Skip to main content

Natural Language Processing by the Exciton Research

Project description

Exciton NLP - A tool for natural language processing

Exciton NLP is designed and maintained by the Exciton Research for different NLP tasks, including multilingual classification, NER, translation, etc.

Installation

Use pip to install exciton. Run:

pip install -U exciton

Usage


from exciton.nlp.translation import M2M100

model = M2M100(model="m2m100_1.2b", device="cuda")
source = [
    {"id": 1, "source": "I love you!", "source_lang": "en", "target_lang": "zh"},
    {"id": 2, "source": "我爱你!", "source_lang": "zh", "target_lang": "en"}
]
results = model.predict(source)

Project details


Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

exciton-2.9.1-py3-none-any.whl (50.3 kB view details)

Uploaded Python 3

File details

Details for the file exciton-2.9.1-py3-none-any.whl.

File metadata

  • Download URL: exciton-2.9.1-py3-none-any.whl
  • Upload date:
  • Size: 50.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.12

File hashes

Hashes for exciton-2.9.1-py3-none-any.whl
Algorithm Hash digest
SHA256 cf2ed30fd58ff0bb555c52c61e8af5b153610848878d3767121d86e91afe72d9
MD5 500be06f45bae61d871b694d898e0e2e
BLAKE2b-256 e3fbad43c6005f54436251060055fe722efe2c165f484553aa9c4e7ba9f258f8

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