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app.py

@@ -27,7 +27,47 @@ DEVICE = "cpu"
 # Initialize the OCR object for text detection and recognition
 ocr = OCR(device="cpu", verbose=False)
 def translate_en_hin(given_str):
-    return given_str
+    model = model.to(DEVICE)
+    model.eval()
+    src_lang, tgt_lang = "eng_Latn", "hin_Deva"
+    
+    batch = ip.preprocess_batch(
+        [given_str],
+        src_lang=src_lang,
+        tgt_lang=tgt_lang,
+    )
+    inputs = tokenizer(
+            batch,
+            truncation=True,
+            padding="longest",
+            return_tensors="pt",
+            return_attention_mask=True,
+        ).to(DEVICE)
+    with torch.no_grad():
+        generated_tokens = model.generate(
+            **inputs,
+            use_cache=True,
+            min_length=0,
+            max_length=256,
+            num_beams=5,
+            num_return_sequences=1,
+        )
+
+    # Decode the generated tokens into text
+    with tokenizer.as_target_tokenizer():
+        generated_tokens = tokenizer.batch_decode(
+            generated_tokens.detach().cpu().tolist(),
+            skip_special_tokens=True,
+            clean_up_tokenization_spaces=True,
+        )
+    translation = ip.postprocess_batch(generated_tokens, lang=tgt_lang)[0]
+    return translation
+
+
+
+        
+
+