以下是使用不同编程语言实现的文本生成基础代码框架,内含模型调用示例与扩展教程链接:

Python 示例 🐍

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")
model = AutoModelForCausalLM.from_pretrained("bert-base-uncased")

input_text = "今天天气"
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs, max_length=50)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
文本生成_Python

JavaScript 示例 📜

const { AutoTokenizer, AutoModelForCausalLM } = require('@huggingface/transformers');

(async () => {
  const tokenizer = await AutoTokenizer.from_pretrained('bert-base-uncased');
  const model = await AutoModelForCausalLM.from_pretrained('bert-base-uncased');
  
  const inputText = "今天天气";
  const inputs = tokenizer(inputText, { return_tensors: 'pt' });
  const outputs = await model.generate(inputs, { maxLength: 50 });
  console.log(tokenizer.decode(outputs[0], { skipSpecialTokens: true }));
})();
文本生成_JavaScript

Java 示例 🧠

import org.tensorflow.SavedModelBundle;
import org.tensorflow.Session;

public class TextGeneration {
  public static void main(String[] args) {
    Session session = Session.create("bert-base-uncased");
    SavedModelBundle model = SavedModelBundle.load("bert-base-uncased", "serve");
    
    String inputText = "今天天气";
    // 调用模型生成逻辑
    System.out.println(generateText(session, model, inputText));
  }
}
文本生成_Java

📌 扩展阅读模型训练与优化指南 提供更详细的参数配置说明
📦 代码仓库查看完整示例代码 可获取最新版本