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")# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload README.md with huggingface_hub
a3d6473
-
Upload README.md with huggingface_hub
d1cc05e -
Upload README.md with huggingface_hub
10a26c4 -
Upload README.md with huggingface_hub
9c326bf -
Upload README.md with huggingface_hub
70162a6
-
Upload README.md with huggingface_hub
9e1d048 -
Load model and tokenizer
20c292d -
initial commit
b10109a