Instructions to use petra345/MyAwesomeModel-RegressionGuard with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use petra345/MyAwesomeModel-RegressionGuard with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="petra345/MyAwesomeModel-RegressionGuard")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("petra345/MyAwesomeModel-RegressionGuard") model = AutoModel.from_pretrained("petra345/MyAwesomeModel-RegressionGuard") - Notebooks
- Google Colab
- Kaggle
| { | |
| "repo_name": "MyAwesomeModel-RegressionGuard", | |
| "selection_policy": "highest_safety_with_overall_and_instruction_floor", | |
| "selected_checkpoint": "step_1000", | |
| "reference_checkpoint": "step_900", | |
| "minimum_overall_score": "0.705", | |
| "minimum_instruction_following": "0.754", | |
| "selected_overall_score": "0.710", | |
| "reference_overall_score": "0.709", | |
| "focused_scores": { | |
| "safety_evaluation": "0.739", | |
| "instruction_following": "0.758", | |
| "logical_reasoning": "0.819" | |
| }, | |
| "benchmark_count": 15, | |
| "score_precision": "three_decimals" | |
| } | |