Create app.py

app.py

@@ -0,0 +1,33 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
+import torch
+from ui import title, description, examples
+from langs import LANGS
+
+model = AutoModelForSeq2SeqLM.from_pretrained("facebook/nllb-200-distilled-600M")
+tokenizer = AutoTokenizer.from_pretrained("facebook/nllb-200-distilled-600M")
+
+device = 0 if torch.cuda.is_available() else -1
+
+src_lang = 'som_Latn'
+tgt_lang = "eng_Latn"
+
+def translate(text):
+    translation_pipeline = pipeline("translation",
+                                    model=model,
+                                    tokenizer=tokenizer,
+                                    src_lang=src_lang,
+                                    tgt_lang=tgt_lang,
+                                    device=device)
+
+    result = translation_pipeline(text)
+    return result[0]['translation_text']
+
+
+gr.Interface(
+    translate,
+    [
+        gr.components.Textbox(label="Text")
+    ],
+    ["text"],
+).launch()