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:
- 8c218c779777f71fd3ae4aaaa5ebb80039b3330464e99438d563803c58102a30
- Size of remote file:
- 598 MB
- SHA256:
- 46fb509a83d8ee07b7222f1ff51062f1bb95af25a2ab0be80d0ca3266a252d21
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