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  Poro 34b chat is a chat-tuned version of [Poro
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  34B](https://huggingface.co/LumiOpen/Poro-34B) trained to follow instructions
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- in both Finnish and English. A quantized version will be made available soon.
 
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  Because of the limited amount of instruction tuning available for Finnish, documents from the English datasets were machine-translated by the Poro 34B base model into Finnish, then used to train this chat version. We selected only datasets that are available for commercial use and only contain synthetic data if it was gathered in ToS-compliant fashion.
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  English, 40% Finnish, and 20% cross-lingual entries.
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  We finetuned the base model for 3 epochs with a learning rate of 2e-05, warmup
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- ratio of 0.1, and a global batch size of 48. We used the [Alignment Handbook](https://github.com/huggingface/alignment-handbook/)
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- code for finetuning. For full-parameter finetuning, we used 3 nodes (8 GPUs per
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- node).
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  ## Datasets
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  Poro 34b chat is a chat-tuned version of [Poro
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  34B](https://huggingface.co/LumiOpen/Poro-34B) trained to follow instructions
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+ in both Finnish and English. Quantized versions are available on [Poro
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+ 34B-chat-GGUF](https://huggingface.co/LumiOpen/Poro-34B-chat-GGUF)
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  Because of the limited amount of instruction tuning available for Finnish, documents from the English datasets were machine-translated by the Poro 34B base model into Finnish, then used to train this chat version. We selected only datasets that are available for commercial use and only contain synthetic data if it was gathered in ToS-compliant fashion.
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  English, 40% Finnish, and 20% cross-lingual entries.
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  We finetuned the base model for 3 epochs with a learning rate of 2e-05, warmup
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+ ratio of 0.1, and a global batch size of 48. For full-parameter finetuning, we used 3 nodes (8 GPUs per node). We used the [Alignment Handbook](https://github.com/huggingface/alignment-handbook/)
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+ code for finetuning.
 
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  ## Datasets
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