Text Classification
Transformers
Safetensors
truetype_system_one
feature-extraction
custom_code
gemma4
typed-decisions
Instructions to use stephenlb/system-one-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stephenlb/system-one-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="stephenlb/system-one-model", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("stephenlb/system-one-model", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Browse files
README.md
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| `noul` accuracy | 15/15 | 15/15 | 15/15 |
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| `noul` Brier (lower is better) | 0.000003 | 0.0338 | 0.00035 |
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| `choice` accuracy | 11/12 | 12/12 | 12/12 |
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| `score` accuracy
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| `score` mean error (levels) | 0.09 | 0.48 | 0.004 |
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| 1-question p50 latency | 117 ms | 96 ms | 144 ms |
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| 3-question p50 latency | 332 ms | 121 ms | 164 ms |
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| 47 |
| `noul` accuracy | 15/15 | 15/15 | 15/15 |
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| 48 |
| `noul` Brier (lower is better) | 0.000003 | 0.0338 | 0.00035 |
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| `choice` accuracy | 11/12 | 12/12 | 12/12 |
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| `score` accuracy | 11/12 | 5/12 | 12/12 |
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| 51 |
| `score` mean error (levels) | 0.09 | 0.48 | 0.004 |
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| 52 |
| 1-question p50 latency | 117 ms | 96 ms | 144 ms |
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| 53 |
| 3-question p50 latency | 332 ms | 121 ms | 164 ms |
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