Text Generation
Transformers
Safetensors
English
Japanese
llama
conversational
text-generation-inference
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@@ -188,17 +188,17 @@ The following instruction datasets were used for the instruction tuning.
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  - Japanese
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  - `lmsys-chat-1m-synth-ja-wo-pii-and-template-instructions`
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  - Single-turn Japanese synthetic instruction dataset derived from [lmsys-chat-1m](https://huggingface.co/datasets/lmsys/lmsys-chat-1m) dataset [\[Zhang+, ICLR24\]](https://openreview.net/forum?id=BOfDKxfwt0)).
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- The first-turn user instructions were translated into Japanese via DeepL machine translation, and the assistant responses were generated using the Llama 3.1 405B Instruct model. Rejection sampling (n=6) was applied, with Llama 3.1 70B Instruct serving as a judge.
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  - As implied by the dataset name, conversations that contain personally identifiable information (PII) or template-based user instructions have been removed. Duplicate instuctions have also been removed.
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  - `filtered-magpie-ultra-ja`
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- - A Japanese variant of the `filtered-magpie-ultra-en` dataset, machine-translated into Japanese using the Gemma 2 27B IT.
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  - `gemma-magpie`
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- - Japanese Q&A dataset on diverse topics, generated using prompts with specific category words, with answers by Gemma 2 27B IT, heuristically filtered for quality and length.
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  - English
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  - `lmsys-chat-1m-synth-en-wo-pii-and-template-instructions`
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  - Similar to the `lmsys-chat-1m-synth-ja-wo-pii-and-template-instructions`, but this version uses the original English user instructions. The assistant responses were generated in English as well. Rejection sampling was not applied in this version.
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  - `filtered-magpie-ultra-en`
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- - A subset of the [magpie-ultra](https://huggingface.co/datasets/argilla/magpie-ultra-v0.1) dataset, developed following the MAGPIE recipe [\[Xu+, arXiv24\]](https://arxiv.org/abs/2406.08464) using Llama 3.1 405B Instruct. This subset includes only samples rated as 'average,' 'good,' or 'excellent.'
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  ## Risks and Limitations
 
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  - Japanese
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  - `lmsys-chat-1m-synth-ja-wo-pii-and-template-instructions`
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  - Single-turn Japanese synthetic instruction dataset derived from [lmsys-chat-1m](https://huggingface.co/datasets/lmsys/lmsys-chat-1m) dataset [\[Zhang+, ICLR24\]](https://openreview.net/forum?id=BOfDKxfwt0)).
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+ The first-turn user instructions were translated into Japanese via DeepL machine translation, and the assistant responses were generated using the [Llama-3.1-405B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-405B-Instruct) model. Rejection sampling (n=6) was applied, with [Llama-3.1-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-70B-Instruct) serving as a judge.
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  - As implied by the dataset name, conversations that contain personally identifiable information (PII) or template-based user instructions have been removed. Duplicate instuctions have also been removed.
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  - `filtered-magpie-ultra-ja`
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+ - A Japanese variant of the `filtered-magpie-ultra-en` dataset, machine-translated into Japanese using the [gemma-2-27b-it](https://huggingface.co/google/gemma-2-27b-it).
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  - `gemma-magpie`
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+ - A Japanese synthetic Q&A dataset from scratch, generated using [gemma-2-27b-it](https://huggingface.co/google/gemma-2-27b-it). User instructions were created with prompts specific to each topic, and the assistant responses were generated for these instructions. The conversations were then heuristically filtered for quality and length.
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  - English
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  - `lmsys-chat-1m-synth-en-wo-pii-and-template-instructions`
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  - Similar to the `lmsys-chat-1m-synth-ja-wo-pii-and-template-instructions`, but this version uses the original English user instructions. The assistant responses were generated in English as well. Rejection sampling was not applied in this version.
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  - `filtered-magpie-ultra-en`
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+ - A subset of the [magpie-ultra](https://huggingface.co/datasets/argilla/magpie-ultra-v0.1) dataset, developed following the MAGPIE recipe [\[Xu+, arXiv24\]](https://arxiv.org/abs/2406.08464) using [Llama-3.1-405B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-405B-Instruct). This subset includes only samples rated as 'average,' 'good,' or 'excellent.'
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  ## Risks and Limitations