Token Classification
Transformers
ONNX
Safetensors
modernbert
ner
on-device
privacy
flowx
openner
insurance
de-identification
Instructions to use flowxai/partyresolve with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flowxai/partyresolve with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="flowxai/partyresolve")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("flowxai/partyresolve") model = AutoModelForTokenClassification.from_pretrained("flowxai/partyresolve", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8aee99ab444b48ee771d182e4d5984a87af9492085e73d0f91c56bd79ac110e5
- Size of remote file:
- 598 MB
- SHA256:
- 13f9fde7182a3571a6a09e231d9ca626ecaade83ac1ac6f565888297eafac5ac
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