Instructions to use nlpso/m0_flat_ner_ref_ptrn_cmbert_io with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlpso/m0_flat_ner_ref_ptrn_cmbert_io with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="nlpso/m0_flat_ner_ref_ptrn_cmbert_io")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("nlpso/m0_flat_ner_ref_ptrn_cmbert_io") model = AutoModelForTokenClassification.from_pretrained("nlpso/m0_flat_ner_ref_ptrn_cmbert_io", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 31299961544f891c5f3d46c27f1b297821514c299329d839fe09a9883feddd5c
- Size of remote file:
- 3.5 kB
- SHA256:
- 2c2dac3cb81648f330557a480beef0e9e0e88d34e95f751a64b643dd4e486ad9
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