Instructions to use petra345/CalibratedAwesomeModel-AuditRepo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use petra345/CalibratedAwesomeModel-AuditRepo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="petra345/CalibratedAwesomeModel-AuditRepo")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("petra345/CalibratedAwesomeModel-AuditRepo") model = AutoModel.from_pretrained("petra345/CalibratedAwesomeModel-AuditRepo") - Notebooks
- Google Colab
- Kaggle
| { | |
| "selected_checkpoint": "checkpoints/step_700", | |
| "panel_source": "README.md benchmark table", | |
| "panel_order": [ | |
| "Core Reasoning Tasks", | |
| "Language Understanding", | |
| "Generation Tasks", | |
| "Specialized Capabilities" | |
| ], | |
| "panels": [ | |
| { | |
| "panel": "Core Reasoning Tasks", | |
| "benchmarks": [ | |
| "Math Reasoning", | |
| "Logical Reasoning", | |
| "Common Sense" | |
| ], | |
| "selected_average": 0.716, | |
| "best_eligible_checkpoint": "checkpoints/step_900", | |
| "best_eligible_average": 0.723, | |
| "selected_rank_in_panel": 3, | |
| "selected_margin_vs_best": -0.007 | |
| }, | |
| { | |
| "panel": "Language Understanding", | |
| "benchmarks": [ | |
| "Reading Comprehension", | |
| "Question Answering", | |
| "Text Classification", | |
| "Sentiment Analysis" | |
| ], | |
| "selected_average": 0.752, | |
| "best_eligible_checkpoint": "checkpoints/step_900", | |
| "best_eligible_average": 0.759, | |
| "selected_rank_in_panel": 3, | |
| "selected_margin_vs_best": -0.007 | |
| }, | |
| { | |
| "panel": "Generation Tasks", | |
| "benchmarks": [ | |
| "Code Generation", | |
| "Creative Writing", | |
| "Dialogue Generation", | |
| "Summarization" | |
| ], | |
| "selected_average": 0.683, | |
| "best_eligible_checkpoint": "checkpoints/step_900", | |
| "best_eligible_average": 0.69, | |
| "selected_rank_in_panel": 3, | |
| "selected_margin_vs_best": -0.007 | |
| }, | |
| { | |
| "panel": "Specialized Capabilities", | |
| "benchmarks": [ | |
| "Translation", | |
| "Knowledge Retrieval", | |
| "Instruction Following", | |
| "Safety Evaluation" | |
| ], | |
| "selected_average": 0.773, | |
| "best_eligible_checkpoint": "checkpoints/step_900", | |
| "best_eligible_average": 0.78, | |
| "selected_rank_in_panel": 3, | |
| "selected_margin_vs_best": -0.007 | |
| } | |
| ], | |
| "overall_selected_average": 0.732, | |
| "panels_where_selected_is_not_best": 4 | |
| } | |