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import gradio as gr | |
from transformers import AutoTokenizer, AutoModelWithLMHead | |
tokenizer = AutoTokenizer.from_pretrained("dbernsohn/t5_wikisql_en2SQL") | |
model = AutoModelWithLMHead.from_pretrained("dbernsohn/t5_wikisql_en2SQL") | |
def greet(query): | |
input_text = f"translate English to Sql: {query} </s>" | |
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]) | |
iface = gr.Interface(fn=greet, inputs="text", outputs="text", examples=[ | |
"what are the names of all the people in the USA" | |
]) | |
iface.launch() |