Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use Ce/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ce/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Ce/bert-finetuned-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Ce/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("Ce/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Ce/bert-finetuned-ner: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/Ce/bert-finetuned-ner/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Ce/bert-finetuned-ner/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Ce/bert-finetuned-ner/resolve/main/pytorch_model.bin
431 MB
- Xet hash:
- 9925ae8d6dc13720bdb7cba52aecb684ed29b86c53fe336eebe2b2ab3d4ecee7
- Size of remote file:
- 431 MB
- SHA256:
- b0b7d56fd42ba311c71029e03f2aec665d4df98f4ad1b7586b4646e2646b3543
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