Token Classification
Transformers
ONNX
Safetensors
modernbert
ner
on-device
privacy
flowx
openner
insurance
de-identification
Instructions to use flowxai/insurredact with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flowxai/insurredact with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="flowxai/insurredact")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("flowxai/insurredact") model = AutoModelForTokenClassification.from_pretrained("flowxai/insurredact", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f7ca098faaaac192952267ea4fd6c9d51a213fce4ec5657bf694aa191a7839f8
- Size of remote file:
- 5.2 kB
- SHA256:
- ae65ef246c4b6e55c818d1766663d53d5effdba6ebd89a58d056fd17df38809d
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