Update README.md

README.md

@@ -30,11 +30,27 @@ This model is quantized in 8-bit and trained with question and answer pairs for
 
 ```python
 from peft import PeftModel, PeftConfig
-from transformers import AutoModelForCausalLM
+from transformers import AutoModelForCausalLM, AutoTokenizer
 
-config = PeftConfig.from_pretrained("Be-12/text-to-sql-fm")
+# Load the PEFT configuration
+config = PeftConfig.from_pretrained("Lei-bw/text-to-sql-fm")
+
+# Load the base model
 base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2b")
-model = PeftModel.from_pretrained(base_model, "Be-12/text-to-sql-fm")
+
+# Load the fine-tuned model using PEFT
+model = PeftModel.from_pretrained(base_model, "Lei-bw/text-to-sql-fm")
+
+# Load the tokenizer
+tokenizer = AutoTokenizer.from_pretrained("google/gemma-2b")
+
+# Example usage
+text = "What is the average salary of employees in the sales department?"
+inputs = tokenizer(text, return_tensors="pt")
+outputs = model.generate(**inputs)
+generated_text = tokenizer.decode(outputs[0])
+
+print(generated_text)
 ```
 
 ## Training Details