Update README.md

README.md

@@ -71,5 +71,5 @@ import torch
 from transformers import AutoTokenizer, AutoModelForCausalLM
 tokenizer = AutoTokenizer.from_pretrained("sambanovasystems/nova-nsql-Llama-2-70B")
 model = AutoModelForCausalLM.from_pretrained("sambanovasystems/nova-nsql-Llama-2-70B", torch_dtype=torch.bfloat16)
-
+text = "CREATE TABLE stadium (\n    stadium_id number,\n    location text,\n    name text,\n    capacity number,\n    highest number,\n    lowest number,\n    average number\n)\n\nCREATE TABLE singer (\n    singer_id number,\n    name text,\n    country text,\n    song_name text,\n    song_release_year text,\n    age number,\n    is_male others\n)\n\nCREATE TABLE concert (\n    concert_id number,\n    concert_name text,\n    theme text,\n    stadium_id text,\n    year text\n)\n\nCREATE TABLE singer_in_concert (\n    concert_id number,\n    singer_id text\n)\n\n\n-- Using valid SQLite, answer the following questions for the tables provided above.\n\n-- What is the average, minimum, and maximum age of all singers from France?\nSELECT"
 ```