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:
- 429ffc32d1c34610967088da481c31b0478df1018fe7f66a2c82b2f51ef84b25
- Size of remote file:
- 598 MB
- SHA256:
- ae9588cfcc13be628e6989f0b06daf474a080adb145d3f32ea30886ea848d3b0
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