Token Classification
Transformers
ONNX
Safetensors
modernbert
ner
on-device
privacy
flowx
openner
cross
de-identification
Instructions to use flowxai/cvner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flowxai/cvner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="flowxai/cvner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("flowxai/cvner") model = AutoModelForTokenClassification.from_pretrained("flowxai/cvner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b0302e28ca89f46db733ad774afa0e8d95548af2d5f1e490a503263d9ff0c602
- Size of remote file:
- 5.2 kB
- SHA256:
- 8006bed26cc934dd4a46186b967a6ea26f9e48ec365b55bbbdb7ba7103868ea0
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