Pankaj Mathur
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README.md
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library_name: transformers
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---
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#
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# Dataset
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We
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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 [
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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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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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- psmathur/dolly-v2_orca
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- psmathur/WizardLM_Orca
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---
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# orca_mini_3b
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An [OpenLLaMa-3B model](https://github.com/openlm-research/open_llama) model trained on explain tuned datasets, created using Instructions and Input from WizardLM, Alpaca & Dolly-V2 datasets and applying Orca Research Paper dataset construction approaches.
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# Dataset
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We build explain tuned [WizardLM dataset ~70K](https://github.com/nlpxucan/WizardLM), [Alpaca dataset ~52K](https://crfm.stanford.edu/2023/03/13/alpaca.html) & [Dolly-V2 dataset ~15K](https://github.com/databrickslabs/dolly) 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 [wizardlm_alpaca_dolly_orca_open_llama_13b](https://huggingface.co/psmathur/wizardlm_alpaca_dolly_orca_open_llama_13b) 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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