Instructions to use nlpso/m0_flat_ner_ocr_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_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_cmbert_io")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("nlpso/m0_flat_ner_ocr_cmbert_io") model = AutoModelForTokenClassification.from_pretrained("nlpso/m0_flat_ner_ocr_cmbert_io", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from nlpso/m0_flat_ner_ocr_cmbert_io: direct link, hf CLI and curl.
- Browser
- Download file 2.42 MB
-
https://huggingface.co/nlpso/m0_flat_ner_ocr_cmbert_io/resolve/main/tokenizer.json
- Command line
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hf download hf://nlpso/m0_flat_ner_ocr_cmbert_io/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/nlpso/m0_flat_ner_ocr_cmbert_io/resolve/main/tokenizer.json
2.42 MB
File too large to display, you can check the raw version instead.