Instructions to use arubenruben/NER-PT-BERT-CRF-HAREM-Default with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arubenruben/NER-PT-BERT-CRF-HAREM-Default with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="arubenruben/NER-PT-BERT-CRF-HAREM-Default", trust_remote_code=True)# Load model directly from transformers import AutoModelForTokenClassification model = AutoModelForTokenClassification.from_pretrained("arubenruben/NER-PT-BERT-CRF-HAREM-Default", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6d9789413fa9e16dd147a124bc54f6959483459bb262959642d3674173c91520
- Size of remote file:
- 1.34 GB
- SHA256:
- 66a60d10ec43c534b098fdfd34bad5889637c62c0840c83f1404f6843b38cbb9
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