diff --git a/LLM_code/test.py b/LLM_code/test.py
new file mode 100644
index 0000000..11acf7e
--- /dev/null
+++ b/LLM_code/test.py
@@ -0,0 +1,3 @@
+from transformers import AutoTokenizer
+tokenizer = AutoTokenizer.from_pretrained("tokenizer_file/hf_tokenizer")  
+print(tokenizer.vocab_size)
diff --git a/LLM_code/test_huggingface_train.py b/LLM_code/test_huggingface_train.py
new file mode 100644
index 0000000..e69de29
diff --git a/LLM_code/test_huggingface_transformer.py b/LLM_code/test_huggingface_transformer.py
new file mode 100644
index 0000000..c4e6ed9
--- /dev/null
+++ b/LLM_code/test_huggingface_transformer.py
@@ -0,0 +1,18 @@
+import transformers
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from transformers import LlamaForCausalLM
+tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2-0.5B-Instruct")
+from transformers import LlamaConfig
+config = LlamaConfig(
+    vocab_size=32000,  
+    hidden_size=4096,  
+    num_attention_heads=32,  
+    num_hidden_layers=32, 
+    intermediate_size=11008,  
+)
+
+model = LlamaForCausalLM(config)
+
+model = transformers.Qwen2ForCausalLM(config)
+model_size = sum(t.numel() for t in model.parameters())
+print(f"Model Size: {model_size/1000**2:.1f}M parameters")
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