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 from flowxai/kybextract: direct link, hf CLI and curl.
- Browser
- Download file 2.62 MB
-
https://huggingface.co/flowxai/kybextract/resolve/main/onnx/model.onnx
- Command line
-
hf download hf://flowxai/kybextract/onnx/model.onnx
-
curl -L -o model.onnx https://huggingface.co/flowxai/kybextract/resolve/main/onnx/model.onnx
2.62 MB
- Xet hash:
- 716cccce08591067c3320ad863d52a547049a806f00a99302aad896dd382024e
- Size of remote file:
- 2.62 MB
- SHA256:
- 505fbe4c170915ebbc973d33c71ff4b5df5798602bcc6109d241c899277f4de3
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