Skip to main content

Energy Language Model

Project description

The Energy Language Model (ELM) software provides interfaces to apply Large Language Models (LLMs) like ChatGPT and GPT-4 to energy research. For example, you might be interested in:

Installing ELM

  1. from home dir, git clone git@github.com:NREL/elm.git

  2. Create elm environment and install package
    1. Create a conda env: conda create -n elm

    2. Run the command: conda activate elm

    3. cd into the repo cloned in 1.

    4. Prior to running pip below, make sure the branch is correct (install from main!)

    5. Install elm and its dependencies by running: pip install . (or pip install -e . if running a dev branch or working on the source code)

Acknowledgments

This work was authored by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided by the DOE Wind Energy Technologies Office (WETO), the DOE Solar Energy Technologies Office (SETO), and internal research funds at the National Renewable Energy Laboratory. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes.

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

NREL-elm-0.0.0.tar.gz (22.5 kB view details)

Uploaded Source

Built Distribution

NREL_elm-0.0.0-py3-none-any.whl (27.4 kB view details)

Uploaded Python 3

File details

Details for the file NREL-elm-0.0.0.tar.gz.

File metadata

  • Download URL: NREL-elm-0.0.0.tar.gz
  • Upload date:
  • Size: 22.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/4.0.2 CPython/3.11.6

File hashes

Hashes for NREL-elm-0.0.0.tar.gz
Algorithm Hash digest
SHA256 997893547431d2dc91bc58a914334e2159089ed2b11b3d24bc1ed7807c2fd6e9
MD5 b5c398919401110ca7f866418fdee8cb
BLAKE2b-256 96e4f976f72f61655414b34d2ee67872938fb8ae52f6acae1842aac599ac89f0

See more details on using hashes here.

File details

Details for the file NREL_elm-0.0.0-py3-none-any.whl.

File metadata

  • Download URL: NREL_elm-0.0.0-py3-none-any.whl
  • Upload date:
  • Size: 27.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/4.0.2 CPython/3.11.6

File hashes

Hashes for NREL_elm-0.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 f1bb13e4071e161f6dc13ee4d168ea7d6370f5016368a64b04719c925d662270
MD5 311bfd693a71bd4c535ce0ca89913218
BLAKE2b-256 286887ef6987b7a0b186c43ad5010b85c12e8d1bf3379a581413cc823a0875d2

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