Token Classification
Transformers
PyTorch
TensorBoard
Safetensors
English
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use nickprock/bert-finetuned-ner-ontonotes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nickprock/bert-finetuned-ner-ontonotes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="nickprock/bert-finetuned-ner-ontonotes")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("nickprock/bert-finetuned-ner-ontonotes") model = AutoModelForTokenClassification.from_pretrained("nickprock/bert-finetuned-ner-ontonotes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from nickprock/bert-finetuned-ner-ontonotes: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/nickprock/bert-finetuned-ner-ontonotes/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://nickprock/bert-finetuned-ner-ontonotes/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/nickprock/bert-finetuned-ner-ontonotes/resolve/main/pytorch_model.bin
431 MB
- Xet hash:
- 7e2dc2a3cb3aa0087f8a38a730579755526cd8b031c0c0459826d6c2cd408fb9
- Size of remote file:
- 431 MB
- SHA256:
- d9d64a64cb7b00d84a8872fae882d11c9466c5c85795c543e39f6a335a4ee3d6
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