Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use mateocolina/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mateocolina/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mateocolina/bert-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mateocolina/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("mateocolina/bert-finetuned-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0ee5907819ed0f646e84ec67e268a8702640be3afa684acbbe0e9a7c47f2aacb
- Size of remote file:
- 3.18 kB
- SHA256:
- 536814646b3a0ffb67c7328a7684bafeae6aaaf6c90eaed361d509da896e4c67
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