Text Classification
Transformers
ONNX
Safetensors
English
distilbert
intent-classification
multitask
iab
conversational-ai
adtech
calibrated-confidence
text-embeddings-inference
Instructions to use admesh/agentic-intent-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use admesh/agentic-intent-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="admesh/agentic-intent-classifier")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("admesh/agentic-intent-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "calibrated": true, | |
| "confidence_threshold": 0.4, | |
| "generated_at": "2026-03-25T21:19:41.302013+00:00", | |
| "head": "intent_type", | |
| "metrics": { | |
| "calibrated_accuracy": 0.8723, | |
| "calibrated_expected_calibration_error": 0.0798, | |
| "calibrated_negative_log_likelihood": 0.2692, | |
| "mean_calibrated_confidence": 0.8962, | |
| "mean_raw_confidence": 0.8671, | |
| "raw_accuracy": 0.8723, | |
| "raw_expected_calibration_error": 0.1073, | |
| "raw_negative_log_likelihood": 0.2907 | |
| }, | |
| "minimum_threshold_floor": 0.4, | |
| "optimized_temperature_candidate": 0.889496, | |
| "selected_threshold_before_floor": { | |
| "accepted_accuracy": 0.8723, | |
| "coverage": 1.0, | |
| "threshold": 0.0 | |
| }, | |
| "selection_split": "val", | |
| "selection_target_precision": 0.8, | |
| "temperature": 0.889496, | |
| "temperature_scaling_applied": true, | |
| "threshold_summary": { | |
| "accepted_accuracy": 0.8913, | |
| "coverage": 0.9787, | |
| "threshold": 0.4 | |
| } | |
| } | |