Token Classification
Transformers
ONNX
Safetensors
modernbert
ner
on-device
privacy
flowx
openner
logistics
de-identification
Instructions to use flowxai/bolparse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flowxai/bolparse with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="flowxai/bolparse")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("flowxai/bolparse") model = AutoModelForTokenClassification.from_pretrained("flowxai/bolparse", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 95ca2373de7f38022c88a7f6d768c09786385c10fc2c9c2342e16935e859b139
- Size of remote file:
- 598 MB
- SHA256:
- ebbd4ab00f0277493a2985b5fde2f8c69272af9b322bbabb369f93463a5c37d4
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