Token Classification
Transformers
ONNX
Safetensors
modernbert
ner
on-device
privacy
flowx
openner
cross
de-identification
Instructions to use flowxai/kybextract with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flowxai/kybextract with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="flowxai/kybextract")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("flowxai/kybextract") model = AutoModelForTokenClassification.from_pretrained("flowxai/kybextract", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download onnx/model.onnx.data from flowxai/kybextract: direct link, hf CLI and curl.
- Browser
- Download file 598 MB
-
https://huggingface.co/flowxai/kybextract/resolve/main/onnx/model.onnx.data
- Command line
-
hf download hf://flowxai/kybextract/onnx/model.onnx.data
-
curl -L -o model.onnx.data https://huggingface.co/flowxai/kybextract/resolve/main/onnx/model.onnx.data
598 MB
- Xet hash:
- d4d03299565c35acbedf05ead53a095c5baf6bd95470d786f540d7e884f1debd
- Size of remote file:
- 598 MB
- SHA256:
- c8194b8fba5a3da24b6e5ce2b1c9fdf50840d012d2770682bca5298cba47739c
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