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  ## Model Description
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- OPT-IML models are instruction-tuned versions of OPT. They are fine-tuned on 2000 NLP tasks from 8 existing public benchmarks.
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- OPT-IML models are significantly better than OPT model and demonstrate different generalization abilities on four different
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- evaluation benchmarks with diverse tasks and input formats – PromptSource, FLAN, Super-NaturalInstructions, and UnifiedSKG.
 
 
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  ### How to use
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  For large OPT models, such as this one, it is not recommend to make use of the `text-generation` pipeline because
 
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  ## Model Description
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+ [OPT-IML (OPT + Instruction Meta-Learning)](https://arxiv.org/abs/2212.12017) is a set of instruction-tuned versions of OPT, on a collection of ~2000 NLP tasks gathered from 8 NLP benchmarks, called OPT-IML Bench.
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+ We provide two model versions:
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+ * OPT-IML trained on 1500 tasks with several tasks held-out for purposes of downstream evaluation, and
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+ * OPT-IML-Max trained on all ~2000 tasks
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  ### How to use
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  For large OPT models, such as this one, it is not recommend to make use of the `text-generation` pipeline because