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@@ -6,7 +6,7 @@ This model judges if a given output is sufficient to recreate a given instructio
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  It's useful for filtering data to train a reverse instruct model. It could also have applications around determining if an output/instruction pair is linked, or around quality filtering data (data where the instruction can be recreated from the output might be higher quality).
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- The model is a binary classifier trained on top of Python 160m with 50k examples for 1 epoch. The final validation loss is .35. You can see an example of a dataset filtered with this model [here](https://huggingface.co/datasets/vikp/reverse_instruct).
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  To use it, pass in this prompt format:
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  It's useful for filtering data to train a reverse instruct model. It could also have applications around determining if an output/instruction pair is linked, or around quality filtering data (data where the instruction can be recreated from the output might be higher quality).
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+ The model is a binary classifier trained on top of Python 410m with 100k examples for 1 epoch. The final validation loss is .35. You can see an example of a dataset filtered with this model [here](https://huggingface.co/datasets/vikp/reverse_instruct).
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  To use it, pass in this prompt format:
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