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
Download training_args.bin from flowxai/kycextract: direct link, hf CLI and curl.
- Browser
- Download file 5.2 kB
-
https://huggingface.co/flowxai/kycextract/resolve/0bee9ca49d898c183a8465f1ee0f47084a6d2f9e/training_args.bin
- Command line
-
hf download hf://flowxai/kycextract@0bee9ca49d898c183a8465f1ee0f47084a6d2f9e/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/flowxai/kycextract/resolve/0bee9ca49d898c183a8465f1ee0f47084a6d2f9e/training_args.bin
5.2 kB
- Xet hash:
- 40b3410d0c0053307c9d7396eec276c87e4ebafeba2ef37d5c58edac509ed9c9
- Size of remote file:
- 5.2 kB
- SHA256:
- 9670bbd9f01b6ab5a5076928202df2d6679eeb5a898a12eb59bd60b41a6a309b
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