A wrapper for ONNX models that adheres to the instancelib specification
Project description
instancelib-onnx
ONNX extension for instancelib.
Installation
You can install this package as follows:
pip install instancelib-onnx
Or by cloning this repo and issuing:
python setup.py
You will need at least Python 3.8 to use this library.
Usage
import instancelib as il
import ilonnx
# Specify the model location and the label translation
model = ilonnx.build_data_model("example_models/data-model.onnx",
{0: "Bedrijfsnieuws", 1: "Games", 2: "Smartphones"})
Then you can use the normal instancelib functionality to interact with the model.
# Load a dataset with instancelib
env = il.read_excel_dataset("datasets/testdataset.xlsx", ["fulltext"], ["label"])
# Assess the performance like any other instancelib model
performance = il.classifier_performance(model, env.dataset, env.labels)
performance.confusion_matrix
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
instancelib-onnx-0.1.3.tar.gz
(19.6 kB
view hashes)
Built Distribution
Close
Hashes for instancelib_onnx-0.1.3-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 14ab08034db3ef16ca2722c9a8a996ce3a133a35568ae540a99a261ae1cf7537 |
|
MD5 | 712f1bc16ea5581774506aaf0e8e326e |
|
BLAKE2b-256 | bb76b3655c11bf9a43d3137eb350b214ccf444f35ae26e6290dcf737eefdfef3 |