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from transformers import AutoTokenizer, AutoModelForCausalLM
import gradio as gr
import os
huggingface_token = os.getenv("HUGGINGFACE_TOKEN")
if huggingface_token is None:
print("Token Hugging Face tidak ditemukan. Pastikan Anda telah menetapkan variabel lingkungan HUGGINGFACE_TOKEN.")
exit()
tokenizer = AutoTokenizer.from_pretrained("meta-llama/Meta-Llama-3-8B", token=huggingface_token)
model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3-8B", token=huggingface_token)
def translate_code(input_code, prompt=""):
input_text = f"{prompt}\n\n{input_code}"
input_ids = tokenizer.encode(input_text, return_tensors="pt", max_length=1024, truncation=True)
output = model.generate(input_ids, max_length=1024, num_return_sequences=1, temperature=0.7)
translated_code = tokenizer.decode(output[0], skip_special_tokens=True)
return translated_code
gr.Interface(
fn=translate_code,
inputs=["text", "text"],
outputs="text",
title="AI Code Translator",
description="Translate your code using Meta-Llama-3-8B model.",
theme="compact"
).launch() |