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:
- 8d8143934afcf15d008d624b3a6563ec5876c60d6b6bd60e13d123cd4b11afdb
- Size of remote file:
- 5.2 kB
- SHA256:
- 685a2e13c6931c2aedae2161a5c5d6eb1963d313e52ffaf80df3b71a5ebfad99
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