Token Classification
Transformers
PyTorch
Ukrainian
roberta
ukrainian
pos
ubertext
dependency-parsing
Instructions to use KoichiYasuoka/roberta-base-ukrainian-upos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KoichiYasuoka/roberta-base-ukrainian-upos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="KoichiYasuoka/roberta-base-ukrainian-upos")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("KoichiYasuoka/roberta-base-ukrainian-upos") model = AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/roberta-base-ukrainian-upos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| #! /usr/bin/python3 | |
| src="KoichiYasuoka/roberta-base-ukrainian" | |
| tgt="KoichiYasuoka/roberta-base-ukrainian-upos" | |
| import os,sys | |
| os.system("test -d UD_Ukrainian-IU || git clone --depth=1 https://github.com/UniversalDependencies/UD_Ukrainian-IU") | |
| os.system("test -d UD_Ukrainian-ParlaMint || git clone --depth=1 https://github.com/UniversalDependencies/UD_Ukrainian-ParlaMint") | |
| os.system("for F in train dev test ; do cat UD_Ukrainian-*/*-$F.conllu > $F.conllu ; done ; cat *.conllu > train.upos") | |
| os.system(f"{sys.executable} -m esupar.train {src} {tgt} -16 /tmp train.upos") | |
| os.system(f"{sys.executable} -m esupar.train {tgt} {tgt} 16 /// train.conllu dev.conllu test.conllu") | |