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:
- dda3116ce7ad725768f0ebc56726f56c9d8ca89f7c8ea0b1ca95ab0e62b423a8
- Size of remote file:
- 2.62 MB
- SHA256:
- de58e8a58ea7e02d4ba86e1974c9ee7aab3ad3956518572e3b64963abc0cf5c6
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