Instructions to use Yayasb/morocco-bo-domain-classifier-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use Yayasb/morocco-bo-domain-classifier-v1 with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("Yayasb/morocco-bo-domain-classifier-v1", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
Add model card
Browse files
README.md
ADDED
|
@@ -0,0 +1,19 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
library_name: sklearn
|
| 4 |
+
tags:
|
| 5 |
+
- text-classification
|
| 6 |
+
- scikit-learn
|
| 7 |
+
- french
|
| 8 |
+
- legal
|
| 9 |
+
- morocco
|
| 10 |
+
---
|
| 11 |
+
|
| 12 |
+
# Morocco BO Domain Classifier V1
|
| 13 |
+
|
| 14 |
+
TF-IDF + Logistic Regression for Moroccan Bulletin Officiel domain classification.
|
| 15 |
+
|
| 16 |
+
- `pipeline.joblib` — full sklearn Pipeline
|
| 17 |
+
- `weights.joblib` — exported arrays for numpy inference
|
| 18 |
+
|
| 19 |
+
Demo Space: https://huggingface.co/spaces/Yayasb/morocco-bo-domain-classifier
|