Llama Poro 2 8B Long Base

Poro 2 Long Instruct is an instruction-following chatbot model with extended context support, created through supervised fine-tuning (SFT) of the Poro 2 Long Base model followed by merging the SFT checkpoint back with the base model to preserve long-context performance. This model is designed for conversational AI applications and instruction following in both Finnish and English, with support for context lengths up to 128K tokens. It was trained on a carefully curated mix of English and Finnish instruction data.

Poro 2 8B Math Reasoning RL Preview is a specialized model focused on mathematical reasoning and problem-solving. This preview model was created through reinforcement learning (RL) on top of the Math Reasoning SFT checkpoint. This model excels at mathematical reasoning tasks but is not optimized for general conversational use or other domains.

Poro 2 8B Math Reasoning SFT Preview is a specialized model focused on mathematical reasoning and problem-solving. This preview model was created through supervised fine-tuning of a context-extended base model. This model excels at mathematical reasoning tasks but is not optimized for general conversational use or other domains.

Note for most users: This is an intermediate checkpoint from our post-training pipeline. Most users should use Poro 2 70B Instruct instead, which includes an additional round of Direct Preference Optimization (DPO) for improved response quality and alignment. This SFT-only model is primarily intended for researchers interested in studying the effects of different post-training techniques.

Note for most users: This is an intermediate checkpoint from our post-training pipeline. Most users should use Poro 2 8B Instruct instead, which includes an additional round of Direct Preference Optimization (DPO) for improved response quality and alignment. This SFT-only model is primarily intended for researchers interested in studying the effects of different post-training techniques.

Poro 2 70B Base is a 70B parameter decoder-only transformer created through continued pretraining of Llama 3.1 70B to add Finnish language capabilities. It was trained on 165B tokens using a carefully balanced mix of Finnish, English, code, and math data. Poro 2 is a fully open source model and is made available under the Llama 3.1 Community License.