Update README.md

README.md

@@ -7,4 +7,22 @@ language:
 pipeline_tag: text2text-generation
 tags:
 - nl2sql
----
+---
+
+# How to Use
+
+```
+import torch
+from transformers import T5ForConditionalGeneration, AutoTokenizer
+
+device = torch.device("cuda:0")
+
+tokenizer = AutoTokenizer.from_pretrained("LarkAI/codet5p-770m_nl2sql_oig")
+model = T5ForConditionalGeneration.from_pretrained("LarkAI/codet5p-770m_nl2sql_oig").to(device)
+
+text = "Given the following schema:\nroad (road_name, state_name)\nstate (state_name, capital, population, area, country_name, density)\nhighlow (state_name, highest_point, highest_elevation, lowest_point, lowest_elevation)\nlake (lake_name, area, state_name, country_name)\nriver (river_name, length, traverse, country_name)\nborder_info (state_name, border)\nmountain (mountain_name, mountain_altitude, state_name, country_name)\ncity (city_name, state_name, population, country_name)\nWrite a SQL query to what states does the mississippi river run throug"
+inputs = tokenizer.encode(text, return_tensors="pt").to(device)
+output_ids = model.generate(inputs, max_length=512)
+response_text = self.tokenizer.decode(outputs[0], skip_special_tokens=True)
+# SELECT traverse FROM river WHERE river_name = \"mississippi\" ;
+```