Text Classification
sentence-transformers
English
intent-classification
multi-label-classification
voice-notes
asr
routing
mcp
agents
Instructions to use danielrosehill/Voice-Note-Intent-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use danielrosehill/Voice-Note-Intent-Classifier with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("danielrosehill/Voice-Note-Intent-Classifier") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Card: real example scores
Browse files
README.md
CHANGED
|
@@ -50,7 +50,7 @@ python vnic/predict.py "um need to grab oat milk eggs and uh dish soap"
|
|
| 50 |
|
| 51 |
```json
|
| 52 |
{"model_version": "0.1.0", "taxonomy_version": "0.1.0",
|
| 53 |
-
"scores": {"shopping_list": 0.
|
| 54 |
"labels": ["shopping_list", "todo"], "abstain": false}
|
| 55 |
```
|
| 56 |
|
|
|
|
| 50 |
|
| 51 |
```json
|
| 52 |
{"model_version": "0.1.0", "taxonomy_version": "0.1.0",
|
| 53 |
+
"scores": {"shopping_list": 0.88, "todo": 0.54, "...": "..."},
|
| 54 |
"labels": ["shopping_list", "todo"], "abstain": false}
|
| 55 |
```
|
| 56 |
|