Quantized facebook/mbart50 model return empty output during inference

I used pytorchs dynamic_quantization method to quantize the model with this script which reduced the model.bin from 2.4Gb to 1.6GB. I have downloaded mbrat50 model from huggingface to the local folder “model”

import torch
from transformers import MBartConfig, MBartForConditionalGeneration

config = MBartConfig.from_pretrained("model")


model = MBartForConditionalGeneration.from_pretrained("model",config=config)
model.eval()

quantized_model = torch.quantization.quantize_dynamic(model, qconfig_spec={torch.nn.Linear}, dtype=torch.qint8)
print(quantized_model)
torch.save(quantized_model.state_dict(), "model/newww_new_quant.bin")

When I try to translate a word it returns empty string, without quantization model translation works…

from transformers import MBart50TokenizerFast, MBartForConditionalGeneration
import logging

logging.basicConfig(level=logging.INFO)

class Translator:
    def __init__(self, model_path) -> None:

        logging.info('Loading tokenizer.')
        self.tokenizer = MBart50TokenizerFast.from_pretrained(model_path)
        logging.info('Tokenizer loaded.')

        logging.info('Loading model.')
        self.model = MBartForConditionalGeneration.from_pretrained(model_path)
        logging.info('Model loaded.')


    def translate(self, sentences):
        
        encoded_ka = self.tokenizer(sentences, return_tensors="pt", padding=True)
        logging.debug('encoded sentences', encoded_ka)
        print(encoded_ka)
        generated_tokens = self.model.generate(**encoded_ka)
        logging.debug('generated tokens:', generated_tokens)
        print(generated_tokens)
        decoded_ka = self.tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
        print(decoded_ka)
        return decoded_ka

before the quantization the model translation is fine
ouput:

got sent ['პირადი გადარიცხვა']
{'input_ids': tensor([[250004, 185472,   8411, 139656, 114572,      2]]), 'attention_mask': tensor([[1, 1, 1, 1, 1, 1]])}
tensor([[     2, 250004,  17915,  73509,      2]])
['Personal Transfer']
transl : ['Personal Transfer']

after quantization the ouputs is

got sent ['პირადი გადარიცხვა']
{'input_ids': tensor([[250004, 185472,   8411, 139656, 114572,      2]]), 'attention_mask': tensor([[1, 1, 1, 1, 1, 1]])}
tensor([[     2, 250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004,
         250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004,
         250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004,
         250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004,
         250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004,
         250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004,
         250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004,
         250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004,
         250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004,
         250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004,
         250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004,
         250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004,
         250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004,
         250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004,
         250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004,
         250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004,
         250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004,
         250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004,
         250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004,
         250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004,
         250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004,
         250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004, 250004,
         250004,      2]])
['']
transl : ['']

Does someone has any idea what can cause it?