Delete app.py

app.py

@@ -1,33 +0,0 @@
-import gradio as gr
-from transformers import M2M100ForConditionalGeneration
-from tokenization_small100 import SMALL100Tokenizer
-
-langs = """af,am,ar,ast,az,ba,be,bg,bn,br,bs,ca,ceb,cs,cy,da,de,el,en,es,et,fa,ff,fi,fr,fy,ga,gd,gl,gu,ha,he,hi,hr,ht,hu,hy,id,ig,ilo,is,it,ja,jv,ka,kk,km,kn,ko,lb,lg,ln,lo,lt,lv,mg,mk,ml,mn,mr,ms,my,ne,nl,no,ns,oc,or,pa,pl,ps,pt,ro,ru,sd,si,sk,sl,so,sq,sr,ss,su,sv,sw,ta,th,tl,tn,tr,uk,ur,uz,vi,wo,xh,yi,yo,zh,zu"""
-lang_list = langs.split(',')
-
-model = M2M100ForConditionalGeneration.from_pretrained("alirezamsh/small100")
-tokenizer = SMALL100Tokenizer.from_pretrained("alirezamsh/small100")
-
-def translate(lang, text):
-    tokenizer.tgt_lang = lang
-    encoded_text = tokenizer(text, return_tensors="pt")
-    generated_tokens = model.generate(**encoded_text)
-    return tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)[0]
-
-with gr.Blocks(analytics_enabled=False) as app:
-    
-    Source = gr.Textbox( label="Source" )
-    Language = gr.Dropdown( lang_list, label="Language" )
-    Translate = gr.Button( "Translate" )
-    Result = gr.Textbox( label="Result" )
-    
-
-    Translate.click(
-        translate,
-        inputs=[ Language, Source ],
-        outputs=[Result],
-        api_name="translate",
-    )
-
-    app.launch( inline=True )
-    block.queue( concurrency_count=2 )