Instructions to use protectai/bert-base-NER-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use protectai/bert-base-NER-onnx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="protectai/bert-base-NER-onnx")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("protectai/bert-base-NER-onnx") model = AutoModelForTokenClassification.from_pretrained("protectai/bert-base-NER-onnx", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.onnx from protectai/bert-base-NER-onnx: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/protectai/bert-base-NER-onnx/resolve/main/model.onnx
- Command line
-
hf download hf://protectai/bert-base-NER-onnx/model.onnx
-
curl -L -o model.onnx https://huggingface.co/protectai/bert-base-NER-onnx/resolve/main/model.onnx
431 MB
- Xet hash:
- 7161208c13d6c1f42815fb58058d68ca14c0139c3612954ccb0f02276e6732e8
- Size of remote file:
- 431 MB
- SHA256:
- e2165e300f6e0016c1f295bcdee36e084371e1f4f3564cd7e47cb833b58a75b7
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