Token Classification
Transformers
ONNX
Safetensors
modernbert
ner
on-device
privacy
flowx
openner
banking
de-identification
Instructions to use flowxai/kycextract with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flowxai/kycextract with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="flowxai/kycextract")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("flowxai/kycextract") model = AutoModelForTokenClassification.from_pretrained("flowxai/kycextract", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c91d2de30ea76152241fed557d18cc835bc9e7a631807802425552a0a9c86682
- Size of remote file:
- 598 MB
- SHA256:
- df57f8ef5ce15a52d6d3a985231c261e68b6e0de6a9119a9732b216b60db5417
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