Token Classification
Transformers
ONNX
Safetensors
modernbert
ner
on-device
privacy
flowx
openner
banking
de-identification
Instructions to use flowxai/counterpartylink with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flowxai/counterpartylink with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="flowxai/counterpartylink")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("flowxai/counterpartylink") model = AutoModelForTokenClassification.from_pretrained("flowxai/counterpartylink", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eb36bb395e689aa36ec09cd120ce70dadd951faf4d1220763514dfbf82008d85
- Size of remote file:
- 5.2 kB
- SHA256:
- 14b078142790a2888acb53d6047ba021077da735230af8ff6902b4bb16953178
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