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  language:
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  - fi
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  ---
 
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- # Model Card for Model ID
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- <!-- Provide a quick summary of what the model is/does. -->
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- Instruct finetuned model from https://huggingface.co/Finnish-NLP/llama-7b-finnish for 2 epochs using 11014 samples combined from following sources:
 
 
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  LIMA from https://github.com/TurkuNLP/finnish-instructions
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  Dolly from https://github.com/TurkuNLP/finnish-instructions
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  OASST from https://github.com/TurkuNLP/finnish-instructions
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  Heavily filtered version of Ultrachat + deepl translations from https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized/viewer/default/train_sft
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  ### How to use
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  Here is an example of using this model with Unsloth with some generation arguments you can modify:
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  ### Limitations and bias
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- The training data used for this model contains a lot of content from the internet, which is far from neutral. Therefore, the model can have biased predictions. This bias will also affect all fine-tuned versions of this model.
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-
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- To reduce toxic content, training data was filtered with a toxicity classifier but it cannot truly eliminate all toxic text.
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  ### Finetuning
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  language:
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  - fi
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  ---
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+ ## Model description
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+ This is an early v0.1 version release of our Instruct finetuned model from https://huggingface.co/Finnish-NLP/llama-7b-finnish
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+ Model was trained for 2 epochs using 11014 samples and for this release we chose checkpoint at 2500/4048 steps.
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+
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+ For finetuning we used mix of following datasources:
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  LIMA from https://github.com/TurkuNLP/finnish-instructions
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  Dolly from https://github.com/TurkuNLP/finnish-instructions
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  OASST from https://github.com/TurkuNLP/finnish-instructions
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  Heavily filtered version of Ultrachat + deepl translations from https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized/viewer/default/train_sft
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+
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  ### How to use
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  Here is an example of using this model with Unsloth with some generation arguments you can modify:
 
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  ### Limitations and bias
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+ The training data used for this model contains a lot of content from the internet, which is far from neutral.
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+ Therefore, the model can have biased predictions. This bias will also affect all fine-tuned versions of this model.
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+ To reduce toxic content, the pretrained version of thiis model was trained with dataset filtered with a toxicity classifier but it cannot truly eliminate all toxic text.
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  ### Finetuning
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