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-2.4.1-py3-none-any.whl (70.8 kB view details)

Uploaded Python 3

File details

Details for the file exciton-2.4.1-py3-none-any.whl.

File metadata

  • Download URL: exciton-2.4.1-py3-none-any.whl
  • Upload date:
  • Size: 70.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.12

File hashes

Hashes for exciton-2.4.1-py3-none-any.whl
Algorithm Hash digest
SHA256 0c4feefc0008c58e3c0d5f28b95b77241cce13c45ae3269a49da50edf01ec47b
MD5 ec3348c40b3e709fe562aa4ddb382522
BLAKE2b-256 bb256701720e54e53f629fe6c75a438636d64a0b226020c8bcf43ffd381102eb

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