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")# pip install -U transformers accelerate # 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
Download training_args.bin from flowxai/codemap: direct link, hf CLI and curl.
- Browser
- Download file 5.2 kB
-
https://huggingface.co/flowxai/codemap/resolve/main/training_args.bin
- Command line
-
hf download hf://flowxai/codemap/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/flowxai/codemap/resolve/main/training_args.bin
5.2 kB
- Xet hash:
- bc5352bc3d00835083d132aa013427a5109b23ff44ca9da7691791ae9220d7c5
- Size of remote file:
- 5.2 kB
- SHA256:
- b70da71902ad58cb7b1f843e9f1ce144bf6d4598df319c3ed85213299f6b38fb
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