COMBO UD 2.17 Models
Collection
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This is a French-language model based on COMBO-NLP, an open-source natural language preprocessing system. It performs:
The French model uses FacebookAI/xlm-roberta-base as its base encoder and is trained on UD_French-Sequoia (UD v2.17).
Evaluation was performed on the UD_French-Sequoia test split using the standard CoNLL 2018 eval script.
Two evaluation rows are reported:
| Metric | Tokens | Sentences | Words | UPOS | XPOS | UFeats | AllTags | Lemmas |
|---|---|---|---|---|---|---|---|---|
| Full-text (F1) | 99.64 | 88.84 | 99.26 | 98.51 | 99.26 | 96.66 | 96.46 | 98.43 |
| Aligned accuracy | 0.00 | 0.00 | 0.00 | 99.25 | 100.00 | 97.39 | 97.18 | 99.17 |
| Metric | UAS | LAS | CLAS | MLAS | BLEX |
|---|---|---|---|---|---|
| Full-text (F1) | 93.85 | 92.55 | 89.93 | 85.21 | 88.84 |
| Aligned accuracy | 94.55 | 93.24 | 90.36 | 85.61 | 89.26 |
Install the library from PyPI (assuming you have a virtual environment created):
pip install combo-nlp
Install the Lambo segmenter - only needed when passing raw text strings to COMBO:
pip install --index-url https://pypi.clarin-pl.eu/ lambo
from combo import COMBO
# Load a pre-trained model with corresponding Lambo segmenter
nlp = COMBO("French")
# Parse raw text (handles sentence splitting + tokenization)
result = nlp("Le renard brun rapide saute par-dessus le chien paresseux.")
# Inspect results
for sentence in result:
for token in sentence:
print(f"{token.form:<15} {token.lemma:<15} {token.upos:<8} head={token.head} {token.deprel}")
Refer to the COMBO-NLP documentation for installation and usage instructions: