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  > [Announcement tweet](https://twitter.com/dvilasuero/status/1643234487386374148?s=20)
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  A cross-lingual SetFit model to **detect bad instructions from Alpaca Datasets** and other instruction-following datasets.
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- `GarbageCollector` can greatly speed up the validation of these Datasets across many languages, flagging examples that need to be fixed or simply discarded.
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  Data quality is key for LLMs, but open-source LLMs are being built with data of "unknown" quality. This model can help practitioners to find and fix frequent issues (e.g., the model hallucinating stock prices, describing non-existing images, etc.)
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  > [Announcement tweet](https://twitter.com/dvilasuero/status/1643234487386374148?s=20)
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  A cross-lingual SetFit model to **detect bad instructions from Alpaca Datasets** and other instruction-following datasets.
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+ `GarbageCollector` can greatly speed up the validation of instruction-datasets across many languages, flagging examples that need to be fixed or simply discarded.
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  Data quality is key for LLMs, but open-source LLMs are being built with data of "unknown" quality. This model can help practitioners to find and fix frequent issues (e.g., the model hallucinating stock prices, describing non-existing images, etc.)
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