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import gradio
from transformers import GPT2LMHeadModel, GPT2Tokenizer, AdamW
from transformers import AutoTokenizer, AutoModelForCausalLM
model_name = "zaanind/gpt2_finetune_alpaca"
tokenizer = GPT2Tokenizer.from_pretrained(model_name)
tokenizer.pad_token = tokenizer.eos_token
model = GPT2LMHeadModel.from_pretrained(model_name)
def translate(text):
prompt = f"<s>[INST] translate this sentence to sinhala - {text} [/INST] sure,here the translation of the provided text - "
input_ids = tokenizer.encode(prompt, return_tensors='pt')
output = model.generate(input_ids, max_length=250, num_return_sequences=1)
translation = tokenizer.decode(output[0], skip_special_tokens=True)
return translation
def nmtapifunc(text):
text = translate(text)
return text
gradio_interface = gradio.Interface(
fn=nmtapifunc,
inputs="text",
outputs="text",
title="ZoomAI Inference Server",
description="",
article="© Zaanind 2023-2024"
)
gradio_interface.launch() |