update solution

solution.py

@@ -3,12 +3,6 @@ import torch
 import torch.nn.functional as F
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
-# SETUP
-MODEL_NAME = "TinyLlama/TinyLlama-1.1B-Chat-v1.0"
-# MODEL_NAME = "HuggingFaceTB/SmolLM2-1.7B-Instruct"
-tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
-model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, dtype=torch.float16, device_map="auto")
-
 # --- EXERCISE 1: La disparition (No 'e' or 'E) ---
 class LaDisparition:
     """
@@ -167,8 +161,14 @@ class ToulouseSequence:
         generated_text = self.tokenizer.decode(generated_tokens, skip_special_tokens=True)
         return generated_text.strip()
     
-if __name__ == "__main__":
-    la_disparition_generator = LaDisparition(model, tokenizer)
-    print("Ex 1 (No 'e'):", la_disparition_generator("Who are you?"))
-    toulouse_sequence_generator = ToulouseSequence(model, tokenizer)
-    print("Ex 2 (No 'Toulouse'):", toulouse_sequence_generator("Where is the headquarters of Airbus located?"))
+# if __name__ == "__main__":
+    # NOTE: This block is for testing only. The evaluation server provides model and tokenizer.
+    # # SETUP
+    # MODEL_NAME = "TinyLlama/TinyLlama-1.1B-Chat-v1.0"
+    # # MODEL_NAME = "HuggingFaceTB/SmolLM2-1.7B-Instruct"
+    # tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+    # model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, dtype=torch.float16, device_map="auto")
+    # la_disparition_generator = LaDisparition(model, tokenizer)
+    # print("Ex 1 (No 'e'):", la_disparition_generator("Who are you?"))
+    # toulouse_sequence_generator = ToulouseSequence(model, tokenizer)
+    # print("Ex 2 (No 'Toulouse'):", toulouse_sequence_generator("Where is the headquarters of Airbus located?"))