Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use ocm/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ocm/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ocm/bert-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ocm/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("ocm/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd926c2fd50d6406ee5bade6d14af30910ff2ea9757ee9daf8b100430aace65a
- Size of remote file:
- 431 MB
- SHA256:
- a1a0beb30e7bc75806f1f455c92c5547ff49949a3c7837ecb8db73d2bc189538
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