Create app.py

app.py

@@ -0,0 +1,53 @@
+import gradio as gr
+from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
+
+# Initialize model and tokenizer at startup
+model = M2M100ForConditionalGeneration.from_pretrained("facebook/m2m100_418M")
+tokenizer = M2M100Tokenizer.from_pretrained("facebook/m2m100_418M")
+
+LANGUAGES = {
+    "English": "en",
+    "Spanish": "es",
+    "French": "fr",
+    "German": "de",
+    "Chinese": "zh",
+    "Hindi": "hi",
+    "Punjabi": "pa",
+    "Arabic": "ar",
+    "Japanese": "ja",
+    "Urdu": "ur",
+}
+
+def translate(text, target_lang):
+    if not text.strip():
+        return "Please enter text to translate"
+        
+    try:
+        tokenizer.tgt_lang = LANGUAGES[target_lang]
+        encoded = tokenizer(text, return_tensors="pt")
+        generated_tokens = model.generate(
+            **encoded,
+            forced_bos_token_id=tokenizer.get_lang_id(LANGUAGES[target_lang]),
+            max_length=400  # Added for safety
+        )
+        return tokenizer.decode(generated_tokens[0], skip_special_tokens=True)
+    except KeyError:
+        return "Selected language not supported"
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Create interface with Hugging Face optimized settings
+demo = gr.Interface(
+    fn=translate,
+    inputs=[
+        gr.Textbox(label="Input Text", placeholder="Enter text to translate...", lines=3),
+        gr.Dropdown(list(LANGUAGES.keys()), 
+    ],
+    outputs=gr.Textbox(label="Translation", lines=8),
+    title="🌍 Universal Translator",
+    description="Human Language Translator Created By _____________",
+    allow_flagging="never"
+)
+
+if __name__ == "__main__":
+    demo.launch(server_name="0.0.0.0", server_port=7860)