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  This repo contains a low-rank adapter for **LLaMA-7b** fit on datasets part of the OpenAssistant project.
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- You can see sampling results [here](https://open-assistant.github.io/oasst-model-eval/?f=https%3A%2F%2Fraw.githubusercontent.com%2FOpen-Assistant%2Foasst-model-eval%2Fmain%2Fsampling_reports%2Foasst-sft%2F2023-03-18_llama_30b_oasst_latcyr_400_sampling_noprefix_lottery.json%0Ahttps%3A%2F%2Fraw.githubusercontent.com%2FOpen-Assistant%2Foasst-model-eval%2F8e90ce6504c159d4046991bf37757c108aed913f%2Fsampling_reports%2Foasst-sft%2Freport_file_jordiclive_alpaca_gpt4-dolly_15k-vicuna-lora-7b_full_lottery_no_prefix.json)
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- Note the sampling params are not necessarily the optimum—they are OpenAssistant defaults for comparing models.
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  This version of the weights was trained with the following hyperparameters:
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  This repo contains a low-rank adapter for **LLaMA-7b** fit on datasets part of the OpenAssistant project.
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+ You can see sampling results [here](https://open-assistant.github.io/oasst-model-eval/?f=https%3A%2F%2Fraw.githubusercontent.com%2FOpen-Assistant%2Foasst-model-eval%2Fmain%2Fsampling_reports%2Foasst-sft%2F2023-03-18_llama_30b_oasst_latcyr_400_sampling_noprefix_lottery.json%0Ahttps%3A%2F%2Fraw.githubusercontent.com%2FOpen-Assistant%2Foasst-model-eval%2F8e90ce6504c159d4046991bf37757c108aed913f%2Fsampling_reports%2Foasst-sft%2Freport_file_jordiclive_alpaca_gpt4-dolly_15k-vicuna-lora-7b_full_lottery_no_prefix.json). Note the sampling params are not necessarily the optimum—they are OpenAssistant defaults for comparing models.
 
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  This version of the weights was trained with the following hyperparameters:
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