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
File size: 423 Bytes
b751bb5 f0d902a b751bb5 1519226 b751bb5 f0d902a b751bb5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | {
"model_type": "distilbert",
"num_labels": 2,
"pipeline_tag": "text-classification",
"vocab_size": 30522,
"max_position_embeddings": 512,
"dim": 64,
"hidden_dim": 256,
"n_layers": 2,
"n_heads": 2,
"dropout": 0.1,
"custom_pipelines": {
"admesh-intent": {
"impl": "pipeline.AdmeshIntentPipeline",
"pt": [
"AutoModelForSequenceClassification"
],
"tf": []
}
}
}
|