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:
- 4bd8206f7765dd58920a236f7bf356b91248ef531b8c4b862393dd0a2e0664d0
- Size of remote file:
- 5.2 kB
- SHA256:
- 18d27c18edf621c0bd1bb0395323e11bdf98894152b2e24f7875cd369f1cc80a
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