Instructions to use ethnmcl/ontask-participation-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ethnmcl/ontask-participation-classifier with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ethnmcl/ontask-participation-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
| { | |
| "model_type": "sentence-transformers + xgboost", | |
| "embedder": "all-MiniLM-L6-v2", | |
| "threshold": 0.4, | |
| "auc_roc": 0.8483, | |
| "cv_mean_auc": 0.803, | |
| "training_rows": 2296, | |
| "task": "on-task participation detection", | |
| "input_format": "Yesterday: <yesterday_checkin> Today: <today_checkin>", | |
| "output": { | |
| "on_task": "bool", | |
| "confidence": "float 0-1" | |
| } | |
| } |