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:
- 8ae70c3f9cbb924eacb79877c12972937b854f77b9a2c9d01a9eb5eb029b6a7c
- Size of remote file:
- 431 MB
- SHA256:
- d3105719719ebb2b6e05c8ca8562e6e2c3616d41eaa137b84e30c942c79650f9
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