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import gradio as gr | |
import requests | |
import os | |
TK = os.environ['HF_TOKEN'] | |
API_URL = "https://api-inference.huggingface.co/models/gowtham58/T_TL" | |
headers = {"Authorization": f"Bearer {TK}"} | |
def get_output(text): | |
response = requests.post(API_URL, headers=headers, json={"inputs": text,}) | |
response = response.json() | |
#print(response) | |
while response[0]=='error': | |
response = requests.post(API_URL, headers=headers, json={"inputs": text,}) | |
response = response.json() | |
return response[0]['generated_text'] | |
description = """TRANSLITERATE is to represent or spell in the characters of another alphabet. Normally we create tamil words using English Characters | |
in our daily text conversations. This Model can generate the words in tamil given a transliterated tamil word in english""" | |
css = """ | |
h1 { | |
text-align: center; | |
display:block; | |
} | |
p { | |
text-align: center; | |
display:block; | |
} | |
.contain { | |
max-width: 900px; | |
margin: auto; | |
padding-top: 1.5rem; | |
} | |
""" | |
app = gr.Interface( | |
fn=get_output, | |
inputs="textbox", | |
outputs="text", | |
title="Tamil Transliteraion", | |
description=description, | |
examples=[["Hello, Nanba epdi iruka"], ["Naa Ready dha varava"]], | |
css = css, | |
allow_flagging="never", | |
) | |
app.launch() | |