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:
- d79f27bf527e26763c153e738668c26511403e2e4f0674592df6f341aa0c3351
- Size of remote file:
- 598 MB
- SHA256:
- 7172d42837550a6b07c7e3c7cf9e5982dd5a0104cda817081a9198078e3c021e
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