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:
- 75103341091914feffcc029d4a1f280303698faf98752942bd0d2e4c9dd43c90
- Size of remote file:
- 598 MB
- SHA256:
- 43a9e2a68f7a95e4893fe5c82525a356bca88c33ca404f6310498c7cb9a22a3d
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