Skip to main content

Benchmarking procedure to test approaches on the PET-dataset (hosted on huggingface).

This is an beta version.

Documentation will come soon.

Example of ‘’how to benchmark an approach’’

from petbenchmarks.benchmarks import BenchmarkApproach

BenchmarkApproach(tested_approach_name='Approach-name',
                  predictions_file_or_folder='path-to-prediction-file.json')

The BenchmarkApproach object does all the job. It reads the prediction file, computes score and generates a reports.

Created by Patrizio Bellan.

Download files

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

Source Distribution

petbenchmarks-0.0.2.tar.gz (12.6 kB view details)

Uploaded Source

File details

Details for the file petbenchmarks-0.0.2.tar.gz.

File metadata

  • Download URL: petbenchmarks-0.0.2.tar.gz
  • Upload date:
  • Size: 12.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.5

File hashes

Hashes for petbenchmarks-0.0.2.tar.gz
Algorithm Hash digest
SHA256 da094f8404e47cbb07476fb10075ab754014a7c9b017188681fb27276b4f4634
MD5 32b325b35402897ae0f355f24a4719a3
BLAKE2b-256 39386b715b6d9b0b570293f4dcae2acf270b2846f02d6307098bf21f56587cf9

See more details on using hashes here.

Release history Release notifications | RSS feed

This release

0.0.2 This release

1 file

0.0.1

1 file

Supported by

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