Delete test

test

@@ -1,22 +0,0 @@
-import streamlit as st
-
-from transformers import T5ForConditionalGeneration, T5Tokenizer
-
-model = T5ForConditionalGeneration.from_pretrained("Unbabel/gec-t5_small")
-tokenizer = T5Tokenizer.from_pretrained('t5-small')
-
-sentence = st.text_area("enter some text")
-
-tokenized_sentence = tokenizer('gec: ' + sentence, max_length=128, truncation=True, padding='max_length', return_tensors='pt')
-corrected_sentence = tokenizer.decode(
-    model.generate(
-        input_ids = tokenized_sentence.input_ids,
-        attention_mask = tokenized_sentence.attention_mask, 
-        max_length=128,
-        num_beams=5,
-        early_stopping=True,
-    )[0],
-    skip_special_tokens=True, 
-    clean_up_tokenization_spaces=True
-)
-print(corrected_sentence)