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
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Download README.md from tesemnikov-av/NER-RUBERT-Per-Loc-Org: direct link, hf CLI and curl.
- Browser
- Download file 393 Bytes
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https://huggingface.co/tesemnikov-av/NER-RUBERT-Per-Loc-Org/resolve/main/README.md
- Command line
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hf download hf://tesemnikov-av/NER-RUBERT-Per-Loc-Org/README.md
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curl -L -o README.md https://huggingface.co/tesemnikov-av/NER-RUBERT-Per-Loc-Org/resolve/main/README.md
393 Bytes
| 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 | |