Instructions to use petra345/MyAwesomeModel-BalancedGate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use petra345/MyAwesomeModel-BalancedGate with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="petra345/MyAwesomeModel-BalancedGate")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("petra345/MyAwesomeModel-BalancedGate") model = AutoModelForSequenceClassification.from_pretrained("petra345/MyAwesomeModel-BalancedGate") - Notebooks
- Google Colab
- Kaggle
| { | |
| "repo_name": "MyAwesomeModel-BalancedGate", | |
| "selected_checkpoint": "cobalt_0510", | |
| "checkpoint_dir": "checkpoints/cobalt_0510", | |
| "deployment_score": "0.827", | |
| "eval_accuracy": "0.858", | |
| "safety_score": "0.846", | |
| "latency_ms": 98, | |
| "stability_score": "0.906", | |
| "min_benchmark": "0.702", | |
| "selection_rule": "eligible_min_benchmark_ge_0.600_then_max_weighted_deployment_score" | |
| } | |