Feature Extraction
Transformers
Safetensors
English
modernbert
autonomous-driving
structured-output
compositional-semantics
research-only
text-embeddings-inference
Instructions to use UNIC0RN-Zhu/modernbert-drive-command-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UNIC0RN-Zhu/modernbert-drive-command-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="UNIC0RN-Zhu/modernbert-drive-command-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("UNIC0RN-Zhu/modernbert-drive-command-base") model = AutoModel.from_pretrained("UNIC0RN-Zhu/modernbert-drive-command-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "schema": "modernbert-driving-command-training-v1", | |
| "base_model": "/root/autodl-tmp/models/modernbert-drive-command-base", | |
| "output": "/root/autodl-tmp/models/modernbert-drive-command-epoch2", | |
| "train_rows": 463998, | |
| "validation_rows": 132540, | |
| "epochs": 1, | |
| "batch_size": 128, | |
| "max_length": 96, | |
| "learning_rate": 1e-05, | |
| "seed": 20260721, | |
| "elapsed_seconds": 385.475597538054, | |
| "label_schema": { | |
| "actions": [ | |
| "KEEP_LANE", | |
| "SET_SPEED", | |
| "ADJUST_SPEED", | |
| "STOP", | |
| "WAIT", | |
| "FOLLOW", | |
| "APPROACH", | |
| "NAVIGATE_TO", | |
| "CHANGE_LANE", | |
| "MERGE", | |
| "TURN", | |
| "U_TURN", | |
| "PROCEED", | |
| "YIELD", | |
| "PULL_OVER", | |
| "PARK", | |
| "OVERTAKE", | |
| "PASS_BY", | |
| "AVOID", | |
| "REVERSE", | |
| "ENTER_AREA", | |
| "EXIT_AREA", | |
| "EMERGENCY_BRAKE", | |
| "RESUME", | |
| "CANCEL" | |
| ], | |
| "statuses": [ | |
| "VALID", | |
| "NEEDS_CLARIFICATION", | |
| "UNSUPPORTED" | |
| ], | |
| "categories": [ | |
| "BASIC_CONTROL", | |
| "NAVIGATION", | |
| "COMPLEX_OBSTACLE_AVOIDANCE", | |
| "EMERGENCY_RESPONSE", | |
| "META_CONTROL" | |
| ], | |
| "urgencies": [ | |
| "NORMAL", | |
| "URGENT", | |
| "EMERGENCY" | |
| ], | |
| "directions": [ | |
| "LEFT", | |
| "RIGHT", | |
| "STRAIGHT", | |
| "BACKWARD" | |
| ], | |
| "changes": [ | |
| "NONE", | |
| "INCREASE", | |
| "DECREASE" | |
| ] | |
| }, | |
| "history": [ | |
| { | |
| "samples": 132540, | |
| "action_exact_match": 0.9829636336200392, | |
| "action_micro_precision": 0.9356169331077613, | |
| "action_micro_recall": 0.9870056950348921, | |
| "action_micro_f1": 0.9606245425713588, | |
| "status_accuracy": 0.994009355666214, | |
| "category_accuracy": 0.9919797796891504, | |
| "urgency_accuracy": 0.999109702731251, | |
| "direction_exact_match": 0.9966274332277049, | |
| "change_accuracy": 0.9985061113626075, | |
| "epoch": 1, | |
| "train_loss": 0.03627125481040827, | |
| "epoch_seconds": 385.1342375576496 | |
| } | |
| ], | |
| "metric_scope": "PSEUDO_LABEL_TEACHER_AGREEMENT_NOT_HUMAN_GOLD_ACCURACY" | |
| } | |