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-2.3.0-py3-none-any.whl (68.6 kB view details)

Uploaded Python 3

File details

Details for the file exciton-2.3.0-py3-none-any.whl.

File metadata

  • Download URL: exciton-2.3.0-py3-none-any.whl
  • Upload date:
  • Size: 68.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.12

File hashes

Hashes for exciton-2.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 590e6d6cb1339ca24bf57cf606c801a6c787dc550d9b5bb2bb3e8e442fd8e6ed
MD5 bc9f04c477588b64175730fc893bc841
BLAKE2b-256 8e4a5ca020b7efccfbe25ff7d9b889c75f7f45058afacfd6e7f39ace0ef75063

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