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README.md
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license: apache-2.0
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tags:
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- generated_from_trainer
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model-index:
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- name: flan-t5-small-distil-v2
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results: []
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language:
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- en
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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#
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This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on
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## Model description
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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- lr_scheduler_type: linear
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- num_epochs: 5
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## Use
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### CPU
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</details>
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### Framework versions
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license: apache-2.0
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tags:
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- generated_from_trainer
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- instruction fine-tuning
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model-index:
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- name: flan-t5-small-distil-v2
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results: []
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language:
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- en
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pipeline_tag: text2text-generation
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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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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## Model description
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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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## Training procedure
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- lr_scheduler_type: linear
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- num_epochs: 5
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## Training and evaluation data
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We conducted two sets of evaluations: automatic evaluation on downstream NLP tasks and human evaluation on user-oriented instructions. For more detail, please refer to our [paper]().
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## Use
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### CPU
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</details>
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## Intended uses & limitations
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More information needed
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### Framework versions
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