Create app.py

app.py

@@ -0,0 +1,15 @@
+import gradio as gr
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+
+model_name = "flexudy/t5-base-multi-sentence-doctor"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+
+def correct_sentences(text):
+    inputs = tokenizer.encode(text, return_tensors="pt", truncation=True)
+    outputs = model.generate(inputs, max_length=512)
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+demo = gr.Interface(fn=correct_sentences, inputs="text", outputs="text", title="Sentence Doctor")
+
+demo.launch()