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"
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file classifierpratik-0.0.2.tar.gz.
File metadata
- Download URL: classifierpratik-0.0.2.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
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
8b90cde44cce463639808437453ba47d6ffa958029844d848b96d0210f385eac
|
|
| MD5 |
a7290b220497d8590e145b57c17e8eae
|
|
| BLAKE2b-256 |
18cb83a20dcf260fdc9abbd1413d9b47672a1aa40e239db2efb69c5cc9a1d4ee
|
File details
Details for the file classifierpratik-0.0.2-py3-none-any.whl.
File metadata
- Download URL: classifierpratik-0.0.2-py3-none-any.whl
- Upload date:
- Size: 3.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.13.2
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
b9aae81fd3f75b9846b8b01d4441ad948b782b3db8017ef69d7a8a8da48a13d5
|
|
| MD5 |
81214a7d5c637db611da3b91a490e6bb
|
|
| BLAKE2b-256 |
7f7401c1224681cebadda68c0b1a73ed9238cb92e64fb05c9da994377db16154
|
