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
File size: 221 Bytes
543f923 | 1 2 3 4 5 6 7 8 9 10 | {
"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
} |