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import gradio as gr
import requests
import os
import json
API_URL = "https://api-inference.huggingface.co/models/bigscience/bloom"
headers = {"Authorization": f"Bearer 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"}
def translate(prompt_ , from_lang, to_lang, input_prompt = "translate this", seed = 42):
prompt = f"To say \"{prompt_}\" in {to_lang}, you would say"
print(prompt)
if len(prompt) == 0:
prompt = input_prompt
json_ = {
"inputs": prompt,
"parameters": {
"top_p": 0.9,
"top_k": 100,
"temperature": 1.1,
"max_new_tokens": 250,
"return_full_text": True,
"do_sample": True,
"num_beams": 3,
"seed": seed,
"repetition_penalty": 3.0,
},
"options": {
"use_cache": True,
"wait_for_model": True,
},
}
response = requests.post(API_URL, headers=headers, json=json_)
print(f"Response is : {response}")
output = json.loads(response.content.decode("utf-8"))#response.json()
print(f"output is : {output}")
#output = json.loads(response.content.decode("utf-8"))
output_tmp = output[0]['generated_text']
print(f"output_tmp is: {output_tmp}")
solution = output_tmp.split(f"\n{to_lang}:")[0]
if '\n\n' in solution:
final_solution = solution.split("\n\n")[0]
else:
final_solution = solution
return final_solution
demo = gr.Blocks()
with demo:
gr.Markdown("<h1><center>Bloom Translation</center></h1>")
with gr.Row():
from_lang = gr.Dropdown(['English', 'Spanish', 'Hindi' , 'Bangla'],
value='English',
label='select From language : ')
with gr.Row():
to_lang = gr.Dropdown(['English', 'Spanish', 'Hindi'],
value='Hindi',
label= 'select to Language : ')
input_prompt = gr.Textbox(label="Enter the sentence : ",
value=f"Please write the text here :",
lines=6)
generated_txt = gr.Textbox(lines=3)
b1 = gr.Button("translate")
b1.click(translate,inputs=[ input_prompt, from_lang, to_lang], outputs=generated_txt)
demo.launch(enable_queue=True, debug=True)
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