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
| import json | |
| try: | |
| from .model_runtime import get_head # type: ignore | |
| except ImportError: | |
| from model_runtime import get_head | |
| def predict(text: str, confidence_threshold: float | None = None): | |
| return get_head("intent_subtype").predict(text, confidence_threshold=confidence_threshold) | |
| examples = [ | |
| "What is CRM software?", | |
| "HubSpot vs Zoho for a small team", | |
| "Which CRM should I buy for a 3-person startup?", | |
| "How do I reset my password?", | |
| ] | |
| if __name__ == "__main__": | |
| for text in examples: | |
| print(f"\nInput: {text}") | |
| print("Prediction:", json.dumps(predict(text), indent=2)) | |