Various seed models on all test sets

[stephaniesamm]

• Use code from https://github.com/katarinagresova/miRBench/blob/main/src/miRBench/predictor.py to update your seed6mer function to include all the definitions of seed6mer there. Extract the code for the other seed types too. Make a function for each seed type (seed6mer, seed7mer, seed8mer).
• Make a python script (.py) that takes as input one test set and outputs the same test set with added column: 1 column per seed type. Use argparse for argument parsing. Pass input test file and output test file with added columns as arguments.
• Run this python script on all test sets (Klimentova test, Hejret test, Manakov test and Manakov leftout).

TASK COMPLETED :) You will have created a script that applies a seed model to our evaluation datasets (the test sets). We can use this as a baseline, to compare ML models performance to a simple rule-based model.