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
Upload README.md with huggingface_hub
Browse files
README.md
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Questions (`noul`, `choice`, `score`) are answered by softmax
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over the logits for each question.
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Requires `transformers>=5.17`. The repo ships custom code, so pass
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`trust_remote_code=True`.
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Questions (`noul`, `choice`, `score`) are answered by softmax
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over the logits for each question.
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## Super Mario Bros. World 1-1 played by the model.
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<video controls width="640" src="https://huggingface.co/stephenlb/system-one-model/resolve/main/mario-world-1.mp4"></video>
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Requires `transformers>=5.17`. The repo ships custom code, so pass
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`trust_remote_code=True`.
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