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from transformers import GPT2LMHeadModel, GPT2Tokenizer
import gradio as gr
# Load the pre-trained GPT2 model and tokenizer
model = GPT2LMHeadModel.from_pretrained("gpt2")
tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
# 設置填充標記 ID
tokenizer.pad_token = tokenizer.eos_token
def generate_command(prompt, max_length=100):
full_prompt = f"生成一個Bash指令，用於{prompt}:```bash\n"
inputs = tokenizer.encode(full_prompt, return_tensors="pt")
output = model.generate(
inputs,
max_length=max_length,
num_return_sequences=1,
temperature=0.7,
pad_token_id=tokenizer.pad_token_id
)
generated_text = tokenizer.decode(output[0], skip_special_tokens=False)
# 提取生成的指令
start = generated_text.find("```bash") + len("```bash")
end = generated_text.find("```", start)
if end == -1:
end = len(generated_text)
command = generated_text[start:end].strip()
return command
def predict(input_text):
output = generate_command(input_text)
return output
iface = gr.Interface(
fn=predict,
inputs=gr.Textbox(lines=2, placeholder="請輸入你的指令生成提示..."),
outputs="text",
title="使用 GPT2 生成指令",
description="根據你的中文輸入提示生成 Bash 指令。"
)
iface.launch() |