Token Classification
Transformers
ONNX
Safetensors
modernbert
ner
on-device
privacy
flowx
openner
banking
de-identification
Instructions to use flowxai/txnclassify with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flowxai/txnclassify with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="flowxai/txnclassify")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("flowxai/txnclassify") model = AutoModelForTokenClassification.from_pretrained("flowxai/txnclassify", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 148fa564d676ba5c96a37ac7f67831f328b728d2a598d2717127220bbc08e6b7
- Size of remote file:
- 598 MB
- SHA256:
- ef64d20ab754df16bbdaee47cf9cbb53d1d62c6e2ce25e056e5570641513e1d4
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