Token Classification
Transformers
Safetensors
layoutlmv3
ner
on-device
privacy
flowx
openner
cross
de-identification
Instructions to use flowxai/docformner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flowxai/docformner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="flowxai/docformner")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("flowxai/docformner") model = AutoModelForTokenClassification.from_pretrained("flowxai/docformner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2c91735162e71a39f9dbdd6c3d46fd4fc45459aa0210692001f5ea0b83de0cfc
- Size of remote file:
- 504 MB
- SHA256:
- 4e5c7d23ea9f7dff640f4dd922dd0ff2a803c31026524fbea4d0381cd139b36f
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