Token Classification
Transformers
ONNX
Safetensors
modernbert
ner
on-device
privacy
flowx
openner
logistics
de-identification
Instructions to use flowxai/portroute with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flowxai/portroute with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="flowxai/portroute")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("flowxai/portroute") model = AutoModelForTokenClassification.from_pretrained("flowxai/portroute", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 34dda4ed661ecdcec4551fae3424d95c73ad9ed5d07217af3dc1e7676a754568
- Size of remote file:
- 5.2 kB
- SHA256:
- 3a5cece3b76bd78a69319c70898dee7a9bfaa1555f019cd16b531952b1f81d12
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