Create app.py

app.py

@@ -0,0 +1,37 @@
+import torch
+from transformers import (T5ForConditionalGeneration,T5Tokenizer)
+import gradio as gr
+
+best_model_path = "swcrazyfan/Dekingify-T5-Large"
+model = T5ForConditionalGeneration.from_pretrained(best_model_path)
+tokenizer = T5Tokenizer.from_pretrained("swcrazyfan/Dekingify-T5-Large")
+
+def tokenize_data(text):
+    # Tokenize the review body
+ #   input_ = "paraphrase: "+ str(text) + ' >'
+    input_ = "deking: " + str(text) + ' </s>'
+    max_len = 512
+    # tokenize inputs
+    tokenized_inputs = tokenizer(input_, padding='max_length', truncation=True, max_length=max_len, return_attention_mask=True, return_tensors='pt')
+
+    inputs={"input_ids": tokenized_inputs['input_ids'],
+        "attention_mask": tokenized_inputs['attention_mask']}
+    return inputs
+
+def generate_answers(text):
+    inputs = tokenize_data(text)
+    results= model.generate(input_ids= inputs['input_ids'], attention_mask=inputs['attention_mask'], do_sample=True,
+                           num_beams=5,
+                            max_length=512,
+                            min_length=1,
+                            early_stopping=True,
+                            num_return_sequences=1)
+    answer = tokenizer.decode(results[0], skip_special_tokens=True)
+    return answer
+
+#iface = gr.Interface(fn=generate_answers, inputs=["Write your text here..."], outputs=["Jamesified text"])
+#iface.launch(inline=False, share=True)
+
+iface = gr.Interface(title="Dekingify", description="Write anything from around the 17th-century below. Then, click submit to 'Dekingify' it (make the text more modern).", fn=generate_answers, inputs=[gr.inputs.Textbox(label="Original Text",lines=10)], outputs=["text"])
+#iface = gr.Interface(title="King Jamesify” fn=generate_answers, inputs=[gr.inputs.Textbox(label="Original",lines=30)],outputs=[gr.outputs.Textbox(label="King Jamesified", lines=30)])
+iface.launch(inline=False)