textgen.py

import torch

class TextGen:
    def __init__(self,tokenizer,model,device):
        self.tokenizer = tokenizer
        self.model = model
        self.device = device
        self.model.to(self.device)


    def generate_text(self, user_input):
        inputs = self.tokenizer.encode(user_input, return_tensors="pt").to(self.device)

        # generate text
        attention_mask = torch.ones(inputs.shape, device=self.device)
        output = self.model.generate(
            inputs,
            attention_mask=attention_mask,
            num_return_sequences=1,
            max_length=50,
            max_new_tokens=100,
            temperature=0.5,
            repetition_penalty=1.2,
            pad_token_id=self.tokenizer.eos_token_id,
            )

        generated_text = self.tokenizer.decode(output[0], skip_special_tokens=True)


        return generated_text