Token Classification
Transformers
ONNX
Safetensors
modernbert
ner
on-device
privacy
flowx
openner
banking
de-identification
Instructions to use flowxai/ibandetect with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flowxai/ibandetect with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="flowxai/ibandetect")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("flowxai/ibandetect") model = AutoModelForTokenClassification.from_pretrained("flowxai/ibandetect", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 423cc6ded0435f90082ca4aae9aec59d7932b24c8b7e8db84ba13b6b0ca0449c
- Size of remote file:
- 5.2 kB
- SHA256:
- e7b81b79e609ce0dfa3960c7eddcfd9579643d2b1ef6dfe09f8539bef9886e06
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