calibration-tuning
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Llama-2-7b-chat-hf-ct-choice

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 - calibration-tuning/Llama-2-7b-chat-hf-20k-choice
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-# Model Card for Model ID
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 - calibration-tuning/Llama-2-7b-chat-hf-20k-choice
 ---
+# Model Card
+**Llama 7B Chat CT-Choice** is a fine-tuned [Llama 7B Chat](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf) model that provides well-calibrated confidence estimates for multiple-choice question answering.
+The model is fine-tuned (calibration-tuned) using a [dataset](https://huggingface.co/datasets/calibration-tuning/Llama-2-7b-chat-hf-20k-choice) of *multiple-choice* generations from `meta-llama/Llama-2-7b-chat-hf`, labeled for correctness.
+At test/inference time, the probability of correctness defines the confidence of the model in its answer.
+For full details, please see our [paper](https://arxiv.org/) and supporting [code](https://github.com/activatedgeek/calibration-tuning).
+**Other Models**: We also release a broader collection of [Multiple-Choice CT Models](https://huggingface.co/collections/calibration-tuning/multiple-choice-ct-models-66043dedebf973d639090821).
+## Usage
+This adapter model is meant to be used on top of `meta-llama/Llama-2-7b-chat-hf` model generations.
+The confidence estimation pipeline follows these steps,
+1. Load base model and PEFT adapter.
+2. Disable adapter and generate answer.
+3. Enable adapter and generate confidence.
+All standard guidelines for the base model's generation apply.
+For a complete example, see [play.py](https://github.com/activatedgeek/calibration-tuning/blob/main/experiments/play.py) at the supporting code repository.
+**NOTE**: Using the adapter for generations may hurt downstream task accuracy and confidence estimates. We recommend using the adapter to estimate *only* confidence.
+## License
+The model is released under the original model's Apache 2.0 license.