# AI机器人开发代码示例 import tensorflow as tf from transformers import GPT2LMHeadModel, GPT2Tokenizer class AIRobot: def __init__(self, model_name="gpt2"): self.tokenizer = GPT2Tokenizer.from_pretrained(model_name) self.model = GPT2LMHeadModel.from_pretrained(model_name) def generate_response(self, input_text, max_length=100): inputs = self.tokenizer.encode(input_text, return_tensors='pt') outputs = self.model.generate( inputs, max_length=max_length, num_return_sequences=1, no_repeat_ngram_size=2, temperature=0.7 ) response = self.tokenizer.decode(outputs[0], skip_special_tokens=True) return response def train(self, dataset, epochs=3): # 训练模型的代码 optimizer = tf.keras.optimizers.Adam(learning_rate=5e-5) for epoch in range(epochs): print(f"Epoch {epoch+1}/{epochs}") for batch in dataset: # 训练步骤 pass print("训练完成！") # 创建机器人实例 robot = AIRobot() # 测试机器人 response = robot.generate_response("你好，我是开发者") print(response)