Token Classification
Transformers
ONNX
Safetensors
modernbert
ner
on-device
privacy
flowx
openner
banking
de-identification
Instructions to use flowxai/mortgagedocner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flowxai/mortgagedocner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="flowxai/mortgagedocner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("flowxai/mortgagedocner") model = AutoModelForTokenClassification.from_pretrained("flowxai/mortgagedocner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 89bfb9829ec92496011aa4e2de8f7485bd1ed685559b01ce8e2d69fde8ddb18f
- Size of remote file:
- 599 MB
- SHA256:
- 2d02b9213e799e43e2d04917ebe30a88c0c3270d321bee917eadd55281652a0e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.