Update app.py

app.py

@@ -6,13 +6,15 @@ import os
 os.environ['HUGGINGFACE_HUB_CACHE'] = '/app/.cache/huggingface/hub'
 
 # The name of the model you want to use
-model_name = "facebook/nllb-200-distilled-600M"
+model_name = "16pramodh/NMT_YAP"
+tokenizer = NllbTokenizer.from_pretrained("facebook/nllb-200-distilled-600M")
 
 # Load the translation pipeline
 # The pipeline will automatically download the tokenizer and model from the Hub
 pipe = pipeline(
     "translation",
     model=model_name,
+    tokenizer=tokenizer,
     src_lang="eng_Latn",
     tgt_lang="hin_Deva",
     device=0,  # Use GPU if available
@@ -37,8 +39,8 @@ iface = gr.Interface(
         gr.Textbox(label="Input Text")
     ],
     outputs="text",
-    title="NLLB-200 Distilled Translation API",
-    description="A public API for the NLLB-200 translation model, with support for multiple languages."
+    title="NLLB-200 Distilled finetuned Translation API",
+    description="A public API for the NLLB-200 translation model, for english to hindi translation."
 )
 
 # Launch the Gradio app