Instructions to use danielfein/raid-ce-gemma4-e4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danielfein/raid-ce-gemma4-e4b with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("danielfein/raid-ce-gemma4-e4b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "beemo": { | |
| "accuracy_at_zero": 0.7172907998150717, | |
| "auroc": 0.7688818952974723, | |
| "auroc_ci95": [ | |
| 0.7555810120573192, | |
| 0.7820446754125032 | |
| ], | |
| "mean_ai_score": 8.300825430565116, | |
| "mean_human_score": -1.0891033262221061, | |
| "pairs": 2163, | |
| "texts": 4326 | |
| }, | |
| "full_steps": 75, | |
| "full_train_pairs": 5000, | |
| "full_train_sources": 4071, | |
| "raid_standard_test": { | |
| "accuracy_at_zero": 0.834, | |
| "auroc": 0.9599298888888887, | |
| "auroc_ci95": [ | |
| 0.9549222138888889, | |
| 0.9647777 | |
| ], | |
| "mean_ai_score": 6.002089725395043, | |
| "mean_human_score": -13.72776710220178, | |
| "pairs": 3000, | |
| "texts": 6000 | |
| }, | |
| "selected_pilot": { | |
| "accuracy_at_zero": 0.702, | |
| "auroc": 0.790656, | |
| "checkpoint": "/workspace/expanded_raid_ai_20260726/outputs/gemma_locked_pairwise_ce_seed707/pilot/lr_0.001/final", | |
| "final_rolling_loss": 0.10128707309773745, | |
| "lr": 0.001, | |
| "mean_ai_score": 6.3129822878837585, | |
| "mean_human_score": -0.7812474756240845, | |
| "pairs": 250, | |
| "steps": 125, | |
| "texts": 500 | |
| }, | |
| "tokens": "/workspace/expanded_raid_ai_20260726/outputs/gemma_locked_pairwise_ce_seed707/full/final/tokens" | |
| } | |