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")# pip install -U transformers accelerate # 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
Download metrics.json from flowxai/containerdetect: direct link, hf CLI and curl.
- Browser
- Download file 244 Bytes
-
https://huggingface.co/flowxai/containerdetect/resolve/main/metrics.json
- Command line
-
hf download hf://flowxai/containerdetect/metrics.json
-
curl -L -o metrics.json https://huggingface.co/flowxai/containerdetect/resolve/main/metrics.json
244 Bytes
| { | |
| "test_loss": 2.3796054904323682e-07, | |
| "test_precision": 1.0, | |
| "test_recall": 1.0, | |
| "test_f1": 1.0, | |
| "test_accuracy": 1.0, | |
| "test_runtime": 4.319, | |
| "test_samples_per_second": 926.134, | |
| "test_steps_per_second": 28.942, | |
| "epoch": 3.0 | |
| } |