Text Generation
PEFT
Safetensors
English
lora
control-theory
regularization
information-theory
llama
adapter
Instructions to use hunterbown/shannon-control-unit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use hunterbown/shannon-control-unit with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-1B") model = PeftModel.from_pretrained(base_model, "hunterbown/shannon-control-unit") - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
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## Data Files
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- Ablations (CSV):
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- [PI Control](./ablations/pi_control.csv)
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- [Fixed 位=1.0](./ablations/fixed_1.0.csv)
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- [Fixed 位=5.0](./ablations/fixed_5.0.csv)
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- Validation summary (JSON): [results/3b_validation_results.json](./results/3b_validation_results.json)
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## Control Telemetry
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## Data Files
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- Ablations (CSV):
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- [PI Control](https://huggingface.co/hunterbown/shannon-control-unit/blob/main/ablations/pi_control.csv)
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- [Fixed 位=1.0](https://huggingface.co/hunterbown/shannon-control-unit/blob/main/ablations/fixed_1.0.csv)
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- [Fixed 位=5.0](https://huggingface.co/hunterbown/shannon-control-unit/blob/main/ablations/fixed_5.0.csv)
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- Validation summary (JSON): [results/3b_validation_results.json](https://huggingface.co/hunterbown/shannon-control-unit/blob/main/results/3b_validation_results.json)
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## Control Telemetry
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