Instructions to use Mar-C/BERT-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mar-C/BERT-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Mar-C/BERT-NER")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Mar-C/BERT-NER") model = AutoModelForTokenClassification.from_pretrained("Mar-C/BERT-NER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download BERT_ner_cpu from Mar-C/BERT-NER: direct link, hf CLI and curl.
- Browser
- Download file 0 Bytes
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https://huggingface.co/Mar-C/BERT-NER/resolve/main/BERT_ner_cpu
- Command line
-
hf download hf://Mar-C/BERT-NER/BERT_ner_cpu
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curl -L -o BERT_ner_cpu https://huggingface.co/Mar-C/BERT-NER/resolve/main/BERT_ner_cpu
0 Bytes