Create new file

app.py

@@ -0,0 +1,49 @@
+INDIC = {
+"Hindi":"hin_Deva",
+"English":"eng_Latn",
+"Kannada": "kan_Knda",
+"Tamil":"tam_Taml",
+"Bengali":"ben_Beng",
+"Nepali" : "npi_Deva",
+"Telugu":"tel_Telu",
+"Gujarati":"guj_Gujr",
+"Marathi":"mar_Deva",
+"Odia":"ory_Orya",
+"Sanskrit":"san_Deva",
+"Maithili":"mai_Deva",
+"Urdu":"urd_Arab",
+"Punjabi" : "pan_Guru",
+"Malayalam" :"mal_Mlym",
+"Assamese" : "asm_Beng"
+}
+
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
+
+model_name='facebook/nllb-200-distilled-600M'
+
+model=AutoModelForSeq2SeqLM.from_pretrained(model_name)
+tokenizer=AutoTokenizer.from_pretrained(model_name)
+
+
+
+
+def translate(text, src_lang, tgt_lang):
+  translator=pipeline('translation', model=model, tokenizer=tokenizer, src_lang=INDIC[src_lang], tgt_lang=INDIC[tgt_lang], max_length=200)
+  return translator(text)
+
+
+
+languages = list(INDIC.keys())
+
+iddwn = grd.inputs.Dropdown(languages, type="value", default="English", label="Select Source Language")
+oddwn = grd.inputs.Dropdown(languages, type="value", default="Hindi", label="Select Target Language")
+
+txt = grd.inputs.Textbox( lines=5, placeholder="Enter Text to translate", default="", label="Enter Text in Source Language")
+txt_ouptut = grd.outputs.Textbox(type="auto", label="Translated text in Target Language")
+
+example=[['I want to translate this sentence in Hindi','English','Hindi'],
+        ['I am feeling very good today.', 'English','Bengali']]
+
+supp = ', '.join(languages)
+iface = grd.Interface(fn=translate, inputs=[txt,ddwn] , outputs=txt_ouptut, title='Translation for 15 Indic Languages', description = 'This is a demo based on NLLB by Meta. Supported: '+supp, article = 'Original repo [link](https://github.com/AI4Bharat/indicTrans) by AI4Bharat. <b>Note: This space can only perform translation from English to Indic languages. Support for other combinations will be provided soon.', examples=example)
+iface.launch(enable_queue=True)