Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use gagan3012/bert-tiny-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gagan3012/bert-tiny-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="gagan3012/bert-tiny-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("gagan3012/bert-tiny-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("gagan3012/bert-tiny-finetuned-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aaf8e9046e427107401234c0047e3bc38c726311e9a811c9025f841e7f689e3e
- Size of remote file:
- 17.5 MB
- SHA256:
- 0d10049bb6ee5ff10f0a73fd1ca30100a563dc0d5019fa4470123a319424c909
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