Language Model Zoo
The Language Model Zoo is an open-source repository of state-of-the-art
language models, designed to support black-box access to model predictions and
representations. It provides the command line tool lm-zoo, a standard
interface for interacting with language models.
You can use lm-zoo to
- compute language model predictions at the word level,
- extract token-level surprisal data (popularly used in psycholinguistic experiments), and
- preprocess corpora according to a language model's particular tokenization standards.
Quick links:
Getting started
Running language models from this repository requires Docker.
You can install the lm-zoo via pip:
$ pip install lm-zoo
List available language models:
$ lm-zoo list
gpt2
Image URI: docker.io/cpllab/language-models:gpt2
Full name: None
Reference URL: https://openai.com/blog/better-language-models/
Maintainer: None
Last updated: None
RNNG
Image URI: docker.io/cpllab/language-models:rnng
Full name: None
Reference URL: TODO
Maintainer: None
Last updated: None
ordered-neurons
Image URI: docker.io/cpllab/language-models:ordered-neurons
Full name: None
Reference URL: https://github.com/yikangshen/Ordered-Neurons
Maintainer: None
Last updated: None
...
Tokenize some text according to a language model's standard:
$ wget https://cpllab.github.io/lm-zoo/metamorphosis.txt -O metamorphosis.txt
$ lm-zoo tokenize gpt2 metamorphosis.txt
Pulling latest Docker image for cpllab/language-models:gpt2.
One Ġmorning , Ġwhen ĠGreg or ĠSam sa Ġwoke Ġfrom Ġtroubled Ġdreams , Ġhe Ġfound Ġhimself Ġtransformed Ġin Ġhis Ġbed Ġinto Ġa Ġhorrible Ġver min .
He Ġlay Ġon Ġhis Ġarmour - like Ġback , Ġand Ġif Ġhe Ġlifted Ġhis Ġhead Ġa Ġlittle Ġhe Ġcould Ġsee Ġhis Ġbrown Ġbelly , Ġslightly Ġdom ed Ġand Ġdivided Ġby Ġar ches Ġinto Ġstiff Ġsections .
The Ġbed ding Ġwas Ġhardly Ġable Ġto Ġcover Ġit Ġand Ġseemed Ġready Ġto Ġslide Ġoff Ġany Ġmoment .
...
Get token-level surprisals for text data:
$ lm-zoo get-surprisals ngram metamorphosis.txt
sentence_id token_id token surprisal
1 1 one 7.76847
1 2 morning 9.40638
1 3 , 1.05009
1 4 when 7.08489
1 5 gregor 18.8963
1 6 <unk> 4.27466
1 7 woke 19.0607
1 8 from 10.3404
1 9 troubled 17.478
1 10 dreams 10.671
1 11 , 3.39374
1 12 he 5.99193
1 13 found 8.07358
1 14 himself 2.92718
1 15 transformed 16.7328
1 16 in 5.32057
1 17 his 7.26454
1 18 bed 9.78166
1 19 into 8.90954
1 20 a 3.72355
1 21 horrible 14.2477
1 22 <unk> 3.56907
1 23 . 3.90242
1 24 </s> 22.8395
2 1 he 4.43708
2 2 lay 14.1721
...
For more information, see our Quickstart tutorial.
Metadata
Release files for lm-zoo 1.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| lm-zoo-1.3.tar.gz | 19.2 kB | Without provenance | Details |
Release files / lm-zoo-1.3.tar.gz
| Download URL | lm-zoo-1.3.tar.gz |
|---|---|
| Size | 19.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
064959ba93eb73edaf4a4f2d75d02640e26b48f9f272b919f4f8d4d3a85238d6
|
|
BLAKE2b-256 checksum How to use checksums |
bec6bdfa2be8f1e0c91b80c7503142bf9dbef9c37efc870d978cda349cf98445
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/4.8.2 pkginfo/1.7.0 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.7.6
|
Security for lm-zoo 1.3
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.