Create model_2_of_10.safetensors

model_2_of_10.safetensors

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+import torch
+from safetensors.torch import load_model, save_model
+import logging
+
+# Logging setup
+logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
+
+class CharmModel:
+    """Handles loading and saving advanced safetensors models for Charm 15."""
+
+    def __init__(self, model_path: str):
+        self.model_path = model_path
+        self.model = None
+
+    def load(self):
+        """Loads Model 2 of 10 safely with optimized memory handling."""
+        try:
+            logging.info(f"Loading model from {self.model_path}...")
+            self.model = load_model(torch.nn.Module(), self.model_path)
+            logging.info("Model loaded successfully.")
+        except Exception as e:
+            logging.error(f"Error loading model: {e}")
+
+    def save(self, save_path: str):
+        """Saves the model safely in safetensors format."""
+        if self.model:
+            try:
+                logging.info(f"Saving model to {save_path}...")
+                save_model(self.model, save_path)
+                logging.info("Model saved successfully.")
+            except Exception as e:
+                logging.error(f"Error saving model: {e}")
+        else:
+            logging.warning("No model loaded. Cannot save.")
+
+    def infer(self, input_data):
+        """Runs inference on the loaded model (Placeholder for actual logic)."""
+        if self.model:
+            logging.info("Running inference...")
+            # Implement AI logic here (depends on actual model architecture)
+            return "Inference result"
+        else:
+            logging.warning("No model loaded. Cannot perform inference.")
+            return None