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  # LaMini-FLAN-T5-Small
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- This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on [LaMini dataset]() that contains 2.58M samples for instruction fine-tuning. For more information about our dataset, please refer to our [project repository]().
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  ## Training Procedure
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  We initialize with [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) and fine-tune it on our [LaMini dataset](). Its total number of parameters is 61M.
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  ## Use
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  ### Intended use
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  We now show you how to load and use our model using HuggingFace `pipline()`.
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  ### CPU
 
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  # LaMini-FLAN-T5-Small
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+ This model is one of our LaMini model series in paper "[LaMini: Distilling Knowledge from Large Language Models]()". This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on [LaMini dataset]() that contains 2.58M samples for instruction fine-tuning. For more information about our dataset, please refer to our [project repository]().
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  ## Training Procedure
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  We initialize with [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) and fine-tune it on our [LaMini dataset](). Its total number of parameters is 61M.
 
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  ## Use
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  ### Intended use
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+ We recommend to use model to reponse to humen instructions wrote in natural language.
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  We now show you how to load and use our model using HuggingFace `pipline()`.
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  ### CPU