Delete app.py

app.py

@@ -1,56 +0,0 @@
-from transformers import pipeline
-import torch
-import gradio as gr
-
-# Translation pipeline
-translator = pipeline(task="translation",
-                      model="facebook/nllb-200-1.3B",
-                      torch_dtype=torch.bfloat16)
-
-# list of EU languages and their FLoRes-200 code
-eu_languages = {
-'Bulgarian':'bul_Cyrl',
-'Croatian':'hrv_Latn',
-'Czech':'ces_Latn',
-'Danish':'dan_Latn',
-'Dutch':'nld_Latn',
-'English':'eng_Latn',
-'Estonian':'est_Latn',
-'Finnish':'fin_Latn',
-'French':'fra_Latn',
-'German':'deu_Latn',
-'Greek':'ell_Grek',
-'Hungarian':'hun_Latn',
-'Irish':'gle_Latn',
-'Italian':'ita_Latn',
-'Latvian':'lvs_Latn',
-'Lithuanian':'lit_Latn',
-'Maltese':'mlt_Latn',
-'Polish':'pol_Latn',
-'Portuguese':'por_Latn',
-'Romanian':'ron_Latn',
-'Slovak':'slk_Latn',
-'Slovenian':'slv_Latn',
-'Spanish':'spa_Latn',
-'Swedish':'swe_Latn'
-}
-
-# Translate function
-def translate(input, src, tgt):
-    src_lang = eu_languages[src]
-    tgt_lang = eu_languages[tgt]
-    output = translator(input, src_lang=src_lang, tgt_lang=tgt_lang)
-    return output[0]['translation_text']
-
-
-# Gradio Interface
-gr.close_all()
-demo = gr.Interface(fn=translate, 
-                    inputs=[gr.Textbox(label="Text to translate", lines=6),
-                            gr.Dropdown(eu_languages.keys(), label="Source Language"),
-                            gr.Dropdown(eu_languages.keys(), label="Target Language")],
-                    outputs=[gr.Textbox(label="Result", lines=10)],
-                    title="NLLB Translator between EU Languages",
-                    description="Translate texts in EU languages using the `facebook/nllb-200-1.3B` model!"
-                   )
-demo.launch()