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", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "accepted_accuracy": 0.8276, | |
| "accepted_coverage": 1.0, | |
| "accuracy": 0.8276, | |
| "confusion_matrix_path": "/content/agentic-intent-classifier/artifacts/evaluation/latest/decision_phase_val_confusion_matrix.csv", | |
| "count": 29, | |
| "dataset_path": "/content/agentic-intent-classifier/data/decision_phase/val.jsonl", | |
| "fallback_rate": 0.0, | |
| "head": "decision_phase", | |
| "macro_f1": 0.8254, | |
| "per_class_metrics": { | |
| "accuracy": 0.8275862068965517, | |
| "action": { | |
| "f1-score": 1.0, | |
| "precision": 1.0, | |
| "recall": 1.0, | |
| "support": 3.0 | |
| }, | |
| "awareness": { | |
| "f1-score": 0.8333333333333334, | |
| "precision": 0.7142857142857143, | |
| "recall": 1.0, | |
| "support": 5.0 | |
| }, | |
| "consideration": { | |
| "f1-score": 0.9090909090909091, | |
| "precision": 0.8333333333333334, | |
| "recall": 1.0, | |
| "support": 5.0 | |
| }, | |
| "decision": { | |
| "f1-score": 0.8571428571428571, | |
| "precision": 1.0, | |
| "recall": 0.75, | |
| "support": 4.0 | |
| }, | |
| "macro avg": { | |
| "f1-score": 0.8254483611626469, | |
| "precision": 0.8520408163265306, | |
| "recall": 0.8214285714285714, | |
| "support": 29.0 | |
| }, | |
| "post_purchase": { | |
| "f1-score": 0.75, | |
| "precision": 0.75, | |
| "recall": 0.75, | |
| "support": 4.0 | |
| }, | |
| "research": { | |
| "f1-score": 0.5714285714285714, | |
| "precision": 0.6666666666666666, | |
| "recall": 0.5, | |
| "support": 4.0 | |
| }, | |
| "support": { | |
| "f1-score": 0.8571428571428571, | |
| "precision": 1.0, | |
| "recall": 0.75, | |
| "support": 4.0 | |
| }, | |
| "weighted avg": { | |
| "f1-score": 0.822585460516495, | |
| "precision": 0.8415435139573071, | |
| "recall": 0.8275862068965517, | |
| "support": 29.0 | |
| } | |
| }, | |
| "suite": "val" | |
| } | |