Skip to main content

A Python package for analyzing and transforming neural latent spaces.

Project description

:construction::construction::construction: Developers At Work. The library will be ready next month. Feel free to contact us directly for any specific request! :construction::construction::construction:


Latentis: Your Gateway to Latent Space Communication

CI Coverage Docs Python Code style: black

Welcome to Latentis, the first-of-its-kind Python library dedicated to the innovative field of Latent Space Communication. Latentis is designed to empower researchers, data scientists, and enthusiasts to unlock new insights by providing a comprehensive suite of tools where latent spaces are the core ingredient.

Core Features

Latentis offers a structured suite of tools designed for efficiency and ease of use:

  • Data Download & Processing: streamline the acquisition and preparation of complex datasets (via HuggingFace Datasets).
  • Advanced Encoding: either employ pre-trained models or bring your own to encode anything.
  • Benchmarking Tools: standard and customizable benchmarking tools, allowing for thorough evaluation and refinement of methods.

Getting Started

Ease into your next research project with:

pip install latentis

Development installation

Setup the development environment:

git clone git@github.com:flegyas/latentis.git
cd latentis
conda env create -f env.yaml
conda activate latentis
pre-commit install

Run the tests:

pre-commit run --all-files
pytest -v

Update the dependencies

Re-install the project in edit mode:

pip install -e .[dev]

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

latentis-0.0.8.tar.gz (75.7 kB view details)

Uploaded Source

Built Distribution

latentis-0.0.8-py3-none-any.whl (67.7 kB view details)

Uploaded Python 3

File details

Details for the file latentis-0.0.8.tar.gz.

File metadata

  • Download URL: latentis-0.0.8.tar.gz
  • Upload date:
  • Size: 75.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.0.0 CPython/3.12.3

File hashes

Hashes for latentis-0.0.8.tar.gz
Algorithm Hash digest
SHA256 a868a4351a7d834afdc7df09afe3f699f2d55b76fd43a77a15359075ac74d26b
MD5 298479c8a3c3f13b195c9b96c36c6a1a
BLAKE2b-256 5af4851a7421b0fd77edb36fc2359d05552c7ebf2599dfe22cb052aa98b19980

See more details on using hashes here.

File details

Details for the file latentis-0.0.8-py3-none-any.whl.

File metadata

  • Download URL: latentis-0.0.8-py3-none-any.whl
  • Upload date:
  • Size: 67.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.0.0 CPython/3.12.3

File hashes

Hashes for latentis-0.0.8-py3-none-any.whl
Algorithm Hash digest
SHA256 1ca2d2e1c8288a7b8d635b409586ee85c139865109059bedec7ccdd332a38bd2
MD5 c81f731d5354be974df871b6cdc09223
BLAKE2b-256 fa3a0612499c4ddc9797ef269e5d72dbd714ec685960816df7599f4481c85a7d

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page