Instructions to use EMBO/bert-base-cased_NER-task with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EMBO/bert-base-cased_NER-task with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="EMBO/bert-base-cased_NER-task")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("EMBO/bert-base-cased_NER-task") model = AutoModelForTokenClassification.from_pretrained("EMBO/bert-base-cased_NER-task", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8f0403438a7346538a539f179988d1a8854b260f54d67632128789db138de20c
- Size of remote file:
- 431 MB
- SHA256:
- 92b2fea8cd086661eb988c0bea7b142c1c168e6b3db297f20e8b9b74ffd60ccc
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