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:
- 2aeb0a27ab63aef9a650e6b2f04c354469084149be2041f63ed72a620e34478d
- Size of remote file:
- 598 MB
- SHA256:
- 73738fdaa25cefe7442b19a554c175f47fa427a89d9e161f4812a893490208d0
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