

Once your model is quantized, you can push the model and tokenizer to the Hub where it can be easily shared and accessed. Use the [~PreTrainedModel.push_to_hub] method to save the [GPTQConfig]:
py
quantized_model.push_to_hub("opt-125m-gptq")
tokenizer.push_to_hub("opt-125m-gptq")
You could also save your quantized model locally with the [~PreTrainedModel.save_pretrained] method. If the model was quantized with the device_map parameter, make sure to move the entire model to a GPU or CPU before saving it. For example, to save the model on a CPU: