def METHOD_NAME(backend):
    np.random.seed(0)
    n_bins = 100
    model = pyhf.simplemodels.uncorrelated_background(
        [10] * n_bins, [50] * n_bins, [1] * n_bins
    )
    init_pars = model.config.suggested_init()
    observations = np.random.randint(50, 60, size=n_bins).tolist()
    data = observations + model.config.auxdata
    return model, data, init_pars