Create app.py

app.py

@@ -0,0 +1,29 @@
+import gradio as gr
+from transformers import pipeline, AutoModelForSeq2SeqLM, MBart50Tokenizer, AutoTokenizer
+
+tokenizer = AutoTokenizer.from_pretrained('facebook/mbart-large-50', src_lang="bn_IN", tgt_lang="bn_IN", use_fast=True)
+model = AutoModelForSeq2SeqLM.from_pretrained("jafrilalam/bangla_sentence_correction", use_safetensors=True)
+
+def correct_text(given_sentence):
+    inputs = tokenizer.encode(
+        given_sentence,
+        truncation=True,
+        return_tensors="pt",
+        max_length=len(given_sentence),
+    )
+
+    output_ids = model.generate(
+        inputs,
+        max_new_tokens=len(given_sentence),
+        early_stopping=True,
+    )
+    
+    return tokenizer.decode(output_ids[0], skip_special_tokens=True)
+
+iface = gr.Interface(
+    fn=correct_text,
+    inputs=gr.Textbox(lines=4, label="Incorrect Bangla Sentence"),
+    outputs=gr.Textbox(label="Corrected Bengali Sentence")
+)
+
+iface.launch()