Token Classification
Transformers
PyTorch
TensorBoard
Safetensors
roberta
Generated from Trainer
Eval Results (legacy)
Instructions to use raulgdp/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use raulgdp/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="raulgdp/bert-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("raulgdp/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("raulgdp/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4dda59eaf30cc014fe3cd10dda1f3ee233beae6843de6aee029a5e0afe81e7ac
- Size of remote file:
- 5.24 kB
- SHA256:
- 06f5657c7cb57a86f4eb9bec5fe92bdb02efa545c4c960c2907319041143d4a9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.