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:
- 26b86ec04557b01a85698e5033a67ea43a6164c1ea6b942cb96ffc11239b661c
- Size of remote file:
- 623 Bytes
- SHA256:
- ec6331a2d4f82e15c898be3d09fa0a39ccbc9d6fd132b0505ce16e06776b6d8e
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