diff --git a/train_test/test.cpp b/train_test/test.cpp
deleted file mode 100644
index 41e25e7..0000000
--- a/train_test/test.cpp
+++ /dev/null
@@ -1,96 +0,0 @@
-#include <algorithm>
-#include <csignal>
-#include <fstream>
-#include <iostream>
-#include <map>
-#include <set>
-#include <string>
-#include <torch/script.h>
-#include <vector>
-
-bool running = true;
-void handle_sigint(int)
-{
-      std::cout << "\n\n[Stopped by user]\n";
-      running = false;
-}
-
-std::map<int, char> build_vocab(const std::string &path)
-{
-      std::ifstream file(path);
-      if (!file.is_open())
-      {
-            std::cerr << "[Error] Cannot open: " << path << "\n";
-            exit(1);
-      }
-      std::string text((std::istreambuf_iterator<char>(file)), std::istreambuf_iterator<char>());
-
-      std::set<char> char_set(text.begin(), text.end());
-      std::vector<char> chars(char_set.begin(), char_set.end());
-      std::sort(chars.begin(), chars.end());
-
-      std::map<int, char> it;
-      for (int i = 0; i < (int)chars.size(); i++)
-            it[i] = chars[i];
-
-      return it;
-}
-
-int main()
-{
-      signal(SIGINT, handle_sigint);
-
-      std::string model_path = "../best_model_script.pt";
-      std::string cleaned_path = "../cleaned.txt";
-
-      std::cout << "--- Loading Pre-trained Model ---\n";
-      torch::jit::script::Module model;
-      try
-      {
-            model = torch::jit::load(model_path, torch::kCPU);
-      }
-      catch (const c10::Error &e)
-      {
-            std::cerr << "[Error] Could not load model: " << e.what() << "\n";
-            return 1;
-      }
-      model.eval();
-
-      auto it = build_vocab(cleaned_path);
-      std::cout << "[INFO] Vocab size : " << it.size() << "\n";
-      std::cout << "[INFO] Device     : CPU\n";
-      std::cout << "Model loaded. Generating text (Ctrl+C to stop)...\n\n";
-      std::cout << std::string(50, '-') << "\n";
-
-      const int block_size = 128;
-      auto context = torch::zeros({1, 1}, torch::kLong);
-
-      torch::NoGradGuard no_grad;
-
-      while (running)
-      {
-            auto idx_cond = context;
-            if (context.size(1) > block_size)
-                  idx_cond = context.slice(1, context.size(1) - block_size);
-
-            std::vector<torch::jit::IValue> inputs = {idx_cond};
-            auto output = model.forward(inputs).toTuple();
-            auto logits = output->elements()[0].toTensor();
-
-            logits = logits.select(1, logits.size(1) - 1);
-            auto probs = torch::softmax(logits, -1);
-            auto idx_next = torch::multinomial(probs, 1);
-
-            context = torch::cat({context, idx_next}, 1);
-            if (context.size(1) > block_size)
-                  context = context.slice(1, context.size(1) - block_size);
-
-            int token = idx_next[0][0].item<int>();
-            if (it.count(token))
-                  std::cout << it[token] << std::flush;
-            else
-                  std::cout << '?' << std::flush;
-      }
-
-      return 0;
-}
\ No newline at end of file