Instructions to use nlpso/m0_flat_ner_ocr_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_ocr_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_ocr_ptrn_cmbert_io")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("nlpso/m0_flat_ner_ocr_ptrn_cmbert_io") model = AutoModelForTokenClassification.from_pretrained("nlpso/m0_flat_ner_ocr_ptrn_cmbert_io") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- db8c266fd4d78bde64e1de980aeb394da2d1f4220fea0cdfdc396fe7e24b2238
- Size of remote file:
- 3.5 kB
- SHA256:
- e8a84955445123f1e446e55dc128a8508559a9b17b726e9b83d950e1dd479e87
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