Token Classification
Transformers
ONNX
Safetensors
modernbert
ner
on-device
privacy
flowx
openner
logistics
de-identification
Instructions to use flowxai/containerdetect with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flowxai/containerdetect with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="flowxai/containerdetect")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("flowxai/containerdetect") model = AutoModelForTokenClassification.from_pretrained("flowxai/containerdetect", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c1c43db716477139052f3fdef12c12ec0b152fe3a9c9d1417d51785a537838fc
- Size of remote file:
- 598 MB
- SHA256:
- 77a675fb3a2167bf71592eeb7086247262bb0c393b5836d08495264904d787ce
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