Token Classification
Transformers
ONNX
Safetensors
xlm-roberta
ner
on-device
privacy
flowx
openner
cross
de-identification
Instructions to use flowxai/piiguard with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flowxai/piiguard with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="flowxai/piiguard")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("flowxai/piiguard") model = AutoModelForTokenClassification.from_pretrained("flowxai/piiguard", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff4bbb04753778c1b75af23a75d28a60f0fe78a4446f39b20029b84e6cf0162b
- Size of remote file:
- 1.11 GB
- SHA256:
- d3087fa8d98b33ea98e122b72c88c7af177c95b7e530f929ab5061937df6601a
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