Upload examples/basic_usage.py with huggingface_hub

examples/basic_usage.py

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+"""
+Basic usage examples for DOM KNN models from Hugging Face Hub.
+
+This script demonstrates how to load and use the models for formula assignment.
+"""
+
+from transformers import AutoModel
+import numpy as np
+
+
+def example_1_default_model():
+    """Load the default best-performing model."""
+    print("=" * 60)
+    print("Example 1: Loading default model (21T, K=1, Euclidean)")
+    print("=" * 60)
+    
+    model = AutoModel.from_pretrained(
+        "SaeedLab/dom-formula-assignment-using-knn",
+        trust_remote_code=True
+    )
+    
+    print(f"[OK] Model loaded successfully")
+    print(f"  Config: {model.config}")
+    print()
+
+
+def example_2_variant_by_parameters():
+    """Load a specific variant using parameters."""
+    print("=" * 60)
+    print("Example 2: Loading variant by parameters")
+    print("=" * 60)
+    
+    model = AutoModel.from_pretrained(
+        "SaeedLab/dom-formula-assignment-using-knn",
+        data_source="7T-21T",
+        k_neighbors=1,
+        metric="euclidean",
+        training_version="ver3",
+        trust_remote_code=True
+    )
+    
+    print(f"[OK] Model loaded successfully")
+    print(f"  Data source: 7T-21T")
+    print(f"  K neighbors: 1")
+    print(f"  Metric: euclidean")
+    print(f"  Training version: ver3")
+    print()
+
+
+def example_3_variant_by_name():
+    """Load a specific variant by direct name."""
+    print("=" * 60)
+    print("Example 3: Loading variant by name")
+    print("=" * 60)
+    
+    model = AutoModel.from_pretrained(
+        "SaeedLab/dom-formula-assignment-using-knn",
+        variant="knn_21T_k3_manhattan",
+        trust_remote_code=True
+    )
+    
+    print(f"[OK] Model loaded: knn_21T_k3_manhattan")
+    print(f"  Config: {model.config}")
+    print()
+
+
+def example_4_make_predictions():
+    """Make predictions with the model."""
+    print("=" * 60)
+    print("Example 4: Making predictions")
+    print("=" * 60)
+    
+    # Load model
+    model = AutoModel.from_pretrained(
+        "SaeedLab/dom-formula-assignment-using-knn",
+        trust_remote_code=True
+    )
+    
+    # Create sample data (replace with your actual mass spec features)
+    # Features might include: m/z, O/C ratio, H/C ratio, N/C ratio, etc.
+    X_sample = np.array([
+        [300.1234, 0.5, 1.2, 0.1],  # Sample 1
+        [450.6789, 0.6, 1.5, 0.2],  # Sample 2
+        [275.5432, 0.4, 1.1, 0.0],  # Sample 3
+    ])
+    
+    print(f"Input shape: {X_sample.shape}")
+    print(f"Making predictions...")
+    
+    # Get predictions
+    predictions = model(X_sample)
+    
+    print(f"[OK] Predictions shape: {predictions.shape}")
+    print(f"  First 3 predictions: {predictions[:3]}")
+    print()
+
+
+def example_5_compare_models():
+    """Compare predictions from different model variants."""
+    print("=" * 60)
+    print("Example 5: Comparing model variants")
+    print("=" * 60)
+    
+    # Sample data
+    X_sample = np.array([[300.1234, 0.5, 1.2, 0.1]])
+    
+    variants = [
+        ("21T K=1 Euclidean", {"variant": "knn_21T_k1_euclidean"}),
+        ("21T K=3 Manhattan", {"variant": "knn_21T_k3_manhattan"}),
+        ("7T-21T K=1 Euclidean", {
+            "data_source": "7T-21T",
+            "k_neighbors": 1,
+            "metric": "euclidean",
+            "training_version": "ver3"
+        }),
+    ]
+    
+    for name, params in variants:
+        model = AutoModel.from_pretrained(
+            "SaeedLab/dom-formula-assignment-using-knn",
+            trust_remote_code=True,
+            **params
+        )
+        pred = model(X_sample)
+        print(f"  {name}: {pred[0]}")
+    
+    print()
+
+
+if __name__ == "__main__":
+    print("\n" + "=" * 60)
+    print("DOM KNN Models - Usage Examples")
+    print("=" * 60 + "\n")
+    
+    try:
+        example_1_default_model()
+        example_2_variant_by_parameters()
+        example_3_variant_by_name()
+        example_4_make_predictions()
+        example_5_compare_models()
+        
+        print("=" * 60)
+        print("[OK] All examples completed successfully!")
+        print("=" * 60)
+        
+    except Exception as e:
+        print(f"\n[ERROR] Error: {e}")
+        print("\nNote: These examples require the model to be uploaded to")
+        print("      Hugging Face Hub at: SaeedLab/dom-formula-assignment-using-knn")
+        print("\nFor local testing, replace the repo ID with a local path.")