Token Classification
Transformers
ONNX
Safetensors
modernbert
ner
on-device
privacy
flowx
openner
insurance
de-identification
Instructions to use flowxai/codemap with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flowxai/codemap with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="flowxai/codemap")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("flowxai/codemap") model = AutoModelForTokenClassification.from_pretrained("flowxai/codemap", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 874fbb0afe8efe1738feec7a1359d120e6b0f18668bfb24829ef8c49d5789dd9
- Size of remote file:
- 152 MB
- SHA256:
- 792386b0beb8a2f10f222041c6ed9342140c3e365efb460672076785c279aea3
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