Skip to main content

Zero-shot classification package using Transformers

Project description

from classifierPratik import ZeroShotClassifier

Initialize the classifier

clf = ZeroShotClassifier()

Define your text and candidate labels

text = "Book me a flight to Paris" labels = ["healthcare", "travel", "not_answerable"]

Predict the best label

best_label = clf.predict(text, labels) print(best_label) # Output: "travel"

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

classifierpratik-0.0.0.tar.gz (2.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

classifierpratik-0.0.0-py3-none-any.whl (2.8 kB view details)

Uploaded Python 3

File details

Details for the file classifierpratik-0.0.0.tar.gz.

File metadata

  • Download URL: classifierpratik-0.0.0.tar.gz
  • Upload date:
  • Size: 2.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.2

File hashes

Hashes for classifierpratik-0.0.0.tar.gz
Algorithm Hash digest
SHA256 6fab20d671949ce8a376765aed5571916de16928531477e074accaeb49e07dea
MD5 0827021b6a35cd8cbb8359283c918216
BLAKE2b-256 fb77738c84de418b424aacc0ce081b7a6a8173a314fff9e0ed7701483fe5e7ad

See more details on using hashes here.

File details

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

File metadata

File hashes

Hashes for classifierpratik-0.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 833242b2737b32cc870265729daed0ba712c34622f6b74c50fc417d3f807f2d1
MD5 7e43def99f7375f75446ea4954c82856
BLAKE2b-256 e55378b6c4ed31af035089932e259b33b34cd590638c2f2a83973f5fca18a8db

See more details on using hashes here.

Supported by

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