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:
- 972059e9c7d222c64c25bef6f2a69a4b91dd5950650975a2ee815dd2689b76d5
- Size of remote file:
- 5.2 kB
- SHA256:
- 63c3c6d8c1923baab542c42160f021e11d03059ac17436e1962317ae6ec79f41
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