Instructions to use tesemnikov-av/NER-RUBERT-Per-Loc-Org with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tesemnikov-av/NER-RUBERT-Per-Loc-Org with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="tesemnikov-av/NER-RUBERT-Per-Loc-Org")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("tesemnikov-av/NER-RUBERT-Per-Loc-Org") model = AutoModelForTokenClassification.from_pretrained("tesemnikov-av/NER-RUBERT-Per-Loc-Org", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 393 Bytes
5f51974 3dcd03e d9ca168 3f5ca3b d9ca168 805d2cd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ---
widget:
- text: "В город Сергиев Посад приехал Курт Кобейн."
---
Fine-tuning [cointegrated/rubert-tiny](https://huggingface.co/cointegrated/rubert-tiny) model on sentences from Wiki auto annotated with PER, LOC, ORG tags [corus/WiNER](https://pypi.org/project/corus/#reference)
language: RU
NER Class:
- PER
- LOC
- ORG
license: mit
|