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:
- 50fb2d358a68caa8f21fe84d6d9622dc46300da04fc87c3b226f2a161bde834a
- Size of remote file:
- 2.62 MB
- SHA256:
- 826d96217b174348fdd5ec4489f84d8b99444367ebaee4a48909c28b52d17f40
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