecastRequest(
+    x=data,
+    horizon=24,  # Forecast 24 steps ahead
+    output_type="quantiles",
+    quantiles=[0.1, 0.5, 0.9],  # 10th, 50th (median), 90th percentiles
+)
+
+# Generate forecast - model inferred automatically from request type
+response = client.forecast(request)
+
+# Access predictions
+print(response.quantiles.shape)  # (32, 24, 3, 1)
+print(response.metadata)  # Model version, inference time, etc.