Instructions to use mpalaval/bert-ner-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mpalaval/bert-ner-5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mpalaval/bert-ner-5")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mpalaval/bert-ner-5") model = AutoModelForTokenClassification.from_pretrained("mpalaval/bert-ner-5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d0401a17584e27c3023fbf1d10f87f9aa8fbebcacf9ff5015d48f48cd616e35d
- Size of remote file:
- 4.54 kB
- SHA256:
- e41a93d78fa58818400ec95ce5b3f1f3901b985f32158023766a9ff11dd32729
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