Update app.py

app.py

@@ -1,16 +1,29 @@
 import streamlit as st
 import layer
+from transformers import AutoModelWithLMHead, AutoTokenizer
 
-model = layer.get_model('layer/t5-fine-tuning-with-layer/models/t5-english-to-sql').get_train()
-tokenizer = layer.get_model('layer/t5-fine-tuning-with-layer/models/t5-tokenizer').get_train()
+tokenizer = AutoTokenizer.from_pretrained("mrm8488/t5-base-finetuned-wikiSQL")
+model = AutoModelWithLMHead.from_pretrained("mrm8488/t5-base-finetuned-wikiSQL")
 
-def convert(query):
-    inputs = tokenizer.encode(f"translate English to SQL: {query}", return_tensors="pt")
-    outputs = model.generate(inputs, max_length=1024)
-    sql = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    return sql
+def get_sql(query):
+  input_text = "translate English to SQL: %s </s>" % query
+  features = tokenizer([input_text], return_tensors='pt')
+
+  output = model.generate(input_ids=features['input_ids'], 
+               attention_mask=features['attention_mask'])
+  
+  return tokenizer.decode(output[0])
+
+# model = layer.get_model('layer/t5-fine-tuning-with-layer/models/t5-english-to-sql').get_train()
+# tokenizer = layer.get_model('layer/t5-fine-tuning-with-layer/models/t5-tokenizer').get_train()
+
+# def convert(query):
+#     inputs = tokenizer.encode(f"translate English to SQL: {query}", return_tensors="pt")
+#     outputs = model.generate(inputs, max_length=1024)
+#     sql = tokenizer.decode(outputs[0], skip_special_tokens=True)
+#     return sql
 
 
 query = st.text_input("Enter Text here", value="")
-output = convert(query)
+output = get_sql(query)
 st.text_area(label="Output Sql Query:", value=output, height=100)