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Use this text2text model to find out what LLM `instruction` (**and** `inputs` if relevant) might have generated `<arbitrary input text>`!
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the `pszemraj/fleece2instructions-inputs-alpaca-cleaned` dataset.
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It achieves the following results on the evaluation set:
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Use this text2text model to find out what LLM `instruction` (**and** `inputs` if relevant) might have generated `<arbitrary input text>`!
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- Check out a [basic demo on Spaces](https://huggingface.co/spaces/pszemraj/generate-instructions)
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- An example of how to use instructiongen models in a CLI script can be found [here](https://gist.github.com/pszemraj/8b0213e700763106074d3ac15d041c14)
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- You can find other models fine-tuned for instruction generation by [searching for the instructiongen tag](https://huggingface.co/models?other=instructiongen)
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## about
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the `pszemraj/fleece2instructions-inputs-alpaca-cleaned` dataset.
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It achieves the following results on the evaluation set:
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