lm-scorer 0.2.1

Language Model based sentences scoring library

lm-scorer

📃 Language Model based sentences scoring library

Synopsis

This package provides a simple programming interface to score sentences using different ML language models.

A simple CLI is also available for quick prototyping.
You can run it locally or on directly on Colab using this notebook.

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Install

pip install lm-scorer

Usage

from lm_scorer.models.auto import AutoLMScorer as LMScorer

LMScorer.supported_model_names()
# => ["gpt2", "gpt2-medium", "gpt2-large", "gpt2-xl", distilgpt2"]

scorer = LMScorer.from_pretrained("gpt2")

scorer.score("I like this package.")
# => -25.835
scorer.score("I like this package.", return_tokens=True)
# => -25.835, {
#   "I": -3.9997,
#   "Ġlike": -5.0142,
#   "Ġthis": -2.5178,
#   "Ġpackage": -7.4062,
#   ".": -1.2812,
#   "<|endoftext|>": -5.6163,
# }

scorer.score("I like this package.", return_log_prob=False)
# => 6.0231e-12
scorer.score("I like this package.", return_log_prob=False, return_tokens=True)
# => 6.0231e-12, {
#   "I": 0.018321,
#   "Ġlike": 0.0066431,
#   "Ġthis": 0.080633,
#   "Ġpackage": 0.00060745,
#   ".": 0.27772,
#   "<|endoftext|>": 0.0036381,
# }

CLI

The pip package includes a CLI that you can use to score sentences.

usage: lm-scorer [-h] [--model-name MODEL_NAME] [--tokens] [--log-prob]
                 [--debug]
                 sentences-file-path

Get sentences probability using a language model.

positional arguments:
  sentences-file-path   A file containing sentences to score, one per line. If
                        - is given as filename it reads from stdin instead.

optional arguments:
  -h, --help            show this help message and exit
  --model-name MODEL_NAME, -m MODEL_NAME
                        The pretrained language model to use. Can be one of:
                        gpt2, gpt2-medium, gpt2-large, gpt2-xl, distilgpt2.
  --tokens, -t          If provided it provides the probability of each token
                        of each sentence.
  --log-prob, -lp       If provided log probabilities are returned instead.
  --debug               If provided it provides additional logging in case of
                        errors.

Development

You can install this library locally for development using the commands below. If you don't have it already, you need to install poetry first.

# Clone the repo
git clone https://github.com/simonepri/lm-scorer
# CD into the created folder
cd lm-scorer
# Create a virtualenv and install the required dependencies using poetry
poetry install

You can then run commands inside the virtualenv by using poetry run COMMAND.
Alternatively, you can open a shell inside the virtualenv using poetry shell.

If you wish to contribute to this project, run the following commands locally before opening a PR and check that no error is reported (warnings are fine).

# Run the code formatter
poetry run task format
# Run the linter
poetry run task lint
# Run the static type checker
poetry run task types
# Run the tests
poetry run task tests

Authors

• Simone Primarosa - simonepri

See also the list of contributors who participated in this project.

License

This project is licensed under the MIT License - see the license file for details.