Instructions to use willem640/grc_grammateus_classifier_documentary_greberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use willem640/grc_grammateus_classifier_documentary_greberta with spaCy:
!pip install https://huggingface.co/willem640/grc_grammateus_classifier_documentary_greberta/resolve/main/grc_grammateus_classifier_documentary_greberta-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("grc_grammateus_classifier_documentary_greberta") # Importing as module. import grc_grammateus_classifier_documentary_greberta nlp = grc_grammateus_classifier_documentary_greberta.load() - Notebooks
- Google Colab
- Kaggle
metadata
tags:
- spacy
- text-classification
language:
- grc
model-index:
- name: grc_grammateus_classifier_documentary_greberta
results: []
license: cc-by-4.0
datasets:
- willem640/MAAT_documentary_with_DDbDP_and_HGV_metadata
base_model:
- bowphs/GreBerta
library_name: spacy
| Feature | Description |
|---|---|
| Name | grc_grammateus_classifier_documentary_greberta |
| Version | 0.0.0 |
| spaCy | >=3.8.7,<3.9.0 |
| Default Pipeline | transformer, textcat |
| Components | transformer, textcat |
| License | CC-BY-4.0 |
| Author | willem640 |
Label Scheme
View label scheme (4 labels for 1 components)
| Component | Labels |
|---|---|
textcat |
Epistolary Exchange, Objective Statement, Recording of Information, Transmission of Information |
This model will classify papyri with the main categories of the Grammateus (https://grammateus.unige.ch/).
Accuracy
| Type | Score |
|---|---|
CATS_SCORE |
94.70 |
CATS_MICRO_P |
94.92 |
CATS_MICRO_R |
94.92 |
CATS_MICRO_F |
94.92 |
CATS_MACRO_P |
95.23 |
CATS_MACRO_R |
94.33 |
CATS_MACRO_F |
94.70 |
CATS_MACRO_AUC |
99.31 |
TRANSFORMER_LOSS |
1928.72 |
TEXTCAT_LOSS |
856.51 |