lm-sim 0.0.3

Python package to compute similarity between LMs

LM-Similarity

lm-sim is a Python module for computing similarity between Language Models and is distributed under the MIT license.

Installation

Dependencies

lm-sim requries:

• Python (>=3.9)
• Numpy (>= 1.19.5)

User installation

If you already have a working installation of NumPy, the easiest way to install lm-sim is using pip:

pip install lm-sim

Example Usage

A simple example to compute Goels $k$ in the context of MCQs (default computation is probabilistic Goels $k_p$). Input has be to formatted as follows:

• output_a: list[np.array], containing the softmax output probabilties of model a
• output_b: list[np.array], containing the softmax output probabilties of model b
• gt: list[int], containing the index of the ground truth

from lmsim.metrics import Goels_k

calculator = Goels_k()
calculator.compute_k(output_a, output_b, gt)

For a discrete computation, when output probabilities are not availble, set the flag prob=False and the input must be formatted as one-hot vectors:

• output_a: list[np.array], one-hot vector of model a
• output_b: list[np.array], one-hot vector of model b

from lmsim.metrics import Goels_k

calculator = Goels_k(prob=False)
calculator.compute_k(output_a, output_b, gt)