Create app.py

app.py

@@ -0,0 +1,32 @@
+import gradio
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+
+
+model_name = "zaanind/nllb-ensi-v1.6" #"zaanind/nllb-ensi-v1-tuning-subs"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+
+tokenizer.src_lang = "eng_Latn"
+
+def translate(text):
+    inputs = tokenizer(text=text, return_tensors="pt")
+    translated_tokens = model.generate(
+        **inputs, forced_bos_token_id=tokenizer.lang_code_to_id["sin_Sinh"]
+    )
+    translation = tokenizer.decode(translated_tokens[0], skip_special_tokens=True)
+    return translation
+
+    
+def nmtapifunc(text):
+    text = translate(text)
+    return text 
+
+gradio_interface = gradio.Interface(
+  fn=nmtapifunc,
+  inputs="text",
+  outputs="text",
+  title="En-Si NMT",
+  description="",
+  article="© zaanind 2024"
+)
+gradio_interface.launch()