Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use ish97/bert-finetuned-chunking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ish97/bert-finetuned-chunking with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ish97/bert-finetuned-chunking")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ish97/bert-finetuned-chunking") model = AutoModelForTokenClassification.from_pretrained("ish97/bert-finetuned-chunking") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d09d8a3d749c65135bab1fbc6d023a4aa54ae82be1c70560d860b29e47402351
- Size of remote file:
- 431 MB
- SHA256:
- 8bfb9bcee6c47077fc9668effcea2bc441983cc51d91e32696f4cdc8cf5614a3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.