Text Classification
Transformers
Safetensors
smollm3
agent-safety
tool-calling
long-context
Eval Results (legacy)
Instructions to use ProCreations/auto-3b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProCreations/auto-3b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ProCreations/auto-3b")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ProCreations/auto-3b") model = AutoModelForSequenceClassification.from_pretrained("ProCreations/auto-3b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 711 Bytes
58323da | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | {
"threshold": 0.295,
"validation_metrics": {
"n": 2581,
"accuracy": 0.9833397907787679,
"balanced_accuracy": 0.9833393179247119,
"f1_deny": 0.9833655705996132,
"auroc": 0.9978311360475756,
"nll": 0.06344092496728404,
"false_approve_rate": 0.016253869969040248,
"false_deny_rate": 0.017067494181536073,
"false_approve_count": 21,
"false_deny_count": 22,
"deny_count": 1292,
"approve_count": 1289,
"threshold": 0.295,
"brier": 0.015282586776204823,
"accuracy_ci95": [
0.9776351922332552,
0.9876077597032694
]
},
"criterion": "balanced accuracy; ties prefer fewer false approvals then 0.5 proximity",
"benchmark_used": false
}
|