Upload test_single_sample.py with huggingface_hub

test_single_sample.py

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+#!/usr/bin/env python3
+"""
+Quick test script to run inference on a single training sample
+"""
+
+import json
+import sys
+from pathlib import Path
+
+# Add scripts to path
+sys.path.insert(0, str(Path(__file__).parent / "scripts" / "inference"))
+
+from inference_codellama import load_local_model, generate_with_local_model
+
+def main():
+    # Paths
+    script_dir = Path(__file__).parent
+    model_path = script_dir / "training-outputs" / "codellama-fifo-v1"
+    base_model_path = script_dir / "models" / "base-models" / "CodeLlama-7B-Instruct"
+    train_dataset = script_dir / "datasets" / "processed" / "split" / "train.jsonl"
+    
+    # Load first sample from training data
+    print("=" * 80)
+    print("📚 Loading sample from training dataset...")
+    print("=" * 80)
+    
+    with open(train_dataset, 'r') as f:
+        first_line = f.readline()
+        sample = json.loads(first_line)
+    
+    instruction = sample.get("instruction", "")
+    expected_response = sample.get("response", "")
+    
+    print("\n📝 Instruction:")
+    print("-" * 80)
+    print(instruction)
+    print("-" * 80)
+    
+    print("\n🎯 Expected Response (first 500 chars):")
+    print("-" * 80)
+    print(expected_response[:500])
+    if len(expected_response) > 500:
+        print("...")
+    print("-" * 80)
+    
+    # Load model
+    print("\n" + "=" * 80)
+    print("📦 Loading model...")
+    print("=" * 80)
+    
+    model, tokenizer = load_local_model(
+        str(model_path),
+        str(base_model_path) if base_model_path.exists() else None,
+        use_quantization=None,
+        merge_weights=False
+    )
+    
+    print("✅ Model loaded!\n")
+    
+    # Generate
+    print("=" * 80)
+    print("🤖 Generating response...")
+    print("=" * 80)
+    print()
+    
+    try:
+        generated_response = generate_with_local_model(
+            model,
+            tokenizer,
+            instruction,
+            max_new_tokens=800,
+            temperature=0.3,
+            stream=False
+        )
+        
+        print("\n" + "=" * 80)
+        print("✅ GENERATED OUTPUT:")
+        print("=" * 80)
+        print(generated_response)
+        print("=" * 80)
+        print(f"\n📊 Output length: {len(generated_response)} characters")
+        
+    except Exception as e:
+        print(f"\n❌ Error: {e}")
+        import traceback
+        traceback.print_exc()
+
+if __name__ == "__main__":
+    main()
+