Token Classification
Transformers
ONNX
Safetensors
modernbert
ner
on-device
privacy
flowx
openner
insurance
de-identification
Instructions to use flowxai/perilclassify with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flowxai/perilclassify with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="flowxai/perilclassify")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("flowxai/perilclassify") model = AutoModelForTokenClassification.from_pretrained("flowxai/perilclassify", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a0fbd90b75cfa6a6c40075d629443eb2d25921cba703e13cfbac0d3b2072764d
- Size of remote file:
- 2.62 MB
- SHA256:
- 30c00a6810013013de8938d8f6047b907ba0b6a92872784ccd5ce5182fb06e69
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