Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use alwaysgetbetter/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alwaysgetbetter/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="alwaysgetbetter/bert-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("alwaysgetbetter/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("alwaysgetbetter/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7e782b3f1709b363d6596582dfb143afe6ea83747b092738662c7f0687774fdb
- Size of remote file:
- 3.18 kB
- SHA256:
- 2a6d715415a9aed2a00e2120fe4922b299bd15b12bc90834f277cbe995e77fe5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.