Token Classification
Transformers
ONNX
Safetensors
modernbert
ner
on-device
privacy
flowx
openner
logistics
de-identification
Instructions to use flowxai/partylink with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flowxai/partylink with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="flowxai/partylink")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("flowxai/partylink") model = AutoModelForTokenClassification.from_pretrained("flowxai/partylink", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4135df171631e87211c47e2e9b3488a57ac4a8b8730b1e76625b631383a18f0a
- Size of remote file:
- 5.2 kB
- SHA256:
- cde5e74d69a754be35945c19ef1baccdc4ef6c6b39ce7793431a9b3216c7ff42
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