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--- |
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library_name: transformers |
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tags: |
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- transformers |
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- peft |
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- arxiv:2406.08391 |
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license: llama2 |
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base_model: meta-llama/Llama-2-7b-hf |
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datasets: |
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- calibration-tuning/Llama-2-7b-hf-20k-oe |
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--- |
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# Model Card |
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**Llama 2 7B CT-OE** is a fine-tuned [Llama 2 7B](https://huggingface.co/meta-llama/Llama-2-7b-hf) model that provides well-calibrated confidence estimates for open-ended question answering. |
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The model is fine-tuned (calibration-tuned) using a [dataset](https://huggingface.co/datasets/calibration-tuning/Llama-2-7b-hf-20k-oe) of *open-ended* generations from `meta-llama/Llama-2-7b-hf`, labeled for correctness. |
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At test/inference time, the probability of correctness defines the confidence of the model in its answer. |
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For full details, please see our [paper](https://arxiv.org/abs/2406.08391) and supporting [code](https://github.com/activatedgeek/calibration-tuning). |
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**Other Models**: We also release a broader collection of [Open-Ended CT Models](https://huggingface.co/collections/calibration-tuning/open-ended-ct-models-66043b12c7902115c826a20e). |
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## Usage |
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This adapter model is meant to be used on top of `meta-llama/Llama-2-7b-hf` model generations. |
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The confidence estimation pipeline follows these steps, |
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1. Load base model and PEFT adapter. |
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2. Disable adapter and generate answer. |
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3. Enable adapter and generate confidence. |
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All standard guidelines for the base model's generation apply. |
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For a complete example, see [play.py](https://github.com/activatedgeek/calibration-tuning/blob/main/experiments/play.py) at the supporting code repository. |
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**NOTE**: Using the adapter for generations may hurt downstream task accuracy and confidence estimates. We recommend using the adapter to estimate *only* confidence. |
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## License |
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The model is released under the original model's Llama 2 Community License Agreement. |
