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  license: mit
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  language:
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  - en
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- library_name: adapter-transformers
 
 
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  ---
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- # Wizardlm Alpaca Dolly Orca Open_LLaMa_3b
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- An Open_LLaMA-3B model trained on custom explain tuned datasets, created using Instructions and Input from Alpaca datasets and applying Orca Research Paper dataset construction approaches.
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  # Dataset
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- We trained [OpenLLaMa-3B model](https://github.com/openlm-research/open_llama) on custom explain tuned [Alpaca dataset](https://crfm.stanford.edu/2023/03/13/alpaca.html) (~52K) created using approaches from [Orca Research Paper](https://arxiv.org/abs/2306.02707).
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- We leverage all of the 15 system instructions provided in Orca Research Paper. to generate custom Alpaca dataset, in contrast to vanilla instruction tuning approaches used by original [Alpaca research paper](https://crfm.stanford.edu/2023/03/13/alpaca.html).
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- This helps student model aka [alpaca_orca_open_llama_3b](psmathur/alpaca_orca_open_llama_3b) to learn ***thought*** process from teacher model, which is ChatGPT (gpt-3.5-turbo-0301 version).
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- Please see below example usage how the **System** prompt is added before each *instruction*.
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  # Training
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  license: mit
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  language:
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  - en
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+ library_name: transformers
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+ datasets:
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+ - psmathur/alpaca_orca
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  ---
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+ # Orca_alpaca_3b
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+ An Open_LLaMA-3B model trained on explain tuned datasets, created using Instructions and Input from Alpaca datasets and applying Orca Research Paper dataset construction approaches.
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  # Dataset
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+ We build explain tuned [Alpaca dataset ~52K](https://crfm.stanford.edu/2023/03/13/alpaca.html) created using approaches from [Orca Research Paper](https://arxiv.org/abs/2306.02707).
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+ We leverage all of the 15 system instructions provided in Orca Research Paper. to generate custom datasets, in contrast to vanilla instruction tuning approaches used by original datasets.
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+ This helps student model aka this model to learn ***thought*** process from teacher model, which is ChatGPT (gpt-3.5-turbo-0301 version).
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+ Please see below example usage how the **System** prompt is added before each **instruction**.
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  # Training
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