Text Classification
Transformers
ONNX
Safetensors
modernbert
ner
on-device
privacy
flowx
openner
healthcare
de-identification
text-embeddings-inference
Instructions to use flowxai/intentrouter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flowxai/intentrouter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="flowxai/intentrouter")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("flowxai/intentrouter") model = AutoModelForSequenceClassification.from_pretrained("flowxai/intentrouter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "test_loss": 4.885196744908171e-07, | |
| "test_accuracy": 1.0, | |
| "test_macro_f1": 1.0, | |
| "test_f1": 1.0, | |
| "test_runtime": 2.6669, | |
| "test_samples_per_second": 1124.91, | |
| "test_steps_per_second": 35.247, | |
| "epoch": 4.0 | |
| } |