Input features of the first layer

[dara1400]

Hello
I hope you are doing well.

model = MOMENTPipeline.from_pretrained(
"AutonLab/MOMENT-1-large",
model_kwargs={
"task_name": "forecasting",
"forecast_horizon": 96,
},
)
model.init()

When calling the model, I noticed that the input features of the first layer is 8.
Dose it mean that the model use the 8 previous inputs to predict the next point?

If it is the case, how can I change it?

[dara1400]

I understand that the model always use 512 previous data to predict new point.
Can this be changed?