Update README.md

README.md

@@ -5,7 +5,29 @@ library_name: peft
 
 # Model Card for Model ID
 
-<!-- Provide a quick summary of what the model is/does. -->
+to genrate tabluar data give instruction like
+
+FastLanguageModel.for_inference(model) # Enable native 2x faster inference
+inputs = tokenizer(
+[
+    alpaca_prompt.format(
+        "understand the pattern and functional dependencies in the table given in json format in Input and generate similar table with 5 rows.", # instruction
+        """{("category":"A","item_id":"A1","location":"loc-001","price":100,"available":true),("category":"A","item_id":"A2","location":"loc-002","price":150,"available":false")},{("category":"B","item_id":"B1","location":"loc-001","price":100,"available":true),("category":"B","item_id":"B2","location":"loc-002","price":150,"available":false")},{("category":"C","item_id":"C1","location":"loc-001","price":100,"available":true),("category":"B","item_id":"B3","location":"loc-002","price":150,"available":false")}""", # input
+        "", # output - leave this blank for generation!
+    )
+], return_tensors = "pt").to("cuda")
+
+where 
+alpaca_prompt = """Below is an instruction that describes a task, paired with an input that provides data mentioned in instruction. Write a response and explanation that appropriately completes the request. In the Input section a table is given in form of json format. ( (col1: 1,col2: 2), (col1: 3, col2: 4)) here (col1: 1,col2: 2) is row 1 and (col1: 3, col2: 4)) is row 2 in row 1 col 1 has value 1 and col 2 has value 2.
+
+### Instruction:
+{}
+
+### Input:
+{}
+
+### Output:
+{}"""