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@@ -16,11 +16,15 @@ We value:
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  In this organization, you can find RoLLM models, based on different underlying models and in different flavours (i.e., foundational, instruct, or chat variants). There are currently four model collections:
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  - RoLlama2: Romanian models based on Llama2
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  - RoMistral: Romanian models based on Mistral
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- - RoGemma: Romanian models based on Gemma
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  - RoLlama3: Romanian models based on Llama3
 
 
 
 
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- Furthermore, here you can find data used to train and evaluate LLMs in Romanian. Currently, there are two data collections:
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  - SFT datasets: data used for supervised (instruction) finetuning
 
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  - Evaluation datasets: data used for evaluating LLM in Romanian
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  See details in [https://arxiv.org/abs/2406.18266](https://arxiv.org/abs/2406.18266) and [https://arxiv.org/abs/2405.07703](https://arxiv.org/abs/2405.07703).
 
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  In this organization, you can find RoLLM models, based on different underlying models and in different flavours (i.e., foundational, instruct, or chat variants). There are currently four model collections:
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  - RoLlama2: Romanian models based on Llama2
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  - RoMistral: Romanian models based on Mistral
 
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  - RoLlama3: Romanian models based on Llama3
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+ - RoLlama3.1: Romanian models based on Llama3.1
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+ - RoGemma: Romanian models based on Gemma
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+ - RoGemma2: Romanian models based on Gemma2
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+
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+ Furthermore, here you can find data used to train and evaluate LLMs in Romanian. Currently, there are three data collections:
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  - SFT datasets: data used for supervised (instruction) finetuning
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+ - Alignment datasets: data used mainly for Direct Preference Optimization (DPO)
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  - Evaluation datasets: data used for evaluating LLM in Romanian
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  See details in [https://arxiv.org/abs/2406.18266](https://arxiv.org/abs/2406.18266) and [https://arxiv.org/abs/2405.07703](https://arxiv.org/abs/2405.07703).