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:
- ba255a5c4e49a20d1263918d2721dce3e647a6c4a6d1d31c2056405a669f467f
- Size of remote file:
- 2.62 MB
- SHA256:
- 104f808057c94cbf84c15e91fee0d88117630321beb09bcd3ed24e5070b29ff1
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